WOK - A SIMULATION MODEL FOR DFS AND LINK ADAPTATION …

WOK - A SIMULATION MODEL FORDFS AND LINK ADAPTATION IN

IEEE 802.11A WLAN

Magnus JansonMagnus Karlsson

LiTH-ISY-EX-3460-2004

Linköping 2004-01-30

WOK - A SIMULATION MODEL FORDFS AND LINK ADAPTATION IN

IEEE 802.11A WLAN

Master Thesis in Data Transmission

Department of Electrical Engineering,

Linköping University

by

Magnus JansonMagnus Karlsson

LiTH-ISY-EX-3460-2004

Supervisor: Mikael Rudberg

Examiner: Ulf Henriksson

Linköping, 30 January 2004.

Avdelning, Institution Division, Department

Institutionen för systemteknik 581 83 LINKÖPING

Datum Date 2004-01-30

Språk Language

Rapporttyp Report category

ISBN

Svenska/Swedish X Engelska/English

Licentiatavhandling X Examensarbete

ISRN LITH-ISY-EX-3460-2004

C-uppsats D-uppsats

Serietitel och serienummer Title of series, numbering

ISSN

Övrig rapport ____

URL för elektronisk version http://www.ep.liu.se/exjobb/isy/2004/3460/

Titel Title

WOK - en simuleringsmodell för DFS och länkadaption i IEEE 802.11a WLAN WOK - A Simulation Model for DFS and Link Adaptation in IEEE 802.11a WLAN

Författare Author

Magnus Janson and Magnus Karlsson

Sammanfattning Abstract With the 1999 introduction of IEEE 802.11b, the 2.4 GHz Wireless Local Area Network (WLAN) standard, the WLAN market finally began to experience the growth levels that had been expected for so long. Now, 5 GHz solutions, with the IEEE 802.11a standard leading the way, offer higher throughput and more efficient use of the spectrum. Just as the 2.4 GHz band, the 5 GHz band is unlicensed. A common concern to all unlicensed bands is interference between devices using the spectrum. Furthermore, in the 5 GHz band, WLAN cells can interfere with radar systems operating at the same frequencies. This report describes a software model, WOK, suitable for simulations of IEEE 802.11a WLANs operating in various environments and under various ambient conditions. The WOK model can be configured extensively with respect to topology, traffic behavior, channel models, signal attenuation, interference sources and radar systems. Further, the concepts of Dynamic Frequency Selection (DFS) and link adaptation are explored in the context of the IEEE 802.11a standard. DFS aims to avoid channels occupied by radar systems and link adaptation aims to maximize the throughput based on current ambient conditions. A DFS algorithm and a link adaptation algorithm are implemented at the Medium Access Control (MAC) layer and evaluated using the WOK model.

Nyckelord Keyword simulation, model, DFS, Dynamic Frequency Selection, link adaptation, algorithm, WLAN, wireless, MAC, PHY, IEEE 802.11a, IEEE 802.11h, access point, transmission rate, radar, noise, interference, SNR, OMNeT++

TABLE OF CONTENTS

1 Abbreviations and Ackronyms 1

2 Introduction 32.1 Purpose. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32.2 Company Description . . . . . . . . . . . . . . . . . . . . . . 32.3 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4

2.3.1 IEEE 802.11 WLAN . . . . . . . . . . . . . . . . . . . . 42.3.2 IEEE 802.11 Layers. . . . . . . . . . . . . . . . . . . . . 52.3.3 WLAN Market. . . . . . . . . . . . . . . . . . . . . . . . . 82.3.4 DFS and Link Adaptation . . . . . . . . . . . . . . . . 9

2.4 Problem Description . . . . . . . . . . . . . . . . . . . . . . 102.4.1 MAC . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 102.4.2 PHY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 102.4.3 The Wireless Medium . . . . . . . . . . . . . . . . . . 102.4.4 Limitations . . . . . . . . . . . . . . . . . . . . . . . . . . . 12

3 Method 133.1 Phases. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 133.2 Important Decisions . . . . . . . . . . . . . . . . . . . . . . . 143.3 Important Tools . . . . . . . . . . . . . . . . . . . . . . . . . . 143.4 OMNeT++ . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14

3.4.1 General Information. . . . . . . . . . . . . . . . . . . . 153.4.2 Modules . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 153.4.3 Communication and Timing . . . . . . . . . . . . . 163.4.4 Parameters . . . . . . . . . . . . . . . . . . . . . . . . . . . 16

4 The WOK Model 174.1 General Description . . . . . . . . . . . . . . . . . . . . . . . 174.2 The Wireless Medium . . . . . . . . . . . . . . . . . . . . . 19

4.2.1 Implementation in the WOK Model . . . . . . . 194.3 PHY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27

4.3.1 Implementation of Traffic Handling . . . . . . . 284.3.2 Implementation of Measurements . . . . . . . . . 30

4.4 MAC . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 334.4.1 MAC Functions in the WOK Model . . . . . . . 33

4.4.2 Modeling Approach . . . . . . . . . . . . . . . . . . . . 404.4.3 MAC Frame Implementation. . . . . . . . . . . . . 414.4.4 MAC Module Overview . . . . . . . . . . . . . . . . 444.4.5 MAC Module Implementation . . . . . . . . . . . 45

4.5 Traffic Generation . . . . . . . . . . . . . . . . . . . . . . . . 484.6 Improvements . . . . . . . . . . . . . . . . . . . . . . . . . . . 504.7 Comments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50

5 Dynamic Frequency Selection 515.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51

5.1.1 Problem Description . . . . . . . . . . . . . . . . . . . 515.1.2 Objectives . . . . . . . . . . . . . . . . . . . . . . . . . . . 535.1.3 Limitations . . . . . . . . . . . . . . . . . . . . . . . . . . . 53

5.2 Regulatory Requirements. . . . . . . . . . . . . . . . . . . 545.3 Prerequisites for DFS in the MAC. . . . . . . . . . . . 55

5.3.1 Local Measurements . . . . . . . . . . . . . . . . . . . 555.3.2 Measurement Requesting and Reporting. . . . 555.3.3 Quiet Periods . . . . . . . . . . . . . . . . . . . . . . . . . 565.3.4 Channel Switching. . . . . . . . . . . . . . . . . . . . . 57

5.4 DFS Support in the IEEE 802.11h Draft . . . . . . . 575.4.1 Spectrum Management Frames . . . . . . . . . . . 575.4.2 Measurement Data Handling . . . . . . . . . . . . . 58

5.5 Integration in the IEEE 802.11a. . . . . . . . . . . . . . 585.5.1 Location of DFS Extensions . . . . . . . . . . . . . 595.5.2 IEEE 802.11h Interface Extensions . . . . . . . . 605.5.3 Further Interface Extensions . . . . . . . . . . . . . 625.5.4 Overview of DFS Primitives . . . . . . . . . . . . . 63

5.6 Implementation of DFS Procedures. . . . . . . . . . . 645.6.1 Measurement Requesting and Reporting. . . . 645.6.2 Quiet Periods . . . . . . . . . . . . . . . . . . . . . . . . . 655.6.3 Quiet Measurements . . . . . . . . . . . . . . . . . . . 665.6.4 Channel Switching. . . . . . . . . . . . . . . . . . . . . 675.6.5 STA Rescue Operation . . . . . . . . . . . . . . . . . 68

5.7 A DFS Algorithm. . . . . . . . . . . . . . . . . . . . . . . . . 695.7.1 General Structure . . . . . . . . . . . . . . . . . . . . . . 695.7.2 The Start-Up Phase . . . . . . . . . . . . . . . . . . . . 695.7.3 The Normal Operation Phase. . . . . . . . . . . . . 715.7.4 The Channel Quality Measure . . . . . . . . . . . . 775.7.5 Late Additions . . . . . . . . . . . . . . . . . . . . . . . . 78

5.8 Evalutation of the Algorithm . . . . . . . . . . . . . . . . 795.8.1 Scenarios and Topologies . . . . . . . . . . . . . . . 795.8.2 Performance Measures. . . . . . . . . . . . . . . . . . 815.8.3 DFS Overhead . . . . . . . . . . . . . . . . . . . . . . . . 82

5.8.4 DFS Radar Detection and Avoidance . . . . . . 865.8.5 ETSI Requirements . . . . . . . . . . . . . . . . . . . . 90

5.9 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 935.10 Comments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94

6 Link Adaptation 956.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 95

6.1.1 Purpose . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 956.1.2 Problem Description . . . . . . . . . . . . . . . . . . . 956.1.3 Limitations . . . . . . . . . . . . . . . . . . . . . . . . . . . 98

6.2 Integration in the WOK Model . . . . . . . . . . . . . . 996.2.1 A Link Adaptation Algorithm . . . . . . . . . . . 100

6.3 Simulations . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1036.3.1 Environments . . . . . . . . . . . . . . . . . . . . . . . . 1036.3.2 General Settings. . . . . . . . . . . . . . . . . . . . . . 1056.3.3 Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 107

6.4 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1156.5 Comments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 116

7 Final Comments 117

References 118

1

1ABBREVIATIONS AND ACKRONYMS

ACK Acknowledgement frameAP Access PointAWGN Additive White Gaussian NoiseBPSK Binary Phase Shift KeyingBSS Basic Service SetCCA Clear Channel AssessmentCEPT European Conference of Postal and Telecommunications

AdministrationsCRC Cyclic Redundancy CheckCSMA/CA Carrier Sense Multiple Access with Collision AvoidanceCTS Clear To SendCW Contention WindowDCF Distributed Coordination FunctionDFS Dynamic Frequency SelectionDIFS Distributed Interframe SpaceDPLE Distance Power Law ExponentDS Distribution SystemEIFS Extended Interframe SpaceESS Extended Service SetETSI European Telecommunications Standards InstituteFAF Floor Attenuation FactorFCS Frame Check SequenceFSM Finite State MachineIEEE Institute of Electrical and Electronic EngineersIP Internet Protocol

2 WOK - A Simulation Model for DFS and Link Adaptation in IEEE 802.11a WLAN

JPEG Joint Photographic Experts GroupLLC Logical Link ControlMAC Medium Access ControlMIB Management Information BaseMLME MAC Layer Management EntityMMPDU MAC Management Protocol Data UnitMPDU MAC Protocol Data UnitMSDU MAC Service Data UnitNAV Network Allocation VectorNIC Network Interface CardOFDM Orthogonal Frequency Division MultiplexingOSI Open System InterconnectionPAF Partition Attenuation FactorPHY Physical layerPLCP PHY Layer Convergence ProcedurePLME PHY Layer Management EntityPRF Pulse Repetition FrequencyQAM Quadrature Amplitude ModulationQPSK Quaternary Phase Shift KeyingRSS Received Signal StrengthRSSRI Received Signal Strength Relative IndicationRTS Request To SendSAP Service Access PointSDL Specification and Description LanguageSIFS Short Interframe SpaceSME Station Management EntitySNR Signal-to-Noise RatioSTA Mobile stationTBTT Target Beacon Transmission TimeTCP Transmission Control ProtocolTPC Transmit Power ControlTU Time UnitUML Unified Modeling LanguageWLAN Wireless Local Area NetworkWM WirelessMedium moduleWOK (Optional interpretation)WRC World Radio Conference

3

2INTRODUCTION

2.1 PURPOSE

The main goal with this master thesis is to build a software model based on aWireless Local Area Network (WLAN) standard, that is ratified by the Insti-tute of Electrical and Electronic Engineers (IEEE), called IEEE 802.11a.Like other general network nodes, the architecture of a node defined by thisstandard can be described by certain abstract layers. One such layer is theMedium Access Control Layer (MAC). The software model in this masterthesis should be appropriate for simulation of two different methods used onMAC level, namely Dynamic Frequency Selection (DFS) and link adaptation.Thus, a realistic representation of nodes, communication and surroundingenvironment is of great concern. In order to confirm that the goal is reached aDFS algorithm and a link adaptation algorithm are implemented and evalu-ated.

This master thesis is an assignment on behalf of Infineon Technologies Wire-less Solutions Sweden AB.

2.2 COMPANY DESCRIPTION

Infineon Technologies Wireless Solutions Sweden AB in Linköping is part ofInfineon Technologies AG. The company is spread world wide, but has itshead office in Munich, Germany. Infineon Technologies Wireless SolutionsSweden AB in Linköping was previously a part of Ericsson Microelectronics


AB, but was bought by Infineon Technologies AG and is now a part of theirResearch and Development unit.

Infineon Technologies Wireless Solutions Sweden AB in Linköping hastoday 12 employees. Their expertise area is processor-based integrated cir-cuits and advanced mixed signal circuits. All of their employees have a Mas-ter of Science in Engineering Degree and some of them have a DoctorDegree.

2.3 BACKGROUND

This chapter provides the background of this report. First, some theoreticalbackground is given, introducing the concepts and terminology of WLANs ingeneral and the IEEE 802.11 standards in particular. Then, an overview of thecurrent WLAN market is provided, justifying the emphasis on the IEEE802.11a standard [7]. Finally, the concepts of DFS and link adaptation areintroduced.

2.3.1 IEEE 802.11 WLAN

Wireless networking is a rapidly evolving technology for connecting comput-ers. WLANs are designed for use in a limited geographical area (homes,office buildings, campuses), and its primary challenge is to mediate access toa shared communication medium - in this case, the radio channel.

The WLAN technology considered in this report is based on the standardsproposed and ratified by IEEE. The original standard, IEEE 802.11 [1], wasproposed in 1997. Since then, a number of variants and extensions have beenadded. Such standards include IEEE 802.11b and IEEE 802.11a, providinghigher data transmission rates. Aspects discussed in this chapter are generaland apply on all standards within the IEEE 802.11 family.

An IEEE 802.11 WLAN is based on a cellular architecture, i.e., the system isdivided into cells. Each cell, or Basic Service Set (BSS), is controlled by anAccess Point (AP). Access points can be connected through a DistributionSystem (DS), typically an Ethernet LAN. The whole interconnected WLANincluding different cells, their respective access points, and the distributionsystem is called an Extended Service Set (ESS). A mobile station (STA) com-municates with other nodes within the ESS via its access point. Figure 2.1

Chapter 2 - Introduction 5

shows a typical IEEE 802.11 WLAN, with the components described above.

Figure 2.1: An IEEE 802.11 WLAN

Within an IEEE 802.11 WLAN, mobile stations can move from one cell toanother without loosing connection. This process is called roaming.

2.3.2 IEEE 802.11 LAYERS

The architecture of a general network node can be described using the OpenSystem Interconnection (OSI) reference model, depicted in figure 2.2 [23].The OSI model partitions network functionality into seven layers. Layerfunctionality is implemented by one or more protocols, utilizing the servicesprovided by lower layers.

AP

AP

STA

STA

STA

STA

STA

DS

BSS

BSS

ESS


Figure 2.2: The OSI reference model

A WLAN technology is defined by the two lowest layers in the OSI model,i.e., the data link layer and the physical layer.

The data link layer provides the transport of data across the physical link. Indoing so, the data link layer is concerned with physical addressing, networkaccess, error notification, flow control, etc. The data entity handled at thislayer is a collection of bits called a frame. In standards within the IEEE 802project1, the data link layer is divided into two sublayers, namely the MediumAccess Control (MAC) layer and the Logical Link Control (LLC) layer.

In IEEE 802.11 standards, the MAC layer coordinates the access to theshared radio channel among IEEE 802.11 devices, utilizing protocols thatenhance communications over the unreliable wireless medium. All IEEE 802LANs use the same LLC layer, as specified by the IEEE 802.2 standard. Thismakes the MAC layer implementation transparent for layers above the data

1. The IEEE 802 standards committee has developed a family of standardsfor LANs. The most known are the standards for Ethernet (IEEE 802.3),Token Ring (IEEE 802.5), and WLAN (IEEE 802.11).

Node

Physical

Data link

Network

Transport

Session

Presentation

Application

Medium

LLC (802.2)

MAC (802.11)

PHY (802.11)


link layer.

The physical layer, also called the PHY layer, handles the transmission of rawbits over the wireless medium. In IEEE 802.11 standards, the PHY layerdefines physical aspects such as the signal modulation technique and fre-quency spectrum used.

Figure 2.3 illustrates the general architecture of an IEEE 802.11 station andits interfaces.

Both MAC and PHY layers conceptually include management entities,namely the MAC Layer Management Entity (MLME) and PHY Layer Man-agement Entity (PLME). These entities provide services related to manage-ment, i.e., activities that are not directly related to the transmission andreception of data. For example, the MLME handles the roaming process.

Interaction between layers and entities is specified by the IEEE 802.11 stand-ards, via Service Access Points (SAPs) across which defined logical primi-tives are exchanged.

The Station Management Entity (SME) is layer-independent, i.e., it is consid-ered residing in a separate management plane. The exact functions of theSME is not specified by the standard but would typically implement high-level management protocols based on services provided by the MLME andthe PLME.

Figure 2.3: An IEEE 802.11 station architecture

MAC SAP

PHY SAP

MAC

PHY

LLC SME

MLME SAP

PLME SAP

PLME SAP

MLME

PLME


2.3.3 WLAN MARKET

The WLAN market has increased dramatically the last couple of years. Whenthe IEEE introduced the IEEE 802.11b standard in 1999, the WLAN marketfinally began to experience the growth levels that had been expected for solong.

The IEEE 802.11a standard was proposed and ratified at the same time as theIEEE 802.11b standard. The two differentiate greatly in the PHY layer andare thus not compatible. The IEEE 802.11b standard uses the unlicensed 2.4GHz frequency band and IEEE 802.11a uses the unlicensed 5 GHz frequencyband.

Until now, the IEEE 802.11b standard has been dominating the market,because of its certified interoperability and declining development costs. Themass adoption of the IEEE 802.11a standard has been delayed by several fac-tors, such as its “cutting edge” as a new and leading technology. Further,while the IEEE 802.11b standard and its operating channels have beenaccepted globally and are supported by many global networking companies, 5GHz band allocations and regulations have been a subject of disputes in andbetween several countries. This has been an important consideration for mul-tinational companies and international travelers considering a WLAN pur-chase. [21]

Nevertheless, the IEEE 802.11a standard is expected to dominate the WLANmarket in the near future. This is because of a number of reasons.

First, the users of an IEEE 802.11a network are provided a raw data rate of upto 54 Mbps, in comparison with up to 11 Mbps in an IEEE 802.11b network.Secondly, because of more efficient use of the spectrum, IEEE 802.11a sup-ports up to 19 non-overlapping channels1. The IEEE 802.11b standard pro-vides only three such channels. This significantly increases the throughputthe WLAN can deliver in a certain area. Ideally, the total data rate providedby the IEEE 802.11a standard in a single area is 1026 Mbps (54 Mbps * 19networks). The corresponding figure for the IEEE 802.11b standard is 33Mbps (11 Mbps * 3 networks).

Further, the global spectrum unification problem seems to have come to asolution. At the World Radio Conference (WRC) 2003 in Geneva, the US andEurope became united about a global increase of the spectrum allocated to

1. Presently, 19 channels are supported in Europe while 12 channels aresupported in the US.


WLAN. Specifically, this means that the 5 GHz band will be allocated 450MHz of spectrum (compared to 83.5 MHz for the 2.4 GHz band) and pro-vided with global regulations, making the use of the same equipment in thewhole world possible. Previously, this process has been held back mainly bythe Pentagon, wanting to protect their military radar systems against interfer-ence. In the agreements discussed at present, i.e., in June 2003, this problemis addressed by introducing regulatory requirements for transmit power limi-tations and Dynamic Frequency Selection (DFS) in WLAN technologiesoperating in the 5 GHz band. [16]

2.3.4 DFS AND LINK ADAPTATION

In the context of WLAN, an implementation of DFS is expected to detect andavoid frequencies occupied by so called primary users, notably radar sys-tems. DFS has never been introduced on such large scale for a public serviceas it will be now because of the WRC agreement. This implies the need forthe exploration of DFS algorithms in the context of the IEEE 802.11a stand-ard. IEEE has initiated the work with an enhancement to the IEEE 802.11astandard, namely the IEEE 802.11h draft supplement, introducing some sup-port for DFS. The DFS-related work of this report is based on this draft.

A common concern to all unlicensed bands is interference between devicesusing the spectrum. This is a valid concern and has historically affected allunlicensed bands; 49 MHz, 330 MHz, 900 MHz, 2.4 GHz, etc. Hence, therewill never be an unlicensed band that is indefinitely free from interference.Given the cost of licensed spectrum free spectrum is, and always will be, veryattractive. Therefore, the claim that a technology utilizes “un-crowded” spec-trum is not relevant. [21]

This implies the need for exploration of link adaptation algorithms in theIEEE 802.11a standard. Link adaptation algorithms are used to adapt thetransmissions to present ambient conditions, e.g., by decreasing the rate wheninterference increases. The purpose is to maximize throughput and minimizethe number of erroneous transmissions.

In order to enable the exploration of both DFS and link adaptation techniquesin IEEE 802.11a networks, a simulation model is needed. Therefore, theWOK model has been developed.


2.4 PROBLEM DESCRIPTION

As with any model in general, one of the primary goals with the WOK modelis to make it realistic. Further, it should be extendable. A major problem is tofind a suitable level of abstraction and to identify aspects significant for DFSand link adaptation.

Modeling traffic over a wireless medium is also a basic concern. The mode-ling problem may be decomposed into several sub-issues by describing theproblems for each layer in IEEE 802.11 and the wireless medium itself.

2.4.1 MAC

On MAC level the ultimate problem is to find and implement the functional-ity, according to the IEEE 802.11 standard [1], required to model normalWLAN traffic, DFS and link adaptation. What is meant by normal WLANtraffic has to be defined.

2.4.2 PHY

On PHY level traffic synchronization is the ultimate problem. It is importantto figure out how frames should be taken care of at reception from the wire-less medium, before forwarding to MAC and vice versa. Timing is importantin order to have realistic simulations. For how long will reception and trans-mission of a certain frame proceed? If one or more frames arrive before thereception of a previous frame has ended a collision occurs. A problem is tohandle collisions in an appropriate and realistic way. It is important for MACto know whether the wireless medium is busy or idle. This is a task for PHYto find out, but how?

2.4.3 THE WIRELESS MEDIUM

There are certain important issues concerning the wireless medium that haveto be modeled. These issues are presented below.

SIGNAL LOSS

The signal strength of a transmitted frame decreases along the path to the


receiver, due to the distance between the transmitter and the receiver as wellas intermediate obstacles1. This is called signal loss or attenuation of thetransmitted frame.

The task is to find out how the signal loss of a transmitted frame is modeled.

HIDDEN NODES

There is a problem known as the hidden node problem. Figure 2.4 demon-strates this problem. Node C is hidden to node A, because it is situated too faraway from node A and won’t hear the transmission from node A. A collisionmay occur at node B if node C begins to transmit a frame before the transmis-sion from node A has ended.

How could we decide that a node is hidden in the WOK model?

Figure 2.4: Hidden node problem

NOISE

Noise could be present both at the transmitter and at the receiver. When thenoise level is too high the receiver might do incorrect detections of some bits

1. Furniture, walls etc. are examples of intermediate obstacles.

CA

B

hidden node

DATA


in a transmitted frame. Bit errors are generally more likely to occur if theframes are sent at high data transmission rate.

There is a phenomenon known as multipath interference. A direct transmittedsignal may be weakened in two different ways. One way is due to multipathfading, when the signal is mixed with reflecting signals. Another way is dueto intersymbol interference, when the signal is mixed with echoes of a previ-ous signal.

A problem is to find out how to generate noise and how noise affects theframes by introducing bit errors. Another problem is to find out how to modelmultipath interference and its consequences.

2.4.4 LIMITATIONS

At Infineon a WLAN is defined by the IEEE standards 802.11a/b/g/e/f/h/i.The WOK model focuses on the IEEE 802.11a standard. Further, the WOKmodel:

• doesn’t include a distribution system, i.e. communication between twoaccess points is not supported.

• consists of stationary access points and stations.

• doesn’t support roaming.

13

3METHOD

This chapter aims at describing the process of our work, important decisionswe take and important tools we use. The most important tool is brieflydescribed in a separate sub-chapter at the end.

3.1 PHASES

Our work is informally divided into several phases. These are presented inchronological order below:

Table 3.1. Phases in chronological order

Phase Brief description

Pre study Theoretical studies and other research needed are performed.

Definition A requirement specification is written.

Design A design specification is written.

Implementation The WOK model is implemented.

Evaluation andcompletion

DFS and link adaptation algorithms are simulated and evaluated.Major parts of this report are written.


3.2 IMPORTANT DECISIONS

The most important decision we take is when we decide which tool we aregoing to use for implementation. We decide to use the OMNeT++ tool,because it is a powerful and a quite unique non-commercial tool for modelingcomputer networks. Lots of useful built-in functions with huge extendablecapabilities are provided. One of its basic concepts as being a discrete eventsimulator is well-known. Furthermore, it is used with the well known C++language. Other similar non-commercial tools are PARSEC, SMURPH, NS,Ptolemy, NetSim++, C++SIM and CLASS. Other similar commercial toolsare OPNET and COMNET III.

Another important decision we take is when we choose to follow the Specifi-cation and Description Language (SDL) formal description, provided in theIEEE 802.11 standard [1], for implementation of MAC functionality. Detailsabout the SDL description and the reason for choosing this description areprovided in chapter “MAC” on page 33.

3.3 IMPORTANT TOOLS

A table of the most important tools we use is presented below:

Table 3.2. Important tools

3.4 OMNET++

This chapter is a brief description of the tool we use for implementation andsimulation of the WOK model.

Tool Usage

OMNeT++ 2.2 It is used for implementation and simulation of the WOK model.

Matlab 6.0 It is used for DFS and link adaptation evaluation purposes andfor being able to implement parts of the WOK model.

FrameMaker 6.0 It is used for writing this report.

Chapter 3 - Method 15

3.4.1 GENERAL INFORMATION

OMNeT++ is a non-commercial object-oriented discrete event simulationtool, powerful for modeling computer networks. It is based on and workswith C++. As in most non-commercial tools, the source code in OMNeT++ isavailable to the user. This makes it possible for a user to examine the simula-tion kernel. Simulation models in OMNeT++ are built up by modules. Inorder to make the inside of a model visible to the user and facilitate debug-ging a graphical user interface is provided.

3.4.2 MODULES

Modules in OMNeT++ may be hierarchically nested. An advantage of hierar-chically nested modules is that a top-down design is directly applicable. Thetop level in the hierarchy, the system module, contains several sub-modules.The lowest level in a nested module is called a simple module and containsthe algorithm of the module. There might be several algorithms running inparallel for each module. Figure 3.1 shows an example of the modular struc-ture property. An algorithm is implemented by the user in C++, by using theOMNeT++ simulation class library, see [8] for details. A simple module maybe implemented using the built-in support for Finite State Machines (FSMs),which work very much like SDLs.

Figure 3.1: Module hierarchy in OMNeT++

SYSTEM MODULE

COMPOUND MODULE

SIMPLE MODULES


3.4.3 COMMUNICATION AND TIMING

Communication between modules is performed via message passing. When amessage is received by a module an event occurs and the local simulationtime of that module advances. A message sent from a certain module may beaddressed to itself. Such a message is called a self message and is used toimplement a timer.

3.4.4 PARAMETERS

A useful feature in OMNeT++ is parameters.

Parameters are used for several purposes, e.g.:

• for module communication

• to parameterize module topology

• to customize simple module behaviour

Parameters may serve as shared variables, as information carriers in messagesor as interconnection characteristics. A module topology parameter might forexample denote the number of stations present in a simulation. The algorithmin a simple module may need other information than from messages beingreceived. An example of that could be when logging should start and stop fora certain module during a simulation.

17

4THE WOK MODEL

This chapter will describe the WOK model implemented. It is introducedwith a general description. After that, descriptions of the larger functionalblocks of the WOK model are provided in separate sub-chapters.

4.1 GENERAL DESCRIPTION

The WOK model is implemented in OMNeT++, see chapter “OMNeT++” onpage 14. An overview of the WOK model is presented in figure 4.1.

Functionality is integrated within modules, communicating with each otherby message passing. Both access points and stations, denoted ap[] and sta[] infigure 4.1, are provided. Message passing between each pair of nodes will govia the WirelessMedium module, denoted WM in figure 4.1. The purpose ofthis form of distribution is to imitate reality. A radar generator, implementedfor DFS purposes, and an interference generator are separate modules con-nected to the WirelessMedium module. Further details about them are givenin chapter “The Wireless Medium” on page 19.


Figure 4.1: Overview of the WOK model

Access points and stations are based on the IEEE 802.11a standard [7]. Theirinternal structure is depicted in figure 4.2.

Figure 4.2: Structure within a station / access point

A user manual of the WOK model is supplied in [22].

WM

...

...

ap[0] ap[m]

sta[0] sta[n]

WOK

RadarInter-

ference

Station / Access point

MAC

PHY

SME

TrafficHandler

Chapter 4 - The WOK Model 19

4.2 THE WIRELESS MEDIUM

The WirelessMedium module is implemented in order to establish uniquelinks1 between each pair of nodes in the WOK model. It includes handlingand distribution of frames, noise, interference and radar signals at differentfrequency channels as well as decisions of how sent frames are affected at thereceiver.

4.2.1 IMPLEMENTATION IN THE WOK MODEL

DISTANCE AND ATTENUATION DETERMINATION

All nodes have fixed positions and fixed transmit power levels during a simu-lation in the WOK model. Cartesian coordinates and transmit power levelsare represented by configurable parameters.

Distance between a pair of nodes in the WOK model is computed using thecartesian coordinates for each node respectively. This measure is used forattenuation computations. Attenuation is neccessary to model as it affects thesignal strength of a received frame. If the signal strength of a frame is toofaint the frame is perhaps not detected at the receiver. The receiver has thenbecome a hidden node, see chapter “PHY” on page 27.

The attenuation formula that is used in the WOK model is taken from a studyby Pop, Croitorum and Antohi [5] and is applicable for indoor as well as foroutdoor environments. It is a function of frequency, distance and some otherelements called distance power law exponent, partition attenuation factor andfloor attenuation factor. Default values for these elements are represented byparameters in the WOK model, according to table 4.1. It is also possible toconfigure links individually regarding attenuation, using a separate input file.

1. The number of links is if n is the sum of the number of STAs and

APs.

n2


Table 4.1. Attenuation parameters

The WOK model attenuation formula:

A : attenuation [dB]f : frequency [MHz]d : distance [meters]DPLE : Distance Power Law Exponent [dB]PAF : Partition Attenuation Factor [dB]FAF : Floor Attenuation Factor [dB]

This implementation makes it possible to simulate conceivable obstructionsbetween two nodes. Two links with the same distances may have differentattenuations. It makes them unique.

LINK BUDGET

Assume that the transmit power is 1 and that we have an attenuationof . The antenna is assumed to be isotropic, i.e. the antenna spreadsenergy in every direction with the same power density. Let us denote thereceived power . The received power computation is implementedas . Also assume that the power of the noise has been esti-mated to .

Parameter Description

defaultDistancePowerLawExponent Affects the weight of distance between twostations in the attenuation formula. [dB]

defaultPartitionAttenuationFactor Sum of partition losses of a signal due toe.g. construction materials of the walls and

other partitions within a building. [dB]

defaultFloorAttenuationFactor Sum of multifloor path losses. [dB]

1. The dBm unit is used instead of the mW unit, because it is more practi-cal. The relationship between these two units is:

.

A 27.56– 20 f( )log⋅ 10 DPLE d( )log⋅ ⋅ PAF FAF+ + + +=

PTX dBm

[dBm] 10 [mW ]( )log⋅=

A dB

PRX dBm

PRX PTX A–=N dBm


The computation of 1 at the receiver is implemented as, see [6]. This link budget implementation is simplified

for our purpose. Focus is laid on the most important fact, that SNR at thereceiver varies due to changing noise levels and attenuation between transmit-ter and receiver.

PROBABILITY OF FRAME ERROR

The following discussion makes an assumption of noise as white and gaus-sian. All bit errors in a frame are independent.

The frame error rate (probability of frame error), , is easily com-puted given the bit error rate, , and the length of the frame, . Theformula used in the WOK model is given below.

is given as the number of octets2 sent from MAC to PHY prior totransmission to the wireless medium, see chapter “PHY” on page 27. How

is determined is explained below.

CHANNEL MODELS

Implementation of frame error generation in the WOK model is based onsimulation results from a confidential internal document3 at Infineon. Thisdocument shows packet error rates4 from simulations with five different chan-nel models, see table 4.2. A channel model is used in order to model a certainenvironment regarding multipath interference.

1. Signal-to-Noise Ratio (SNR) is a measure of the strength of the receivedsignal compared to the current noise level. It is defined as:

.2. One octet is defined as one byte.3. Diagrams of packet error rates vs. SNR values are plotted for given data

transmission rates and channel models.4. A packet in this context represents a frame with a static length of 1000

bytes.

SNR

SNR [dB] 10 signal power noise power⁄( )log⋅=

SNR PTX N– A–=

Pe frame,Pe bit, L frame

Pe frame, 1 1 Pe bit,–( )8 L frame⋅( )

–=

L frame

Pe bit,


Table 4.2. WOK channel models1

In order to generate a certain packet error rate in the WOK model, one of thelinearly interpolated functions stored in a table is used. Which function isused depends on channel model, data transmission rate and SNR value. Usingthe formula for computing probability of frame error, is determinedand a re-computation gives the real frame error rate for a frame oflength bytes, as previously described.

NOISE AND INTERFERENCE MODELING

The ideas behind modeling noise in the WOK model are to let

• the wireless medium be considered busy due to high noise levels.

• SNR vary in time at different frequency channels, due to interference.

The noise levels in the WOK model are equal at all nodes at the same time. Ifthe noise level is higher than a certain threshold value, the wireless medium isconsidered busy, see chapter “PHY” on page 27 for details.

No channels are indefinitely free from noise, thus a constant backgroundnoise affecting all channels simultaneously is implemented in the WOKmodel. The background noise level is represented by a parameter noise-Level.

Interference signals are generated in the Interference module and distributed

Channel Model Description

AWGN Additive White Gaussian Noise channel

A ETSI channel model representing a typical office environment

C ETSI channel model representing an open office environment(greater delay spread than channel model A)

E ETSI channel model representing an open office environment(greater delay spread than channel model C)

RAYLEIGH Rayleigh fading channel

1. Some of the channel models are defined by the European Telecommuni-cations Standards Intitute (ETSI).

Pe bit,Pe frame,

L frame


to the WirelessMedium module via message passing, see figure 4.1. Suchmessages hold the following parameters:

• Bandwidth [MHz]

• Duration [ms]

• Center frequency [MHz]

• Power level [dBm]

When these messages are distributed and which parameter values they holdare deterministically or randomly determined by means of parameters tied tothe Interference module, see table 4.3.

In real life noise and interference are of more complex nature. The main ideabehind the WOK model representation is based on the fact that even though acertain channel is affected by interference, adjacent channels do not necessar-ily have to be affected.

When a certain interference signal occurs is determined from a uniform dis-tribution of the interval bounded by the parameters intervalLower-Limit and intervalUpperLimit. This representation makes it possibleto let the noise level switch more or less often. Parameters determining inter-ference signal characteristics are drawn from a normal distribution, princi-pally in order to let certain values be more likely than others.


Table 4.3. Interference generator parameters


interferenceON Interference generation is switched on/off.{true/false}

deterministicON Deterministic interference according to settings in fileinterferenceFile (see below) is switched on/off.

{true/false}

randomON Random interference is switched on/off.{true/false}

bandwidthMean Mean value in a normal distribution of the interferencesignal bandwidth. [MHz]

bandwidthDeviation Deviation value in a normal distribution of theinterference signal bandwidth. [MHz]

durationMean Mean value in a normal distribution of the interferencesignal duration. [ms]

durationDeviation Deviation value in a normal distribution of theinterference signal duration. [ms]

powerMean Mean value in a normal distribution of the interferencesignal power. [dBm]

powerDeviation Deviation value in a normal distribution of theinterference signal power. [dBm]

frequencyMean Mean value in a normal distribution of the centerfrequency of the interference signal. [MHz]

frequencyDeviation Deviation value in a normal distribution of the centerfrequency of the interference signal. [MHz]

intervalLowerLimit Lower limit in a uniform distribution of the intervalbetween generation of interference signals. [ms]

intervalUpperLimit Upper limit in a uniform distribution of the intervalbetween generation of interference signals. [ms]

changeFrequencyInterval Interval when the center frequency is changed to anotheruniformly distributed frequency. [s]

interferenceStart Time when interference generation should start. [s]

interferenceStop Time when interference generation has to be stopped. [s]

interferenceFile File that defines deterministic noise generation. [string]


A radar signal or an interference signal that comes into the WirelessMediummodule may change the noise level on a certain frequency channel. The high-est signal strength of a present radar signal or interference signal on a certainchannel is the noise level of that channel, see figure 4.3. If a channel is neitheraffected by a radar signal nor an interference signal the noise level on thatchannel is the background noise level. Current noise levels are stored in atable and timeout indications for radar and interference signals are imple-mented by OMNeT++ self messages.

Figure 4.3: Switching noise levels on a certain channel

EXAMPLE 4.1

The background noise level is -100 dBm. No radar or interference is presenton any frequency channel. There are two stations (sta[0] and sta[1]) associ-ated to an access point (ap[0]), see figure 4.4.

An interference signal with power -80 dBm is sent out from the Interferencemodule. The WirelessMedium module, denoted WM in figure 4.4, detects thesignal as having a duration of 5 seconds affecting the frequency channels 44and 45. To inform all nodes about the change of the noise level on these chan-nels messages holding new noise levels are sent out to each node.

Two seconds later a frame of size 500 bytes from sta[0] is coming in to theWirelessMedium module. It is sent with the data rate 54 Mbps on the highestpower level on frequency channel 44. Distance and attenuation to sta[1] andap[0] respectively as well as received power at sta[1] and ap[0] are computed.SNR is determined from the received power and the noise power(-80 dBm) on frequency channel 44. Depending on the channel model usedfor each link the probability of frame error is easily given knowing SNR, datarate (54 Mbps) and frame length (500 bytes). A random function determines

noise

time

levelbackgroundnoise level


from the frame error rate whether the frame to sta[1] and ap[0] should beaffected by errors or not.

The WirelessMedium module sends the processed message from sta[0] fur-ther to sta[1] and ap[0].

Figure 4.4: Example 4.1

RADAR SIGNAL MODELING

Radar signals modeled in the WOK model are assumed originating frompulse radar systems. Such radar systems generate pulses with a certain PulseRepetition Frequency (PRF). Pulses typically have durations between 0.05and 100 us. In real life, radar detection is performed by detecting such pulses.As will be described in chapter “Implementation of Measurements” onpage 30, the radar detection mechanism of the WOK model detects bursts ofradar pulses instead of single pulses. Therefore, the radar signal generator

sta[0]

ap[0]

sta[1]

WM

Inter-ference

2

3

1

2 4

2 4

time-100 dBm

-80 dBm

noiselevel

1

2

3

4


implemented by the Radar module models radar signals at burst level.

The radar burst length represents the time the radar signal is seen by theWLAN. The burst period represents the time between successive scans of theradar beam. The WOK model supports the three radar signal types proposedas DFS test signals by ETSI [13]. These are specified by table 4.4.

Table 4.4. Parameters of radar signals

The Radar module generates new radar sources according to a Poisson proc-ess. This is to achieve an independence between the arrivals of new radarsources on the medium. Radar type and channel are chosen randomly at gen-eration. Only one radar source can be present at a channel at a given time.

Individual radar bursts are “injected” into the WirelessMedium module, atintervals corresponding to the burst period, via message passing. Such a mes-sage holds the following parameters:

• Bandwidth [MHz]

• Burst length [ms]

• Center frequency [MHz]

• Power level [dBm]

4.3 PHY

The PHY module constitutes parts of the PLCP sublayer1 in IEEE 802.11aOFDM2 PHY.

Radar signal type Burst length L [ms] Burst period B [s]

1 26 10

2 5 2

3 210 60

1. The Physical Layer Convergence Procedure (PLCP) sublayer is one oftwo sublayers in PHY.

2. Orthogonal Frequency Division Multiplexing (OFDM) is the modulationtechnique in IEEE 802.11a, used to modulate digital signals to radio sig-nals.


Measurements and ordinary traffic handling are implemented in separate sub-modules within the PHY module.

4.3.1 IMPLEMENTATION OF TRAFFIC HANDLING

CCA AND HIDDEN NODE DETECTION

In practice, an end user’s radio Network Interface Card (NIC) senses thewireless medium. It is the physical carrier-sense mechanism and the ClearChannel Assessment (CCA) operation in the physical layer that determineswhether the wireless medium is busy or idle. If the signal detected is strongenough, the wireless medium appears as busy.

In order to take care of a signal detection in the WOK model two separatethresholds are implemented for interference and frame transmissions respec-tively. The receiver is considered as a hidden node to the transmitter if thesignal strength of an incoming frame is below its threshold value. There areseveral mechanisms provided in order to keep track of activities on the wire-less medium. Two internal states {busy, idle}, a variable holding interferenceactivity and timers set with the transmission duration of each incoming frameare used. When the last timer time-out occurs and there is no interferenceactivity indicated, the internal state switches from busy to idle and MAC isinformed, according to the IEEE 802.11 standard [1].

COMMUNICATION

In reality there is a propagation delay for a transmission between a transmitterand a receiver. The propagation delay in the WOK model is zero. Addition-ally, the transmission of a frame from the PHY module at the transmitter tothe PHY module at the receiver takes no time. Time passes afterwards withineach PHY module with the aid of implemented timers.

Communication between the PHY module and the MAC module follows theinterface described in the IEEE 802.11 standard [1] to a great extent. Allimplemented primitives in PHY-SAP are put together in table 4.5. An optimi-zation is done in order to speed up the simulations. Instead of sending octetsof data to MAC, only messages with indication of when reception of a framestarts and stops are sent. For example, if a frame of length 1024 bytes is goingto be sent to MAC there are 2 messages instead of 1026 (1024 + 2) messages


sent. These messages are sufficient and necessary, because a collision mayoccur during the frame reception, see chapter “Collision Handling” onpage 29. Two timers are implemented in the WOK model in order to synchro-nize the transfer of these messages to the MAC module. The way of sendingoctets of data from the MAC module to the PHY module is optimized simi-larly.

Table 4.5. PHY-SAP primitives implemented

COLLISION HANDLING

The internal state is tied to two different actions {sending, receiving}. Theidea is to let the PHY module act as an antenna set in either sending or receiv-ing mode. It is assumed that an antenna cannot be in two modes at the sametime.

In reality a collision occurs when the PHY layer receives a frame from thewireless medium and it is still busy receiving another frame from the wirelessmedium. If a collision occurs the frame being received is considered as lost.

A collision in the WOK model is detected in the PHY module when a frameis received from the WirelessMedium module and the internal state is busyreceiving. The timer indicating when the reception should have ended if nocollision had occured is cancelled. An indication to the MAC module is sent,

Primitive Description

PHY-RXSTART.indication Indication to the MAC of incoming frame from thewireless medium.

PHY-RXEND.indication Indication to the MAC of ended reception of framefrom the wireless medium.

PHY-CCA.indication Indication to the MAC of the status of the channel.

PHY-TXSTART.request Request from the MAC of transmission of a frame tothe PHY.

PHY-TXSTART.confirm Confirmation to the MAC of transmission request.

PHY-TXEND.request Request from the MAC of ending frame transmissionto the PHY.

PHY-TXEND.confirm Confirmation to the MAC of request of ending frametransmission.


according to the IEEE 802.11 standard [1], indicating that the frame is lost. Inreality there are two transmitters still sending and the wireless medium mustnot be considered idle before the two of them stop transmitting. How this istaken care of in the WOK model was described in chapter “CCA and HiddenNode Detection” on page 28.

If the PHY module receives a frame from the WirelessMedium module andthe internal state is busy sending nothing will happen. In reality the antenna isset in sending mode and incoming frames are therefore neglected.

4.3.2 IMPLEMENTATION OF MEASUREMENTS

In order to implement DFS, the ability of performing measurements on themedium is required in APs and STAs of the WOK model. Measurementmechanisms modeled are based on the IEEE 802.11h draft [12].

In the WOK model, the actual sensing of the medium is performed throughthe arrival of data and interference messages from the WirelessMedium mod-ule. The sense mechanism is perfect, i.e., it senses the status of all channels atall times. This (unrealistic) approach is required since then, the interferencesituation is known at the start of a measurement, independent of which chan-nel is measured. As described in chapter “The Wireless Medium” on page 19,APs and STAs receive interference messages only upon changes of interfer-ence levels.

Three measurement types are specified by [12]. These are:

• Basic

• CCA

• RSSRI

According to [12], the basic measurement type is mandatory while the CCAand the RSSRI measurement types are optional. All three measurement typesare supported in the WOK model, and the resulting reports are implementedby corresponding OMNeT++ classes. A report is passed to the local MACentity following a measurement, possibly to be included as a subfield in anoutgoing measurement report frame.


BASIC

In the WOK model, a basic report is defined by the channel number measuredand the boolean attributes of table 4.6. This definition agrees with the specifi-cation in [12].

Table 4.6. Basic report contents

The basic measurement is based on advanced measuring mechanisms that hasbeen simplified in the WOK model. In a WOK basic measurement, the BSSflag is set if the arrival of a frame occurs during the measurement period. It isnot set by a reception in progress at measurement start. This approach agreeswith the assumption that PHY considers a frame valid if it detects its PLCPheader, i.e., at reception start.

Foreign WLAN signals, such as HiperLAN/2 frames, are not modeled.Hence, the Foreign PLCP Header flag is always false.

In the WOK model, a radar signal is considered detected if the radar signalburst overlaps with the measurement period at any time. The radar signalburst power level must exceed both other present signals and the value set bya configurable parameter dfsDetectionThreshold1. The radar detec-tion mechanism is perfect considering that the false detection probability iszero. This is why radar signals are modeled at burst level instead of pulselevel, as described in chapter “Radar Signal Modeling” on page 26. Note thata radar signal may be “hidden” by other stronger signals, and thus may avoid

Attribute Description

BSS Indicates that at least one valid frame was decoded in thechannel during the measurement period.

Foreign PLCP Header Indicates that at least one foreign PLCP header wasdetected in the channel during the measurement period.

Unknown Indicates that transmissions were detected in the channelduring the measurement period, that cannot be character-

ized as primary users.

Primary User Indicates that a primary user was detected operating in thischannel during the measurement period.

Unmeasured Indicates that this channel has not been measured.

1. ETSI [13] proposes that this threshold should be set to -64 dBm.


detection.

The unmeasured flag is set, i.e., the measurement is considered failed, if anoutgoing transmission is in progress at any time during the measurementperiod.

CCA

A CCA report is defined by the channel number measured and the CCA busyfraction. The CCA busy fraction is the fractional period over which CCAindicated the channel was busy during the measurement period. In the WOKimplementation it is represented as a real number in the interval [0, 1]. In [12]it is represented as .

RSSRI

The Received Signal Strength Relative Indication (RSSRI) measurementreport is defined by the channel number measured and eight RSSRI densities.An RSSRI density for interval i is defined as the fractional period over whichthe RSS value was within interval i during the measurement period. In theWOK implementation it is represented as a real number in the interval [0, 1].In [12] it is represented similar to the CCA busy fraction described above.

[12] defines the RSSRI intervals according to table 4.7.

Table 4.7. Definitions for an RSSRI report

RSSRI Power observed at the antenna [dBm]

0

1

2

3

4

5

6

7

255 Busy duration Measurement duration⁄( )×

Power 87–≤

87– Power 82–≤<

82– Power 77–≤<

77– Power 72–≤<

72– Power 67–≤<

67– Power 62–≤<

62– Power 57–≤<

57– Power<


4.4 MAC

The MAC implementation of the WOK model constitutes a subset of theMAC layer, as specified by the IEEE 802.11 standard [1]. This chapterdescribes the collection of MAC operations and mechanisms implemented inthe WOK model. Furthermore, the actual implementation of the MAC, i.e.,the MAC module, is described.

4.4.1 MAC FUNCTIONS IN THE WOK MODEL

A primary goal with the MAC of the WOK model is to implement MACoperations sufficient for studying DFS and link adaptation. Specifically, MACfunctions enabling normal WLAN traffic are required, i.e., the transmissionand reception of MAC frames within a BSS. The most important MAC oper-ations and mechanisms implemented for this purpose are presented below.

• Basic medium access method:- The Distributed Coordination Function (DCF)

• Reliable data delivery:- Frame exchange protocol between stations- Fragmentation and defragmentation of frames

• Channel state notion:- The physical carrier-sense mechanism- The virtual carrier-sense mechanism

• Frames

• Management:- Synchronization- Scanning

• Management Information Base (MIB)

• Interfaces:- IEEE 802.11 SAPs

BASIC MEDIUM ACCESS METHOD

The Distributed Coordination Function (DCF) implements the basic accessmethod to the wireless medium through the use of Carrier Sense Multiple


Access with Collision Avoidance (CSMA/CA) and a random backoff time fol-lowing a busy medium. According to the DCF, a station must sense themedium before initiating the transmission of a frame. If the medium is sensedidle for a time interval greater than a Distributed Interframe Space (DIFS)period, the station transmits. Otherwise, the transmission is deferred and thebackoff procedure is started. Specifically, the station computes a randombackoff time interval, uniformly distributed between zero and a maximumvalue called the Contention Window (CW). This backoff interval is used toinitialize the backoff timer. Each time the medium becomes idle, the stationagain waits for DIFS and then periodically decrements the backoff timer. Thedecrementing period is referred to as a slot time. As soon as the backoff timerexpires, the MAC is authorized to transmit. [11]

FRAME EXCHANGE PROTOCOL

The frame exchange protocol is used to provide a reliable data delivery serv-ice to MAC users. Unlike in wired networks, it is not sufficient to simplytransmit a frame and expect that the destination has received it. In its minimalform, the frame exchange protocol includes two frames. A data frame is sentfrom the source to the destination and a corresponding acknowledgementframe (ACK) is sent from the destination to the source indicating that the dataframe was received correctly. After a successful reception of a frame requir-ing an acknowledgement, transmission of the ACK commences after a ShortInterframe Space (SIFS) period, without regard to the state of the medium.Since SIFS is shorter than DIFS, other stations cannot access the mediumuntil the frame exchange is complete. If the source does not receive anacknowledgement within a certain duration of time, it tries to retransmit theframe, according to the rules of the basic access method. MAC-levelacknowledgements (and retransmissions) concern unicast frames only. [11]

FRAGMENTATION AND DEFRAGMENTATION

The process of partitioning a MAC Service Data Unit (MSDU)1 or a MACManagement Protocol Data Unit (MMPDU)2 into smaller MAC level frames,

1. An MSDU is the data unit arriving from the layer above the MAC, i.e.,the LLC layer.

2. An MMPDU is a management-related frame generated internally by theMLME.


MAC Protocol Data Units (MPDUs), is called fragmentation. Fragmentationis performed in order to increase the probability of a successful transmissionin cases where a noisy environment limits reception reliability for longerframes. The reverse process of reassembling MPDUs into a single MSDU orMMPDU is called defragmentation. Fragmentation is accomplished at theimmediate transmitter and defragmentation is performed at each immediatereceiver. Only unicast frames longer than a certain fragmentation thresholdare fragmented. [1, 11]

A sequence of fragments originating from the same MSDU or MMPDU iscalled a fragment burst. Subsequent fragments of such a burst are transmitteda SIFS period after the acknowledgement of the previous fragment, withoutneeding to compete for the medium. This is to minimize the total amount oftime that is taken to deliver a single frame that has been fragmented. [1, 11]

Since fragmentation can be used as a mean in link adaptation algorithms, it isof significance for the WOK model.

CHANNEL STATE NOTION

In the DCF, both physical and virtual carrier-sense functions are used todetermine the state of the medium. When either function indicates a busymedium, the medium is considered busy. The physical carrier-sense mecha-nism is provided by the PHY and was described in chapter “PHY” onpage 27.

The virtual carrier-sense mechanism is also referred to as the Network Alloca-tion Vector (NAV). The NAV is a value that indicates the amount of time thatremains before the medium will become available. A station that receives aframe not addressed to it updates its NAV with the duration informationincluded in the frame header. By examining the NAV, a station may avoidtransmitting, even though the physical carrier-sense mechanism indicates anidle medium. This mechanism prevents some situations where collisions oth-erwise would occur due to the hidden node problem. [11]

FRAMES

A MAC frame consists of three basic components; a MAC header, a variablelength frame body, and a Frame Check Sequence (FCS). Figure 4.5 depictsthe format of a general MAC frame. It comprises a set of fields that occur in


most frames. The length of each field is given in bytes. [1]

Figure 4.5: A general MAC frame

The MAC header subfields include information needed for data deliverymechanisms, such as addressing, NAV updating, and fragmentation. Hence, aMAC frame representation is required in the WOK model. The FCS fieldcontains a 32-bit Cyclic Redundancy Check (CRC) used to detect bit errors.[11]

Table 4.8 shows the specific frame formats implemented in the WOK model.

Table 4.8. Frame formats

A management frame body generally includes so called fixed fields and infor-mation elements, relevant for the specific management task. Table 4.9 showswhich are supported in the WOK model. All management frames of subtypeaction are introduced in the IEEE 802.11h draft [12]. These frames and theirframe body contents are related to DFS.

Frame format Type Subtype

Data Data Data

ACK Control Acknowledgement

Beacon Management Beacon

Channel switch announcement Management Action

Measurement request Management Action

Measurement report Management Action

Framecontrol

Duration/ID

Address 1 Address 2 Address 3 Address 4Sequencecontrol

Framebody

FCS

MAC header

2 2 6666 2 0-2312 4


Table 4.9. Frame body contents

MANAGEMENT

Unlike other IEEE 802 LAN standards, the IEEE 802.11 includes significantmanagement capabilities. This is because of the complexity of the environ-ment the WLAN must deal with. Such management functions include:

• Authentification:The identification procedure between stations through the exchange ofauthentification management frames.

• Association:The procedure of “connecting” STAs to APs through the exchange ofassociation management frames. Through this procedure, IEEE 802.11provides transparent mobility to STAs, i.e., roaming.

• Power management:The procedure of allowing a STA to go into sleep mode, while data des-tined to it is buffered at the associated APs for delivery at wake-up time.

• Synchronization:The procedure of synchronizing all STAs of the BSS with the AP.

• Scanning:The procedure a STA performs in order to find a suitable BSS to join.

• BSS start:The procedure an AP performs in order to start a new BSS.

Both authentication and association are required in order to deliver databetween peer MAC entities within a BSS. However, in the WOK model it isassumed at simulation start that all STAs are already appropriately authenti-

Frame format Fixed field(s) Information element

Beacon Beacon intervalTimestamp

Quiet

Channel switch announcement Action descriptor Channel switch announcement

Measurement request Action descriptor Measurement request

Measurement report Action descriptor Measurement report


cated and associated. Since roaming is not modeled, this approach is enough.The composition of WLAN cells in a WOK simulation is preconfigured.

Power management is not considered significant in the context of DFS andlink adaptation, and is thus not supported in the WOK model.

Synchronization is performed through so called beaconing. The AP isresponsible for periodically transmitting beacon frames broadcast toannounce the presence of the BSS. The time between subsequent beaconframes is called the beacon interval. The AP will try to transmit the beaconframe at Target Beacon Transmission Times (TBTTs). However, the beaconmust compete for the medium as any other frame. Thus, the beacon may bedelayed beyond the TBTT.

In a BSS, the beaconing procedure is mandatory and consequently, beacontransmissions are a natural part of normal traffic flow. Further, beacon framescan be used to facilitate the synchronization of DFS procedures. Therefore,beaconing is implemented in the WOK model.

Since BSS compositions in the WOK model are static and preconfigured,scanning and BSS start procedures are not required. However, a simplified“directed” passive scan procedure is implemented in WOK stations, enablinga station to find its access point in cases where the channel is not known inadvance. This procedure is needed when studying DFS.

The IEEE 802.11h draft [12] introduces some additional management mecha-nisms related to DFS. These will be treated in chapter “IEEE 802.11h Inter-face Extensions” on page 60.

MANAGEMENT INFORMATION BASE (MIB)

The IEEE 802.11 MAC includes a Management Information Base (MIB),holding MAC parameters. The parameters implemented in the WOK modelare specified by table 4.10 and table 4.11. Time periods are often specified inTime Units (TUs) in the IEEE 802.11 MAC. One TU equals 1024 us.


Table 4.10. MIB parameters

Table 4.11. MIB counter parameters


dot11BeaconPeriod Specifies the beacon interval. [TUs]

dot11FragmentationThreshold MSDUs and MMPDUs longer than this threshold willbe fragmented. [Bytes]

dot11MacAddress The MAC address

dot11MaxReceiveLifetime MSDUs or MMPDUs not completely received (due tofragmentation) within this time will be discarded at

the receiver. [TUs]

dot11MaxTransmitMSDULifetime Attempts to transmit an MSDU will stop when thistime has elapsed since the first transmission attempt.

[TUs]

dot11ShortRetryLimit The number of transmission attempts before a trans-mission is considered failed.


dot11ACKFailureCount Incremented at an ACK timeout.

dot11FailedCount Incremented at a failed transmission.

dot11FcsErrorCount Incremented at the reception of a frame withbit error.

dot11MulticastReceivedFrameCount Incremented at the reception of amulticast frame.

dot11MulticastTransmittedFrameCount Incremented following thetransmission of a multicast frame.

dot11ReceivedFragmentCount Incremented at the reception of an MPDU.

dot11TransmittedFragmentCount Incremented following a transmission of anMPDU.

dot11TransmittedFrameCount Incremented following a transmission of anMSDU or an MMPDU.

dot11FrameDuplicateCount Incremented at the reception of a duplicateframe.


INTERFACES

The MAC within the WOK model supports the interfaces, or SAPs, specifiedby the IEEE 802.11 standard [1]. These could be seen in figure 2.3:

• MAC SAP provides data services to the LLC layer.

• PHY SAP provides services that support MAC peer-to-peer interactions,i.e., transmission and reception of MPDUs. See chapter “PHY” onpage 27.

• MLME SAP provides MAC-level management services to the StationManagement Entity (SME). See chapter 5.

• PLME SAP provides PHY-level management services to MLME andSME. See chapter “PHY” on page 27.

Somewhat simplified versions of these SAPs are supported in the WOKmodel. For example, only MLME and PLME SAP primitives associated withmanagement procedures actually implemented are supported in the WOKmodel.

The MAC SAP is defined by the primitives described briefly in table 4.12below. The notation used agrees with the notation used in [1].

Table 4.12. MAC SAP primitives

4.4.2 MODELING APPROACH

The modeling of the MAC is almost entirely based on the Specification andDescription Language (SDL) formal description provided by the IEEE

Primitive Parameter Usage

MA-UNITDATA.request sourcedestination

(data)

The LLC requests the transmissionof some data (MSDU) to adestination MAC address.

MA-UNITDATA.indication sourcedestination

(data)

The MAC passes incoming data(MSDU) to the LLC.

MA-UNITDATA-STATUS.indication sourcedestination

status

The MAC reports the status of acorresponding request following asuccessful or failed transmission.


802.11 standard [1], defining the operation of the MAC protocol. Thisapproach is convenient for several reasons.

The SDL description defines the MAC as a set of logically separated blocks.Each block’s functionality is described as a state machine process. Eventsthat force state transitions are either generated by incoming signals fromother blocks or by the expirations of internal timers. This corresponds well tothe design paradigm of OMNeT++, which is based on modules (blocks) andmessage-passing (events) between and within modules. OMNeT++ also sup-ports the concept of Finite State Machines (FSMs). [1, 8]

By using the SDL description as a template, future improvements of theMAC model are facilitated. Further, since the SDL description is formal, it isassumed to be a correct and a complete description of the MAC protocol.

4.4.3 MAC FRAME IMPLEMENTATION

As already mentioned, all events in the WOK model are generated by thearrivals of messages. This is a direct consequence of using OMNeT++ andthe messages used are OMNeT++ cMessage objects. In the WOK model, adistinction is made between “regular” messages (events) and data messagesthat represent actual information, i.e., frames. Regular messages are imple-mented using the cMessage class. In order to model frames the DataMes-sage class has been designed. It provides the means for modeling the MACframe header and body. Figure 4.6 shows a class diagram1 of the DataMes-sage implementation.

1. Class diagrams in this chapter uses the Unified Modeling Language(UML). UML is often used for describing object oriented design.


Figure 4.6: The DataMessage class

A number of attributes represents the MAC frame header subfields. Thereader is referred to [1] for detailed descriptions of these fields.

For convenience, the unicast MAC address is modeled as a string on the form“sta[2]” instead of a 48-bit sequence as in [1]. Broadcast frames are des-tined to the “broadcast” address. Multicast addresses that are not broad-cast addresses are not supported.

No actual data is included in the data frame representation of the WOKmodel, i.e., the frame body is not modeled as a sequence of bits. This is due tothe fact that the information itself is not important, in the context of DFS andlink adaptation. Consequently, the FCS field is not modeled either since thereis no bit pattern to perform the CRC algorithm upon. Bit errors are insteadindicated by a cMessage boolean attribute provided by OMNeT++ for thispurpose.

In management frames, the frame body includes one or more fixed fields andinformation elements. The frame body is implemented by the FrameBodyclass, holding two dynamic-length arrays representing the sets of fixed fields

DataMessage

cMessage

FrameBody

InfoElementFixedField

0..*

1

1

1

0..*

type : stringsubtype : stringtoDs : boolfromDs : boolmoreFragments : boolretry : booldurationID : intaddress1 : stringaddress2 : stringaddress3 : stringaddress4 : stringsequenceNumber : intfragmentNumber : int

Get/Set methods

DataMessage

frameBodyLength : intframeBody : FrameBody


and information elements. This implementation enables flexible managementframe creation.

The fixed field and information element classes are derived from the abstractclasses FixedField and InfoElement, respectively. This is depicted infigure 4.7 and figure 4.8.

Figure 4.7: The FixedField class

Specific fixed field classes and information element classes are simple repre-sentations of the corresponding fields specified by [1] and [12]. By represent-ing frame fields and subfields as OMNeT++ classes, future improvementsand additions are facilitated.

FixedField

MeasurementBeaconInterval Timestamp ActionOffsetDescriptor


Figure 4.8: The InfoElement class

4.4.4 MAC MODULE OVERVIEW

Figure 4.9 shows the structure of the MAC module. As with the WOK modelin general, submodules interact by passing messages. Note that a message isnot necessarily a frame. The submodules corresponds to the blocks describedin the SDL description in the IEEE 802.11 standard [1]. Each submoduleimplements a certain part of the MAC protocol.

InfoElement

MeasurementElement

ChannelSwitchAnnouncement

Quiet

MeasurementReport

MeasurementRequest

Report

Basic CCARSSRI

Histogram

1

1


Figure 4.9: The MAC module

4.4.5 MAC MODULE IMPLEMENTATION

This chapter describes the functions, responsibilities, and implementations ofthe submodules of the MAC module.

DataService

This module provides the MAC SAP functions previously described. Uponreception of a MA-UNITDATA.request from the LLC, DataService cre-ates a corresponding DataMessage object representing an MSDU to beforwarded to MPDUGeneration. DataService is not used in the AP, since

DataService

DistributionService

MACMIB

MPDUGeneration

MLMEProtocol

ReceptionTransmission

PHY SAP

MAC SAP

(AP)

MAC SAP functions

FragmentationBuffering

BeaconingDFS procedures

DCFSIFS timingACK generationRecovery mechanism

Backoff algorithm

Validation/FilteringDuplicate detectionDefragmentationChannel state notion

Frame reception

Frame transmission


LLC traffic is generated in STAs only.

MPDUGeneration

This module implements the fragmentation and buffering of incoming datamessages. Fragmentation is implemented by adding special fragmentationparameters to the incoming data message. These parameters specifies numberof fragments, fragment lengths, etc., based on given data length and MIBparameter dot11FragmentationThreshold.

A data message, i.e., an MSDU or an MMPDU, may arrive at any time. Thebuffer used for temporary storage of these is implemented as a queue, whereMMPDUs have priority over MSDUs. The buffer is unbounded in the currentimplementation.

DistributionService

In [1], the DistributionService block implements the AP’s interface to the dis-tribution system. However, the WOK model does not implement the distribu-tion system and thus, the DistributionService module only performs a simpleforwarding function used internally. It is implemented purely to facilitatefuture implementations of a distribution system.

MLME

In the WOK model, MLME responsibilities are limited to synchronizationand providing DFS-related MLME SAP functions to the SME. For the AP,this includes generation and transmission scheduling of beacon frames atevery TBTT. DFS tasks performed by this module in APs and STAs, respec-tively, will be described in chapter 5.

Protocol

This module is the heart of the MAC module. It essentially implements DCFby coordinating the functions of the Transmission module. The Protocolmodule also implements the frame exchange protocol by creating and trans-mitting ACK frames upon the reception of an unicast frame.

Further, it implements SIFS timing. This is needed for scheduling both ACKtransmissions, and the transmission of next fragment within a fragment burst,as described before. SIFS timers are implemented using the OMNeT++selfmessage mechanism, where the module schedules the arrival of a messageto itself.


The ackowledgement timeout timer is implemented similarily. The expirationof this timer activates the retransmission mechanism for a frame based on thefailure of the reception of an ACK frame.

The Protocol module also implements the dwell time boundary deferralmechanism, used in the DFS implementation. This mechanism will be treatedin chapter 5.

Transmission

In the IEEE 802.11 MAC, the Transmission block implements byte-leveltransfers of frames to the PHY. The Transmission module uses the same inter-face, PHY SAP, towards the PHY for data transfer. However, for simulationoptimization reasons and considering that no actual bit sequences are han-dled, the byte-level transfer approach is not suitable in the WOK model. Howthe timing is handled during data transfer to PHY was treated in chapter“PHY” on page 27.

The Transmission module also implements the backoff algorithm, generatinga new random backoff number when requested from the Protocol module.The backoff timer decrements, freezes or expires based on incoming BUSY,IDLE, and SLOT messages from the Reception module.

Reception

In the IEEE 802.11 MAC, the Reception block implements byte-level recep-tion of frames. The Reception module does not use this approach, for thesame reasons as the Transmission module.

The Reception module also implements:

• Bit error detection

• Address filtering

• Frame duplicate detection

• Defragmentation

• Channel state notion

As previously described, bit errors are indicated by an OMNeT++ messageparameter provided for this purpose. Address filtering, duplicate detection,and defragmentation procedures are performed based on the MAC headercontents of the incoming data message.


Defragmentation is performed by buffering information of the fragment datamessages received so far, instead of buffering the actual fragments as in [1].The buffer is “cleaned” regularly, removing “fragments” which have beenpresent in the buffer for longer than a certain time period, defined by MIBparameter dot11MaxReceiveLifetime. Several concurrently incomingMSDUs or MMPDUs can be handled. An MSDU or MMPDU is passed tothe Protocol module only when all fragment data messages have beenreceived.

The MAC notion of channel state is based on both physical carrier-sense,indicated from the PHY, and virtual carrier-sense. The NAV timer, i.e., thevirtual carrier-sense mechanism, is updated with the time specified by theMAC header duration/ID field of the incoming frame. In the WOK model, theNAV timer can be updated by MLME as well. This is used implementingDFS, discussed in chapter 5.

DIFS and EIFS timing following a frame reception, and slot times during anidle channel state is implemented using OMNeT++ selfmessages. The chan-nel state is indicated to the backoff algorithm in the Transmission modulethrough BUSY, IDLE and SLOT messages.

MACMIB

The MACMIB module implements the parameters that were given in table4.10 and table 4.11. Parameters are implemented using OMNeT++ moduleparameters accessible from all other submodules. The parameters in table4.10 can be configured preceding a WOK simulation.

4.5 TRAFFIC GENERATION

The WLAN traffic sources in the WOK model are placed just above the MAClayer in the STAs, i.e., at the LLC layer. A STA traffic source can be config-ured as the well known random traffic generator, described in Tourrilhes [14].That is, all packet sizes are uniformly distributed within the accepted packetsize limits and packets arrive at the MAC following a Poisson process. Themain advantage with this traffic model is that it is widely used and that itallows to experiment with the full range of loads and packet sizes.

The traffic source configuration can also be slightly modified to model voicetraffic. The main characteristics of voice traffic is a constant load, i.e., fixedpacket sizes, and a fixed arrival rate to the MAC. These characteristics also


apply to common multimedia applications like video and gaming. The inter-arrival time can also be kept random, for modeling a variable latency intro-duced by higher layers, e.g., TCP. [14]

A drawback with the traffic modeling approach described is that it assumes astochastic process for a single user based on fixed average values. Under real-life conditions for WLAN applications (such as file transfer, web browsingand e-mail), the traffic process of a single user is not autonomous but subjectto flow control. The TCP/IP flow control, with a transmit congestion andreceive window make sure that the transmission of new packets is slaved tothe response from the receiving node. With slower response from the otherside, the next packet will be scheduled later. [15]

However, achieving realistic traffic patterns is not a primary concern in theWOK model. Link adaptation and DFS simulations can be performed satis-factory using a simple traffic source as the one described above.

The traffic source is implemented by the module TrafficHandler. Trafficparameters are given in table 4.13. The deterministic traffic type uses a fixedpacket interarrival time.

Table 4.13. Configurable traffic parameters

An alternative traffic model is also implemented in the WOK model. It imple-ments a simple flow control by requesting the transmission of a packet onlyupon the indication from MAC that the transmission of the previous packethas been completed. In this model, the trafficInterval parameterdefines the delay between the indication and the next request.


traffic Traffic type.{NONE, DETERMINISTIC, POISSON}

trafficInterval Packet interarrival time. If Poisson traffic isused, this is the mean interarrival time. [s]

trafficFixedMsduLength Fixed packet length on/off.[true/false]

trafficMsduLength Packet length, if fixed. [Bytes]

trafficStart First packet arrival timestamp. [s]


4.6 IMPROVEMENTS

In order to perform more realistic simulations, it is desirable to improve thetraffic model used. At present, evaluation is performed by comparing simula-tion runs, achieving relative results. More realistic traffic patterns in theWLAN cells simulated would generate more accurate results. A first step is toimplement TCP-based traffic models, with flow control and congestion con-trol.

Another improvement related to traffic is to transmit actual data bit sequencesin the WOK model, i.e. include frame body contents in the data messages.This would be the ultimate test of the MAC implementation, e.g. by lettingnodes transmit JPEG image files to each other, opening and viewing the filesat the receiving nodes.

4.7 COMMENTS

Our first approach was to model the delivery of frames at octet level. In theWOK model, this implied that an event was generated for every byte sent (atthe sender node) and every byte received (at all the other nodes in the simula-tion). In addition, events were generated every slot time (9 us) at every node,in order to control the backoff algorithm. Both these approaches agreed withthe IEEE 802.11 standard [1]. However, even at modest traffic loads and witha limited number of nodes, we experienced far too slow simulations (<< 1%of simulated time). Obviously, we overestimated the performance ofOMNeT++, and had to change our modeling approach.

Another unpleasent surprise for us was that the IEEE 802.11 standard [1]showed to be incomplete and somewhat ambiguous regarding the MACimplementation. This caused us problems, having to guess the correct imple-mentation. As a consequence, there is no guarantee that the MAC model inthe WOK in every detail agrees with a “typical” MAC implementation.

51

5DYNAMIC FREQUENCY SELECTION

5.1 INTRODUCTION

At the World Radio Conference (WRC) 2003 in Geneva, US and Europebecame united about providing the 5 GHz band with global regulationsrequiring the use of DFS in WLANs. [16]

At present, the exact framing of these regulations are not final, but they willlikely agree with the current regulations specified by the European Confer-ence of Postal and Telecommunications Administrations (CEPT). In order tosatisfy these and similar future regulatory requirements, IEEE have initiatedthe work with an enhancement to the IEEE 802.11a standard [7], namely theIEEE 802.11h draft [12], which includes some support for DFS at MAC-level. Furthermore, the European Telecommunications Standards Institute(ETSI) is in the final stage of the work with a harmonized standard document[13] covering essential requirements for equipment deploying DFS. The workby both IEEE and ETSI is expected to have great impact on the design andimplementation of DFS in future WLAN devices. Therefore, these two draftshave served as a base for the work described in this chapter.

5.1.1 PROBLEM DESCRIPTION

The primary goal with DFS for WLANs operating in the 5 GHz band is to

by Magnus Janson


reduce interference with primary users. More formally, and according toETSI [13], a DFS function is expected to:

• Detect interference from other systems and to avoid co-channel operationwith these systems, notably radar systems.

• Provide on aggregate a uniform loading of the spectrum across alldevices.

In this report, emphasis is given to DFS on MAC-level within the IEEE802.11a standard. Obviously, the final goal is to design a DFS algorithm thatsatisfies the requirements given above. However, there are several issues thatmust be considered before this can be accomplished. These issues are pre-sented below.

• What “low-level” DFS mechanisms must be implemented? Within thescope of this text, a DFS mechanism is considered low-level if it consti-tutes a service needed by a (high-level) DFS algorithm. We call thesemechanisms DFS procedures. A typical example of such a procedure isthe concept of a quiet period, which will be treated later on.

• How should these DFS procedures be implemented? The distributednature of DFS possibly requires synchronized behaviour among membersof a WLAN cell. This increases complexity and demands for carefullydesigned procedures. E.g., timing is certainly a factor when implement-ing a channel switch in a BSS.

• Are there any architectural constraints on where to place DFS functional-ity? We must determine where, within the logical structure of the IEEE802.11a standard, DFS extensions should be implemented.

• How should various DFS tasks be distributed among the members of theBSS? How much work should be centrally controlled or scheduled by theAP, and how much work should be performed autonomously by theSTAs? These questions will be answered partly by simulations, but it isimportant to design the DFS algorithm in a way that the distribution ofthe DFS work load can be varied.

• Which parameters are relevant? In general, we need to determine a set ofDFS algorithm parameters that can be varied. Obviously, we want capa-bility to tune the algorithm in order to perform interesting simulationsand obtain meaningful results.

• How should performance of the DFS function be measured? ETSI [13]

Chapter 5 - Dynamic Frequency Selection 53

specifies requirements that must be satisfied, e.g., an upper limit forchannel move time – the time to cease all transmissions on the channelupon detection of a primary user. The satisfaction of these kinds ofrequirements is of course a performance measure, since avoiding primaryusers is the main objective of DFS. However, it may be of interest tostudy how performance of the WLAN cell is affected by the work load ofDFS. Which performance measures are interesting?

5.1.2 OBJECTIVES

It should be pointed out that the main objective with the DFS-related part ofthe work described in this report is not to design a ready-to-use DFS algo-rithm. Rather, there are several equally important objectives. These are as fol-lows:

• To map out the prerequisites for MAC-level DFS in the IEEE 802.11a.

• To identify and propose extensions to the support introduced by the IEEE802.11h draft [12], needed for implementation of DFS.

• To implement DFS procedures and proposed extensions, obtaining a basefor implementing a DFS algorithm.

• To implement an example DFS algorithm.

• To evaluate the DFS algorithm, given a set of performance measures. Theresults of the evaluation should provide guidance in future DFS algorithmdesign.

5.1.3 LIMITATIONS

As already mentioned, we focus on DFS only in the context of the IEEE802.11a standard. Thus, we are not considering other WLAN technologies,such as HiperLAN/2. However, some of the results presented in this reportare general and may therefore be applicable in other wireless communicationsystems.

Furthermore, several assumptions have been made about the behaviour atPHY-level. DFS is very much based on extensive functionality below MAC-level, including radar signal detection mechanisms. These functions are ofcourse represented in the WOK model but not at a very detailed level. Fur-ther, certain problems of physical nature that may arise at this low level are


not modeled. However, they are considered when relevant and, in some cases,choice of method is based upon such phenomena.

Regarding the DFS algorithm, emphasis has been laid almost entirely on pri-mary user detection and avoidance, since it is the original reason for deploy-ing DFS in WLANs. Dynamic channel switch decisions can, however, bemade based on other aspects, such as high interference levels in general. Thesupport for designing such an algorithm is implemented in the WOK model,providing several measurement types, but the example algorithm does not uti-lize this support much.

The DFS algorithm parameter values are static. This results in a static DFSstrategy during a simulation run. Thus, the strategy itself is not adaptive andseveral simulations are needed to evaluate the algorithm. Further, in order toachieve meaningful results based on DFS simulations, long simulation runsmust be performed. To perform many, long simulation runs is very time con-suming and unfortunately, this has had great impact on the DFS algorithmevaluation.

Furthermore, DFS in the context of IEEE 802.11a is rather new and unex-plored. So far, work related to DFS in WLANs has been limited to Hiper-LAN/2 systems. The DFS approaches used in HiperLAN/2 are notapplicable1 in the IEEE 802.11a standard. Therefore, the DFS algorithm pre-sented in this chapter, is somewhat ad-hoc.

5.2 REGULATORY REQUIREMENTS

ETSI [13] defines the following requirements on a DFS algorithm.

Before initiating a BSS, the AP shall monitor the starting channel for a cer-tain duration of time to ensure that there is no radar operating on the channel.This time is called the channel availability check time.

If the AP detects a radar signal, during in-service monitoring, the operatingchannel is made unavailable. The AP must instruct all associated devices tostop transmitting on this channel, which they shall do within the channelmove time. The aggregate transmissions during this time should be less than

1. The HiperLAN/2 MAC is completely different from the IEEE 802.11MAC. For example, it enables channel measurements within the MACframe.


the channel closing transmission time.

Further, the AP must not resume any transmissions on a channel where radarwas detected, during a period referred to as the non-occupancy period.

The specified values of these parameters are given in table 5.1.

Table 5.1. ETSI DFS requirements

There is also a requirement of uniform spreading of channels. In practice, thismeans that the AP shall select a channel from the available n channels with aprobability of approximately 1/n.

5.3 PREREQUISITES FOR DFS IN THE MAC

Before discussing how to integrate DFS in the IEEE 802.11a, we need to mapout the MAC-level prerequisites for DFS. Here, we introduce a number ofDFS procedures and mechanisms upon which an algorithm can be built.

5.3.1 LOCAL MEASUREMENTS

Obviously, measurements must be performed on the medium in order todetermine the quality of the channels available. From a MAC perspective, aninterface towards PHY is needed for this purpose.

5.3.2 MEASUREMENT REQUESTING AND REPORTING

There are several reasons why the AP should not perform all the neededmeasurements by itself. First, since all BSS traffic passes through the AP, itwill experience the heaviest traffic load in the cell. Therefore, additionalworkload should be limited if possible. Secondly, it is not always desirable

Parameter Value

Channel availability check time > 60 s

Channel move time < 10 s

Channel closing transmission time < 260 ms

Non-occupancy period > 30 min


having the AP measuring on other channels than the operating channel, sinceincoming packets will then be lost during the measurement. Further, interfer-ence from radar systems might be present at only a subset of the cell. Thesesignals will not be detected if the AP cannot hear them.

Therefore, the AP needs to be able to request measurements from the STAs inthe cell. This requires the encoding and distribution of measurement requestframes.

In order to respond to measurement requests from the AP, a STA needs to beable to interpret incoming request frames and schedule local measurementsaccordingly. It also needs to encode and send measurement report frames, fol-lowing performed measurements.

5.3.3 QUIET PERIODS

In real life, extracting correct information from a measurement is a very com-plex task. For example, there is always a risk that a signal is interpreted as aradar signal when it is not. This is called the false alarm probability. Threesituations that might lead to a false radar detection are listed below.

• Frame collisions:If neither of the colliding frames can be decoded it is difficult to distin-guish the signal from radar. Even if one of the OFDM signals is signifi-cantly stronger, and thus can be decoded, the weaker signal may havelonger duration and be interpreted as radar anyway. [17]

• A noisy environment:Contributions from noise affect the RSS measurements that are used forradar detection. RSS values may exceed the radar detection thresholdeven if no radar is present on the channel. [18]

• STAs at neighbouring frequency channels:An OFDM signal on one channel leaks energy to adjacent channels. Onthese channels the signal cannot be decoded. However, its strength mayexceed the radar signal detection threshold at the measuring device,resulting in a false radar detection. [17]

Further, during traffic in the cell, a radar signal may be “hidden” by OFDMsignals. This does not only result in one or more bit errors, but also in a failedradar detection.

In order to increase measurement reliability, it is desirable to perform meas-


urements during so called quiet periods. A quiet period is defined as a sched-uled duration of time when all members of the BSS are quiet, i.e., none of theSTAs attempts to transmit. Another reason for measuring during quiet periodsis that measurements can be performed on other channels than the operating,without missing incoming frames.

Hence, a procedure is needed for the AP to schedule quiet periods in the cell,and for all STAs to obey the order by blocking outgoing traffic for the speci-fied duration of time.

5.3.4 CHANNEL SWITCHING

Based upon achieved measurement results, the AP may decide to perform achannel switch. A procedure is needed for the AP to schedule a channelswitch in the cell. This includes the encoding and sending of channel switchannouncement frames. STAs must be able to schedule and performannounced channel switches accordingly.

Further, a rescue operation is needed in STAs, for the situation where a STAdoes not receive the channel switch announcement frame. The AP does notdiscover this, since the channel switch announcement frame is sent broadcast,and consequently, does not require an ACK.

5.4 DFS SUPPORT IN THE IEEE 802.11H DRAFT

The IEEE 802.11h draft [12] provides some MAC-level support for DFS, byintroducing a set of special DFS management frames and measurement types.It also includes logical extensions to MAC interfaces, which will be treatedlater.

5.4.1 SPECTRUM MANAGEMENT FRAMES

The IEEE 802.11h draft [12] introduces so called action frames, associatedwith certain types of spectrum management actions. Actions related to DFS1

are measurement requesting and reporting between APs and STAs, and APchannel switch announcing. Hence, [12] specifies the frame formats for:

1. Other actions in the IEEE 802.11h concern Transmit Power Control(TPC). Such actions are not supported in the WOK model.


• Meaurement request frames

• Measurement report frames

• Channel switch announcement frames

These frames are implemented in the WOK model, using the modelingapproach described in chapter “MAC” on page 33. A general action manage-ment frame is depicted in figure 5.1.

Figure 5.1: A general action managment frame

The action descriptor fixed field specifies the action, e.g., a measurementrequest. In the case of a measurement request/report frame the informationelement part consists of one or more measurement request/report elements. Inthe case of a channel switch announcement frame, it consists of a single chan-nel switch announcement element.

[12] also specifies certain quiet information elements, to be included in bea-con frames, for scheduling quiet periods in the BSS. These are also supportedin the WOK model.

5.4.2 MEASUREMENT DATA HANDLING

Basic, CCA, and RSSRI measurement types, that are introduced by the IEEE802.11h draft [12], were all treated in chapter “PHY” on page 27. [12] alsosupports the handling of measurement data from these types of measure-ments, by introducing information elements specifying requests and reportsof single measurements. These can be included in corresponding manage-ment frames or used internally within the MAC layer.

5.5 INTEGRATION IN THE IEEE 802.11A

Here, a description is given on how DFS can be integrated into the IEEE802.11a, based on the logical structure of the standard. Further, interface

Frame body

MACheader

Actiondescriptor

Information element(s) FCS


extensions are proposed, as a complement to the IEEE 802.11h draft [12].

5.5.1 LOCATION OF DFS EXTENSIONS

DFS is a management-related task. Hence, it is relevant to consider the IEEE802.11 management model, in order to determine where to locate DFS exten-sions. We want to use existing layer models and mechanisms to facilitate inte-gration of desired DFS functionality. The general architecture of an IEEE802.11 station and its interfaces could be seen in figure 2.3.

Given this logical structure, the location of DFS functionality can be deter-mined. Actually, DFS can be implemented using a layered approach as well,as can be seen in figure 5.2.

The actual DFS algorithm resides at the highest layer. It implements a high-level DFS management protocol used between the AP and STAs. The APdecides the measurement policy, distributes measurement requests among theSTAs in the cell, evaluates incoming measurement reports, and decides whento switch channel.

The middle layer implements DFS procedures, used by the algorithm, includ-ing local measurements, quiet periods, channel switching, encoding anddecoding of DFS management frames, and synchronization.

At the lowest layer, the physical mechanisms are found. These include theactual measurements, frequency switching, and radar detection.

Figure 5.2: DFS layers

Figure 5.3 shows how DFS layers map into the structure of the IEEE 802.11management model, integrating DFS naturally into the standard. The MLMEand PLME SAPs are extended with DFS management primitives to supportinterlayer communication. This is described below.

DFS algorithm

DFS procedures

Physical mechanisms


Figure 5.3: DFS layer management model

5.5.2 IEEE 802.11H INTERFACE EXTENSIONS

The tables below describe the DFS-related MLME SAP interface extensionsintroduced by the IEEE 802.11h draft. Specific primitive parameters aredescribed in detail in [12] and will be treated when relevant in later chapters.

Table 5.2. Channel measurement request primitives

Primitive Parameters Usage

MLME-CMREQUEST.request destinationa

activationDelayoffsetb

dialogueTokenmeasurementRequestSet

a. The destination parameter is not supported by [12].b. The offset parameter is not supported by [12].

The SME requestsmeasurements of a peer

STA. (AP)

MLME-CMREQUEST.confirm resultCode The MAC confirms thecorresponding request to

the SME. (AP)

MLME-CMREQUEST.indication activationDelaydialogueToken,

measurementRequestSet

The MAC indicatesincoming measurement

requests to the SME. (STA)

SME SME

MAC

DFS management protocol

DFS management frame exchange

PHY

MLME SAPMAC

PLME SAPPHY

Measurement policyChannel switch decision

Measurement frameQuiet period

Measurement processing

Channel switch timing

MAC timing

switchingFrequency

Measuring

Radar detection


Table 5.3. Channel measurement report primitives

Table 5.4. Channel switch primitives

Table 5.5. Local measurement primitives

Primitive Parameters Usage

MLME-CMREPORT.request dialogueTokenmeasurementReportSet

The SME requests the reportingof measurements to a peer AP.

(STA)

MLME-CMREPORT.confirm resultCode The MAC confirms thecorresponding request to the

SME. (STA)

MLME-CMREPORT.indication dialogueTokenmeasurementRequestSet

The MAC indicates incomingmeasurement reports to the

SME. (AP)

Primitive name Parameters Usage

MLME-CHANNELSWITCH.request channelNumberactivationDelay

The SME requests a BSSchannel switch. (AP)

MLME-CHANNELSWITCH.confirm resultCode The MAC confirms thecorresponding request to the

SME. (AP)

MLME-CHANNELSWITCH.indication channelNumberactivationDelay

The MAC indicates a channelswitch request to the SME.

(STA)


MLME-CMEASURE.request measurementIdmeasurementRequest

The SME requests a measurement tobe performed locally. (AP/STA)

MLME-CMEASURE.confirm resultCodemeasurementId

measurementReport

The MAC confirms the correspondingrequest to the SME. (AP/STA)


5.5.3 FURTHER INTERFACE EXTENSIONS

Below, we propose an additional set of primitives as an extension to the IEEE802.11h draft [12]. This extension has been implemented in the WOK model.

LOCAL MEASUREMENT REQUESTING

We need to extend the PLME SAP in order to enable MAC-controlled localmeasurements on the wireless medium. The primitives proposed supportingthis are presented below.

Table 5.6. Local measurement request primitives

QUIET PERIOD REQUESTING

In the IEEE 802.11h draft [12], there is no defined interface supporting aSME request of the scheduling of quiet periods. Hence, an interface extensionto the MLME SAP is proposed supporting this. The primitives are presentedin table 5.7.


PLME-CM.request channelNumbera

measurementIdtokenb

duration

a. A channel switch associated with a local measurement is performed implic-itely, in the WOK model. That is, no additional channel switch request is re-quired prior measurement.b. The token parameter is used to distinguish autonomous measurementsfrom externally requested measurements. A zero token indicates an autono-mous measurement.

The MAC requests a measurement to beperformed at the PHY. (AP/STA)

PLME-CM.confirm channelNumbertoken

measurementReport

The PHY confirms a completed measurementto the MAC. (AP/STA)


Table 5.7. Quiet period request primitives

5.5.4 OVERVIEW OF DFS PRIMITIVES

To summarize, a complete overview of the interface service primitives sup-porting DFS in the WOK model is given. This can be seen in figure 5.4.

Figure 5.4: Service primitives supporting DFS in the WOK model


MLME-QUIET.request quietElement The SME requests the scheduling of aquiet period in the BSS. (AP)

MLME-QUIET.confirm resultCode The MAC confirms the correspondingrequest to the SME. (AP)

MLME-CMREQUEST.request (AP)MLME-CMREPORT.request (STA)MLME-CHANNELSWITCH.request (AP)MLME-QUIET.request (AP)

MLME-CMEASURE.request (AP/STA)

MLME-CMEASURE.confirm (AP/STA)MLME-CMREQUEST.confirm (AP)MLME-CMREQUEST.indication (STA)MLME-CMREPORT.confirm (STA)MLME-CMREPORT.indication (AP)MLME-CHANNELSWITCH.confirm (AP)MLME-CHANNELSWITCH.indication (STA)MLME-QUIET.confirm (AP)

MLME SAP

SME

PLME SAP

PLME-CM.request (AP/STA)PLME-SET.request (AP/STA)

PLME-CM.confirm (AP/STA)PLME-SET.confirm (AP/STA).

MAC

PHY

DFS algorithm

DFS procedures

Physical mechanisms


5.6 IMPLEMENTATION OF DFS PROCEDURES

This chapter describes how various MAC-level procedures have been imple-mented in the WOK model.

5.6.1 MEASUREMENT REQUESTING AND REPORTING

An AP may request a set of measurements to be performed by a STA, via theMLME-CMREQUEST.request primitive. The measurements within this setare performed sequentially. The start of the measurement sequence is speci-fied by two parameters, activationDelay and offset. Figure 5.5below shows how the scheduling of this procedure has been implemented inthe WOK model.

Activation delay is expressed in TBTTs until the beacon interval is reachedwhere measurements shall be performed. The offset within this interval isexpressed in TUs, i.e., in units of 1024 us. These parameters are denoted nand k, respectively, in the figure. The duration of the sequence of measure-ments are determined by the sum of the durations of the individual measure-ments. Following a measurement session, the STA reports back to the AP.

Figure 5.5: Measurement requesting and reporting

activationDelay = n, offset = k

n1 2 n+1TBTTs

Request

Measurements

Report

AP

STA

k


5.6.2 QUIET PERIODS

Quiet period scheduling is performed by the AP by including a quiet informa-tion element in a beacon frame, upon a MLME-QUIET.request from theSME. The quiet element, as specified by the IEEE 802.11h draft [12],includes fields holding quiet period parameters. These parameters are speci-fied by table 5.8.

Table 5.8. Quiet element fields

Figure 5.6 shows an example of how the scheduling of quiet periods can beperformed.

A quiet period is performed successfully if all BSS members block all trans-missions during the duration of the period. In the WOK model, this is imple-mented using the virtual carrier-sense NAV mechanism. At quiet period start,NAV is set for a period corresponding to the value of the quiet durationparameter. While NAV is set, the MAC considers the medium busy andblocks all outgoing traffic. At the end of the quiet period, i.e., when the NAVtimer has expired, DIFS elapses and the random backoff procedure is per-formed. This is normal collision avoidance in IEEE 802.11.

When a quiet period has been scheduled at a STA, the start timestamp is con-sidered a dwell time boundary, as described in the IEEE 802.11 [1]. Beforetransmitting a frame, the end-of-transmission timestamp is estimated andcompared to the dwell time boundary. This comparison indicates whether ornot there is enough time for sending the frame (and receive an ACK, if appro-priate) before the quiet period starts.


quietCount The number of TBTTs until the beacon intervalduring which the next quiet period shall start.

quietPeriod The number of TBTTs between periodic quietperiods, if used.

quietDuration The duration of the quiet period. [TUs]

quietOffset The offset of the quiet period start within thespecified beacon interval. [TUs]


Figure 5.6: Quiet period scheduling

quietCount = n, quietPeriod = 2, quietDuration = d, quietOffset = m

This mechanism solves two potential problems. First, it prevents spoiled quietperiods because of illicit transmissions. Secondly, it prevents transmissionsfrom being spoiled due to channel switches that the STA may have performedduring the quiet measurement.

5.6.3 QUIET MEASUREMENTS

By synchronizing measurements with quiet periods, quiet measurements canbe performed. This is used extensively in the DFS algorithm. At the end of aquiet period, STAs report back to the AP, and the AP schedules measure-ments for the next quiet period.

Figure 5.7 shows this situation from a simulation run, with a cell consisting ofone AP and four STAs. Request and report frames are marked with arrows.

n0 n+1TBTTs

AP

STAs

m

n+2 n+3 n+4 n+5 n+6

AP

STAs

Scheduling

Beacon

Quiet period

d


Figure 5.7: Quiet measurement end

5.6.4 CHANNEL SWITCHING

The AP DFS algorithm may decide to switch channel at any time, via theMLME-CHANNELSWITCH.request primitive. The AP advertises itsswitch of channel to peer STAs by sending a channel switch announcementframe. The channel switch announcement element of this frame, as specifiedby the IEEE 802.11h [12], includes fields holding the parameters specified bytable 5.9. Figure 5.8 shows how the synchronization of a BSS channel switchis implemented. The switch count value is denoted n in the figure.

Table 5.9. Channel switch announcement element fields


channelNumber The channel number to switch to.

channelSwitchCount The number of TBTTs until the beacon intervalwhen the AP will perform the switch.

0 1000 2000 3000 4000 5000 6000 7000 8000

ap[0]

sta[0]

sta[1]

sta[2]

sta[3]

Transmissions following a quiet period

Time [us]

Sta

tions

Original frameACK

Quiet period

Requests

Reports


As with the quiet period implementation, the virtual carrier-sense mechanismis used. At the TBTT preceding the channel switch, NAV is set for a beaconinterval in all STAs. This quiets all transmissions in the cell in good time,avoiding further interference with the radar system. This TBTT is considereda dwell time boundary and all STAs adhere to the same rules relating to dwelltimes as with quiet periods.

In the WOK implementation, the actual channel switch is performed 1 TUbefore the end of the beacon interval specified by the channelSwitch-Count parameter. This guarantees that the switch is performed within the“quiet” period.

Figure 5.8: Channel switch synchronization

channelSwitchCount = n

5.6.5 STA RESCUE OPERATION

As mentioned earlier, a procedure is needed for the case where a channelswitch announcement frame does not reach all STAs. In the WOK model,STAs implement a simple rescue operation by going back to passive scanningafter missing a predefined number of consecutive beacons. This solution ismostly to avoid getting simulations with STAs not participating due to lostcontact with the AP.

n+11TBTTs

AP

Scheduling

Channel switchannouncement

n2

Setting NAV Channel switch

STAs


5.7 A DFS ALGORITHM

In this chapter, a high-level DFS example algorithm is presented. The algo-rithm is based on the procedures and mechanisms previously described.

5.7.1 GENERAL STRUCTURE

A common approach is to divide the DFS algorithm into two main phases, thestart-up phase and the normal operation phase (or in-service monitoringphase). This is the structure of the DFS algorithm treated here, as well. Thestart-up phase concerns the AP only and is performed prior to a BSS start,i.e., on power-up. The normal operation phase algorithm is distributed amongall the stations in the cell, but channel selection decisions are made in the AP.

The AP administers a channel ranking list, holding information of all availa-ble channels. The channels on this list is continously ordered with respect to achannel quality measure.

5.7.2 THE START-UP PHASE

The main objective with having a start-up phase is to select a starting channelfor the BSS that is not occupied by primary users. This is accomplished byrequiring measurements on a channel for a specific duration of time (withoutdetecting primary users) before selection. A secondary goal is to avoid chan-nels that are already used by secondary users, e.g., other WLAN cells.

The start-up phase is divided into two subphases, the initial phase and thestarting channel selection phase.

INITIAL PHASE

The initial phase described here is a modified version of the initial phase pro-posed by Ranheim [19]. During this phase, all channels are measured for apredefined number of TUs. The measurements are based directly on RSS val-ues, using RSSRI measurements, which gives information of the generalinterference levels. Hence, no radar detection procedure is used at this stage.These initial measurements are performed in order to get a (rough) initialranking list of all available channels. This phase is optional and if not used,the initial ranking list is randomly ordered.


STARTING CHANNEL SELECTION PHASE

A typical radar signal is only present in the WLAN cell for less than 0.5% ofthe time. (As described before, the pulse burst is the part of the radar signalthat is assumed detectable.) Therefore, it is unlikely that a radar signal with along burst period, e.g., 100 seconds, will be detected without a very longstart-up phase. Such a long start-up phase is not desirable. On the other hand,and as we have seen, regulatory requirements might demand long initial mon-itoring of a starting channel before being selected.

Furthermore, radar signals with long burst periods typically have burstlengths in the order of hundreds of milliseconds. Therefore, these signals willbe detected with high probability during the normal operation phase usingperiodic quiet measurements. The main task for the start-up phase will be todetect radar signals with smaller burst periods and burst lengths.

The approach used in this phase is to perform measurements on only a fewselect candidate channels, minimizing the risk of not detecting radar signals(if present) on these particular frequencies. This agrees with the approachproposed by Ranheim [19]. The channels measured are determined by the toppositions of the initial ranking list. Time is divided into measurement timeslots and these are allocated equally among the candidate channels.

The starting channel selection phase ends and the normal operation phasebegins when at least one channel has been measured a certain number of timeslots without radar interference or detection of WLAN traffic from neigh-bouring cells. This channel will be used by the AP when initiating the BSS.

When radar or traffic is detected during this phase, the candidate channel ismoved to the bottom of the list and replaced as a candidate by the best non-candidate challenger.

START-UP PHASE PARAMETERS

The start-up phase can be configured using the parameters presented in table5.10.


Table 5.10. Start-up phase parameters

5.7.3 THE NORMAL OPERATION PHASE

The normal operation phase algorithm is based on both scheduled and sponta-neous measurements. Scheduled measurements are centrally controlled bythe AP. The AP chooses which channels to measure, which STAs to performthe measurements, and schedules quiet periods to enhance measurementresults. This procedure is periodic, and the period corresponds to an operatingtest cycle, as described in the IEEE 802.11h [12]. Spontaneous measurementsare performed autonomously by STAs.

QUIET MEASUREMENTS

Periodic measurements are performed every nth beacon interval. A periodicmeasurement is potentially a sequence of submeasurements, each of a prede-termined length. Since high traffic load may prevent spontaneous measure-ments, periodic measurements are possibly the only ones performed duringnormal operation. Therefore, they are scheduled during quiet periods,increasing measurement quality. We introduce the parameters in table 5.11.

Parameters Description

mInitSlotDuration Duration of initial measurements performed on allchannels. [TUs]

numStartCandidates The number of candidates for being selected asstarting channel.

mStartSlotDuration Duration of measurements being performed oncandidate channels. [TUs]

numStartSlotsReq The number of interference-free measurement slotsrequired on a channel before being selected as a

starting channel.


Table 5.11. Some normal operation phase parameters

The AP has exclusive right to perform quiet measurements on the operatingchannel. This is due to the importance of these particular measurements - aradar signal present on the operating channel is the most critical event - inconjunction with the uncertainty factor of beacon/request/report frame deliv-ery. Hence, the AP spends all the quiet period measuring on the operatingchannel.

STAs perform quiet measurements on other channels, and report back to theAP. It is the job of the AP to provide STAs with relevant requests. Theserequests are based on the channel ranking list. How channels are selected tobe measured upon is described below. Note that there is no regulatoryrequirement from ETSI [13] for measurements on other channels than theoperating channel. However, there is no obvious reason not to perform suchmeasurements, since all STAs are supposed to be quiet anyway.

SELECTION OF CHANNELS FOR STA MEASUREMENTS

During the normal operation phase, the ranking list is considered to bedivided into three subsets. These subsets define three levels of priority forchannels when selected for measurements by the AP. The priority levels are:

1) Operating channel (OP)

2) Top contender channels (TOP)

3) Non-top contender channels (NON-TOP)

The latter two sets are ordered with respect to the channel quality.

When the AP decides to perform a channel switch, it is of great importancethat there are good TOP channels available for selection. That is, we do not


mSlotDuration Duration of a measurement slot. [TUs]

mSeqDuration Duration of a quiet measurement sequence. Usually, this isalso the length of the quiet period. [TUs]

mInterval The number of beacon intervals between quiet measurements.

numMeasuringSTAs The number of STAs participating in quiet measurements.


want to switch to a channel that is already occupied by a primary user. Thus,we want more time to be spent on measuring TOP channels than NON-TOPchannels, in order to maintain accurate quality measures for these channels.

For each quiet measurement sequence we have the following n measurementtime slots available for allocation to the STAs:

The scheme used selecting channels for quiet measurements is as follows:

Every other measurement slot is allocated to a TOP channel and every othermeasurement slot is allocated to a NON-TOP channel.

Of course, the number of TOP channels is assumed much less than thenumber of NON-TOP channels. A parameter numTopContenders is usedfor setting this.

Figure 5.9 illustrates an example of how the AP allocates measurement slotsamong channels and STAs. In this example, the AP may select up to six chan-nels for STA measurements at each quiet measurement occasion. Note thatthe participating STAs might vary from time to time. In this algorithm, partic-ipating STAs are chosen randomly among available STAs prior to each quietmeasurement session. As previously mentioned, the AP spends quiet periodsmeasuring on the operating channel.

In this example, the offset of the quiet measurements within the beacon inter-val is fixed. This is optional. Else, the offset is chosen randomly.

Using this scheduling scheme, we can determine the average number ofmeasurement slots allocated to a certain channel per quiet period. This valueindicates the measurement frequency of a channel. A TOP channel will bemeasured upon for an average of

time slots per quiet period. In the example, this number is 0.75. A NON-TOPchannel will be measured upon for an approximate average of

n numMeasuringSTAsmSeqDurationmSlotDuration---------------------------------------×=

n2 numTopContenders×-------------------------------------------------------------


slots per quiet period, where m is the total number of channels available. Inthe example there are 12 channels available, and the expression evaluates to0.42.

By tuning the parameters introduced, we can balance the way channels areselected for measurements in the cell, in order to achieve good substitutechannels with sufficient accuracy. Of course, the more STAs present in thecell, the more measurements can be performed (or less frequent measure-ments are needed for the same result).

SPONTANEOUS MEASUREMENTS

As a complement to scheduled quiet measurements, spontaneous (or autono-mous) measurements can be performed by the STAs. The AP is relieved fromthese responsibilities since it is under the highest traffic load. These measure-ments are performed non-quiet. Thus, traffic load complicates both measur-ing and achieving accurate results.

If parameter doAutoMeasurements is set, a STA tries to perform regularspontaneous measurements. However, for initiating such a measurement inthe WOK model, a number of requirements must be satisfied.

There must be no backoff algorithm in progress. Then, it is likely that there isat least one MPDU waiting to be transmitted. In the WOK model, outgoingtraffic spoils measurements. For the same reason, there must be no frameexchange in progress.

Furthermore, the end timestamp of the measurement is compared with thefuture dwell time boundary, if present. This is to avoid spontaneous measure-ments going into a quiet period.

Spontaneous measurements are performed on the operating channel exclu-sively, for two reasons. First, it improves the radar detection probability onthe operating channel, which is the most important task of DFS. Secondly,measuring on another channel possibly results in lost incoming frames, sincethe measurement is performed non-quiet.

n2 m numTopContenders– 1–( )--------------------------------------------------------------------------------


Figure 5.9: Channel measurement allocation

numTopContenders = 4, numMeasuringSTAs = 2, mInterval = 1,mSeqDuration = 15, mSlotDuration = 5

161 64 40 48 60157 149

Channel ranking list

1535256

AP

STA[0]

OP TOP NON-TOP

STA[1]

AP

STA[0]

1 2 3

4 5

STA[1]

52 44

153

161

3664

161 153

40

5248

157

36 44

149

15760

52 64

153 40 36

48 44

56 56

56 56

36 44

STA[2]

3

STA[2]


Transmissions and receptions of frames are not affected by spontaneousmeasurements in progress. However, to accept a radar detection as valid, theDFS algorithm requires the basic measurement report to be defined accordingto table 5.12.

Table 5.12. A vaild radar detection in a spontaneous measurement

This is a restrictive acceptance rule. It is justified by the fact that the uncer-tainty factors regarding PHY-level radar detection mechanisms is not repre-sented in the WOK model.

Basic report flag Value

BSS false

Foreign PLCP header false

Unknown false

Primary user true

Unmeasured false


NORMAL OPERATION PHASE CONFIGURABLE PARAMETERS

The parameters associated with the normal operation phase are summarizedin table 5.13.

Table 5.13. DFS normal operation parameters

5.7.4 THE CHANNEL QUALITY MEASURE

In this algorithm, two types of measurements are performed. The initial phaseis based on RSSRI measurements, and the rest of the algorithm is based onbasic measurements.

In the algorithm, a quality measure Qi for channel i is defined as:


numTopContenders The number of TOP channels.

numMeasuringSTAs The number of STAs participating in quietmeasurements.

mInterval The number of beacon intervals between quietmeasurements.

numSeqDuration Duration of a quiet measurement sequence. [TUs]

mSlotDuration Duration of a quiet measurement slot. [TUs]

fixedOffset Switches fixed offset on/off.{true, false}

mOffset Offset within the beacon interval of the quietmeasurement, if fixed. [TUs]

doAutoMeasurements Switches spontaneous measurements on/off. (STA){true, false}

mAutoDuration Duration of spontaneous measurements. (STA)[TUs]

nonOccupancyPeriod Duration of time during which a channel must notbe selected as operating, following a radar

detection. [s]

radarForgettingFactor Tunes the forgetting tendency of a radar detection.[1/s]

Qi QiRSS QiRadar×=


where

and

In the QiRRS expression, j denotes the RSSRI interference interval and ljdenotes the RSSRI density for that interval, as defined in “Implementation ofMeasurements” on page 30. Hence, high interference levels during RSSRImeasurements decrease the value of QiRSS. QiRadar is set to zero upon detec-tion of a radar signal.

is the time elapsed since last measurement. FRSS and FRadar denote forget-ting factors, adjusting how fast the algorithm forgets about measurement data.Eventually, if no measurements are performed or no measurements indicateany new interfering signals, both QiRSS and QiRadar will regain their maximumvalues1.

This quality measure definition has been influenced by the quality measureproposed by Johansson and Ranheim [20].

5.7.5 LATE ADDITIONS

The exchange of DFS management frames and buffered data frames follow-ing quiet periods, results in increased traffic load. As we will see later, thisbecomes a problem when the number of measuring and reporting STAsincreases, resulting in an increased number of collisions. From a DFS point of

1. At start-up, both QiRSS and QiRadar are initialized to their respective maxi-mum values.

QiRSS

7 j–( ) l j , at measurement×0

7

∑QiRSSLast FRSS T , expression 7<∆×+

7 , expression 7≥

=

QiRadar

0 , radar detected

QiRadarLast FRadar T , expression 1<∆×+

1 , expression 1≥

=

∆T


view this is severe, since the AP may have detected a radar signal during thequiet period and wants to announce a channel switch. As previously men-tioned, such an announcement requires no ACK (since it is sent broadcast),and consequently, a collision including such a frame is not discovered.

When evaluating the algorithm, we look at some ways of limiting this prob-lem, and therefore an additional parameter onlyReportRadar is intro-duced. This parameter makes it possible to disable the reporting ofmeasurements at STAs, during which no radar signals were detected.

5.8 EVALUTATION OF THE ALGORITHM

In order to evaluate the DFS algorithm described above, some simulation sce-narios and WLAN topologies are introduced. Further, a set of performancemeasures are determined. The evaluation is then based on these measures,performing sets of simulation runs. These simulation sets are described in[22].

5.8.1 SCENARIOS AND TOPOLOGIES

Mainly two scenarios are used. The ideal scenario includes the topologydepicted in figure 5.10, a small BSS consisting of one AP and four STAs. Theideal scenario is used as a reference environment model, indicating the per-formance of DFS when there are good ambient conditions. All distances areshort and all individual links are configured using a merciful channel model,namely the AWGN model, which was described in chapter “The WirelessMedium” on page 19. Hence, e.g., packet error rate is zero during normal cir-cumstances in this scenario.


Figure 5.10: The ideal scenario topology

The office scenario includes the topology depicted in figure 5.11, a largerBSS consisting of one AP and 10 STAs. This scenario aims to model a roughoffice environment. The distances are longer than for the ideal scenario, andthe devices are separated by walls, increasing attenuation of signals. Further,channel model A is used, which corresponds to a typical office environment.This scenario is used for studying DFS performance under difficult condi-tions, with high packet error rates and many STAs competing for the medium.

A third scenario will be used briefly for validating the detection of neighbour-ing BSS traffic during the start-up phase. The hot spot scenario models twosmall neighbouring WLAN cells in an open environment, similar to an air-port. The C channel model is used, which corresponds to an open spaceindoor environment.

7 m7 m

7 m

7 m


Figure 5.11: The office scenario topology

5.8.2 PERFORMANCE MEASURES

DFS performance can be evaluated using several different approaches. Here,a set of performance measures is introduced, based on DFS load, radar detec-tion performance, and ETSI requirements.

OVERHEAD

The DFS work load adds overhead and may therefore complicate other activ-ities in the WLAN cell. The most important activity is of course the exchangeof data frames. The overhead introduced by the DFS algorithm can be deter-mined by studying traffic related parameters.

Throughput per MSDU, i.e., LLC throughput, is interesting from a short-term

15 m

15 m

STA[0] STA[1] STA[2]

STA[3]

STA[4]

STA[5] STA[6]

STA[7] STA[8]

STA[9]


perspective, since it indicates the current bandwidth of the network from theMAC user’s view.

Further, and as we will see, additional DFS related traffic possibly increasetypical WLAN problems, such as collisions. Therefore, it may be interestingto study how the number of ACK failures varies with DFS work load.

RADAR DETECTION AND AVOIDANCE

In order to determine the performance of the DFS radar detection and avoid-ance mechanisms, i.e., the actual algorithm, we look at two similar measures.

The radar detection time indicates how long the radar signal is present on themedium before being detected for the first time. It is interesting to observehow this time depends on the channel priority, DFS work load, etc. Radardetection time can easily be translated into radar burst number, knowing theradar signal burst period. Average number of bursts before detection is usedas a measure when comparing different algorithm configurations.

ETSI REQUIREMENTS

The satisfaction of the regulatory requirements for DFS specified by ETSI[13], is also considered a performance measure. These requirements weretreated in chapter “Regulatory Requirements” on page 54.

5.8.3 DFS OVERHEAD

The most obvious overhead introduced by the DFS algorithm comes fromquiet measurements, since outgoing traffic is blocked at all devices duringthese measurements. Figure 5.12 shows throughput variations experienced bythe AP in two separate simulation runs. It can be seen clearly that the APusing DFS experiences more poor transmissions due to quiet periods.


Figure 5.12: Throughput vs. DFS usage

Simulation runs included in simulation set 1, see [22].

As previously mentioned, quiet periods also introduce a collision problem.With increasing number of STAs participating in the quiet measurements, theACK failure ratio increases as well because of these collisions. This problemcan be seen in figure 5.13, showing a situation directly following a quietperiod. Collisions are marked with dashed vertical lines, and colliding framesare encircled. In this WLAN cell, all 10 STAs participates in (and reportsresults of) quiet measurements. Consequently, the AP have 10 measurementrequest frames to send regarding the next quiet period.

This is an obvious problem with this algorithm. The MAC backoff procedure,which is performed at all devices at the quiet period end, handles theincreased competition of the medium accordingly.

206 207 208 209 210 211 2120

5

10

15

20

25

Mbp

s

Time [s]

AP throughput, no DFS

206 207 208 209 210 211 2120

5

10

15

20

25

Mbp

s

Time [s]

AP throughput using DFS

Channel switch


Figure 5.13: Quiet period end with collisions

Simulation run included in simulation set 3, see [22].

However, the probability for an arbitrary STA to pick the same random back-off count1 as someone else, following a quiet period, is

where n is the number of STAs competing for the medium. In the simulationdescribed, n = 10 and thus, the collision probability is 0.48. This is severe,considering an AP wanting to transmit a channel switch announcementframe. As a comparison, using three STAs results in a collision probability of0.17.

One way of limiting this problem is to demand reports from the STAs only atthe detection of primary users. This approach works fine for this particularalgorithm. But we can imagine a more sophisticated algorithm based on sev-

1. Here we assume that all devices use the minimum contention windowvalue, i.e., CW = 15. This is a worst case scenario, but not unlikely.

0 500 1000 1500 2000 2500 3000 3500 4000 4500 5000

ap[0]

sta[0]

sta[1]

sta[2]

sta[3]

sta[4]

sta[5]

sta[6]

sta[7]

sta[8]

sta[9]

Collisions following a quiet period

Time [us]

Sta

tions

Original frameACK

P Collision at first tx attempt( ) 115

16------

n–=


eral different types of measurements, e.g., an algorithm that considers generalinterference levels as well when making channel switch decisions. Then, therequirements on the STAs increase dramatically, having to evaluate eachreport, and decide if it is worth sending. Hence, much of the work load ismoved from the AP to the STAs. Further, and most important, this approachdoes not comply with the IEEE 802.11h draft [12], which demands all meas-urement requests to be reported by STAs.

Another way to address the collision problem is for the AP to limit thenumber of STAs participating in the quiet measurements. In the algorithmthis is done via the numMeasuringSTAs parameter. Almost the same DFSperformance may be achieved with a less number of STAs.

Figure 5.14 shows the number of ACK failures during the same period oftime using the two approaches described above.

Figure 5.14: ACK failures at the AP


Note that there is no end in itself to prevent these particular collisions. Colli-

0 2 4 6 8 100

50

100

150

200

250

300

350ACK failures at AP

# of participating STAs

STAs report all measurementsSTAs report primary users only


sions are normal behavior in WLANs and as long as there is no obvious per-formance degrading, i.e., failed transmissions1, the handling of this situationcan be done by basic MAC protocol mechanisms.

Thus, limiting the number of participating STAs is enough for achievingacceptable performance, at least during normal traffic load (the traffic load inthese simulation runs is approximately 25%). Of course, from a performanceperspective, the best solution for this particular algorithm is for the STAs toreport measurement data only at radar detection.

5.8.4 DFS RADAR DETECTION AND AVOIDANCE

Within the context of this report, the performance of the actual algorithm ismeasured by looking at the ability to detect and avoid primary users. In orderto evaluate the channel priority scheme used in the algorithm for this matter,we study how the time before first detection varies with quiet measurementlengths. Figure 5.15 shows how radar signals appears on the medium in aWLAN cell, when they are detected by the DFS algorithm, and when channelswitches are performed in the BSS during one of the simulation runs.

The radar appearance behavior is exaggerated in these simulations, in order toachieve results in reasonable time.

Note the “unnecessary” first channel switch that is performed in the cell. Thealgorithm chooses a (TOP) channel, that turns out to be occupied by radar aswell. These kinds of mistakes cannot be avoided, as long as the algorithm isbased purely on past events. In this case the past is “too present”, i.e., thealgorithm did not detect the first radar burst on the TOP channel. It is impor-tant to limit the radar detection time on TOP channels. Decreasing the detec-tion time increases the probability of choosing a “radar-safe” channel when aswitch must be made.

1. A transmission of a frame is considered failed if the MAC gives up on it,i.e., it has consumed a number of retries. This retry number is configura-ble via the MAC MIB. A common value is 7.


Figure 5.15: Radar signal appearance and BSS channel switches

Simulation run included in simulation set 4, see [22].

In figure 5.16 we can observe how the average number of bursts appearancesbefore (first) detection varies with quiet period lengths. Here, only TOP andNON-TOP channels are considered.

Translating burst numbers into time, these simulations show that by usingquiet period lengths of 8 TUs, the algorithm requires less than 20 seconds (onaverage) for detecting an arbitrary radar signal on a TOP channel.

0 50 100 150 200 250 300

36 40 44 48 52 56 60 64

100104108112116120124128132136140

Radar appearances

Time [s]

Cha

nnel

0 50 100 150 200 250 300

36 40 44 48 52 56 60 64

100104108112116120124128132136140

Operating channel

Time [s]

Cha

nnel

UndetectedDetected


Figure 5.16: Average radar signal detection time on TOP and NON-TOP channels


In general, radar signals of type 2 are the most difficult to detect, having smallburst durations. A natural approach would be to schedule (shorter) quiet peri-ods much more frequently, but the IEEE 802.11h draft [12] provides nomeans for this, unlike HiperLAN/2. Note that, by using these particular DFSsettings, the detection of the first burst of a type 3 radar signal1 is guaranteedif all TOP channels are measured every quiet period. This is the case whenthe quiet period length is 8 or 16 TUs.

The radar detection probabilities on TOP channels can be estimated theoreti-cally, given a certain DFS configuration. The detection probabilities as func-tions of time, using the same DFS settings as above, are plotted in figure 5.17and figure 5.18.

These plots give some hints of what can be stated about a TOP channel atselection time. For example, using quiet periods of 16 TUs, we have:

P(TOP channel was radar free 60 seconds ago) > 0.9

1. A type 3 radar signal has a burst length of 210 ms. The burst lengths oftype 1 and 2 radar signals are 26 and 5 ms, respectively.

TOP NON−TOP02468

101214161820

25

30

35

40

45

50Quiet 8%

TOP NON−TOP0

2

4

6

8

10

15

20

25

30Quiet 16 %

TOP NON−TOP0

5

10

15

20

25

30

35

40

45

50

60

70

80

90

100Quiet 4%

Bur

st #

Radar 1Radar 2Radar 3


Figure 5.17: Detection probability for radar type 1 at different quiet period lengths

Figure 5.18: Detection probability for radar type 2 at different quiet period lengths

Note again the dependence on history. Of course, the TOP channel must havebeen rated TOP for the duration of time considered making such statements.Further, there is always a possibility that a new radar signal has appearedrecently, and not yet being detected. This possibility, however, depends onhow new radar signal sources emerge in the environment and is not treated inthis report.

0 50 100 150 200 2500.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1Detection probability − radar signal type 1

Time [s]

P

Quiet 4% Quiet 8% Quiet 16%

0 20 40 60 80 100 120 140 1600

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1Detection probability − radar signal type 2

Time [s]

P

Quiet 4% Quiet 8% Quiet 16%


The bar charts in figure 5.19 show the average number of bursts appearancesbefore (first) detection on the OP channel. These values indicate what is mostimportant, namely the duration of time a WLAN cell interfers with the radarsystem. This time should be minimized and ideally, the first radar burst isdetected. As can be seen in the figure, this is not achieved in these simula-tions. In the bar chart to the right, spontaneous measurements are performedat (all) STAs, in addition to quiet measurements of 12 TUs per beacon inter-val. Unlike quiet measurements, both the result of and ability to performspontaneous measurements depends on system load. In these simulations,each STA tries to perform measurements every 4 TUs, i.e., mAutoDura-tion = 4. Considering the restrictive acceptance rules in the algorithmregarding spontaneous measurements, the performance is surprisingly good,even at high traffic loads. As a comparison, the left bar chart shows the corre-sponding results using quiet measurements only.

Figure 5.19: Average radar signal detection time on the OP channel

Simulation runs included in simulation set 4 (left) and set 6 (right), see [22].

5.8.5 ETSI REQUIREMENTS

Here, the performance with respect to regulatory requirements is evaluated.

~20% ~50% ~70%0

1

1.5

2

2.5

3

3.5

4

Load

Spontaneous measurementsQuiet 12%

16% 12% 8% 4%0

1

2

3

4

5

6

7

8

9

10Quiet measurements only

Quiet

Bur

st #


AT START-UP

The channel availability check time is defined as the time during which achannel shall be checked for the presence of radar signals before beingselected as a starting channel. ETSI [13] requires this time to be more than 60seconds. In the algorithm described, this is achieved by configuring parame-ters mStartSlotDuration and numStartSlotsReq appropriately.Figure 5.20 shows a simulation example of how a start-up phase mightprogress.

Figure 5.20: Start-up phase

Here, the algorithm is configured to meet the requirement. This is done byusing a measurement slot duration of 1000 TUs and requiring 60 such meas-urements on a candidate channel before selection as operating channel. Ascan be seen, at any given time there are three candidate channels monitoredduring the entire start-up phase. After approximately 211 seconds channel 44has been measured upon for 60 seconds1, without detecting any radar or

1. Actually, the channel has been measured upon slightly longer, since a TUis 1024 us, not 1 ms.

0 20 40 60 80 100 120 140 160 180 200 220

36 40 44 48 52 56 60 64

100104108112116120124128132136140

Radar appearances

Time [s]

Cha

nnel

0 20 40 60 80 100 120 140 160 180 200 220

36 40 44 48 52 56 60 64

100104108112116120124128132136140

Starting candidate channels

Time [s]

Cha

nnel

UndetectedDetected

WLAN signals detected

Starting channel selection


WLAN signals. Consequently, it is selected as a starting channel and therequirement is satisfied.

AT RADAR DETECTION

Figure 5.21 shows the events of a successful channel switch during a simula-tion run. As can be seen, the algorithm satisfies the requirements specified byETSI [13]. The channel move time must be less than 10 seconds, and thechannel closing transmission time must be less than 260 ms. In the figure, thechannel move time is about 150 ms. For a successful channel switch, theupper limit of the channel move time is two beacon intervals.

Figure 5.21: A successful BSS channel switch

However, the algorithm cannot guarantee a successful channel switch, sincechannel switch announcement frames can be lost. As described earlier, theSTAs in the WOK model implement a simple rescue operation that is acti-vated when beacons stop arriving, but until this operation is activated theSTAs will continue their transmission attempts. Hence, in such a situation,the channel closing transmission time requirement is not satisfied.

0 50 100 150 200 250

ap[0]

sta[0]

sta[1]

sta[2]

sta[3]

Transmissions

Time [ms]

Sta

tions

TBTT TBTT

Channel switch

NAV set

Quiet

(Radar detection)

TBTT


The non-occupancy period requirement, disqualifying a channel as operatingfor more than 30 minutes upon radar detection, is trivially satisfied by settingthe corresponding parameter nonOccupancyPeriod to 1800 (s).

UNIFORM SPREADING

The uniform spreading requirement specified by ETSI [13] cannot be satis-fied using a DFS start-up phase selecting a channel based on interference lev-els of any kind, since introducing channel quality measures implies an orderof precedence among available channels. This counteracts the uniform proba-bility distribution required. However, by skipping the start-up phase, the algo-rithm selects starting channel randomly. Hence, the requirement can besatisfied but at the expense of other requirements not being satisfied.

5.9 CONCLUSION

The IEEE 802.11h draft [12] supports the concept of a high-level DFS algo-rithm separated logically from the MAC. Nevertheless, such an algorithm isbased on extensive MAC-level functionality. This report shows, however, thatrelevant MAC procedures can be implemented using the mechanisms alreadypresent, such as the virtual carrier-sense (NAV) and synchronization via bea-coning. Further, some extensions must be made to the interfaces introducedby [12] in order to implement DFS.

Regarding the example algorithm, it cannot guarantee the detection of thefirst radar burst on the operating channel. Thus, WLAN interference withradar systems cannot be avoided completely. In general, radar signals of type2 have been shown to be the most difficult to detect, having small burst dura-tions.

The algorithm can present a radar-safe substitute channel with high probabil-ity when a channel switch must be performed. This is achieved by utilizingthe STAs for quiet measurements and monitoring a few select top-rankedchannels more often than others.

The collision problem following quiet periods is severe using this algorithm.By limiting the number of STAs participating in quiet measurements, the loadfollowing quiet periods is reduced and hence, the collision probability isdecreased.


The collision problem also implies that the transmission closing time limitspecified by ETSI [13] may be exceeded. The algorithm in its current formdoes not handle the situation where a channel switch announcement frame islost. However, when the channel switch announcement frame does not getlost, the requirement is satisfied.

Other requirements specified by [13] are satisfied by the algorithm, if thealgorithm is configured appropriately.

The quiet measurement support of the IEEE 802.11h draft is very limited,only allowing one quiet period per beacon interval. This implies the need forspontaneous measurements.

5.10 COMMENTS

DFS is, in the context of the IEEE 802.11 standard, a completely new area.Almost nothing has been written on this topic. Therefore, the ideas in thisreport are based almost solely on the framework provided by the IEEE802.11h draft. A somewhat surprising result for us was that quiet periodmeasurements, as defined by the IEEE 802.11h draft, are not enough fordetecting radar signals on the operating channel satisfactory. If this had beenknown in advance, the concept of spontaneous measurements should havebeen explored much more extensively.

We further establish that we underestimated the collision problem introducedby quiet periods. As already mentioned, this is particularly severe for broad-cast frames such as the channel switch announcement frame. A simple solu-tion would be to repeat the transmission of such frames with regular intervalsfor a predefined number of times. The STAs simply neglect announcements ifalready received. This procedure is easy to implement, but has not been sodue to lack of time.

95

6LINK ADAPTATION

6.1 INTRODUCTION

Link Adaptation is used in most wireless communication systems today, inorder to adjust the data transmission rate to different circumstances. How toimplement a link adaptation algorithm is not defined in the IEEE 802.11standard though. Instead it has become a competition between vendors find-ing the best and most appropriate algorithm. All of this leads to difficulties infinding public material about well suitable algorithms.

6.1.1 PURPOSE

The purpose of this chapter is twofold. The primary purpose is to demonstratehow link adaptation may fit into the WOK model and secondly to propose away of implementing a link adaptation algorithm on MAC level in IEEE802.11a. This algorithm is evaluated for some different environments.

6.1.2 PROBLEM DESCRIPTION

Link Adaptation deals with the matter of how to establish as fast transmis-sions as possible without losing the quality of the link. It is important toimplement a link adaptation algorithm in a WLAN, especially when interfe-

by Magnus Karlsson


rence is present and there are many rates to choose among. This could beaccomplished by a dynamic selection of the data transmission rate at a givenpoint of time.

Basically it is a trade-off between high rate and good quality of the radio link.Higher rates generally result in higher probability of frame errors, especiallywhen the SNR value is poor, see chapter “The Wireless Medium” on page 19.In the WOK model, channel condition could be defined as channel modelused and presence of background noise and interference. Channel conditionas well as distance between transmitter and receiver are factors that affect theSNR value. Both these factors could be changing over time. The distancebetween two stations may change if one or both of the stations are mobile. Inthe WOK model all stations are stationary, i.e. they are not mobile during asimulation. The transmission rate should be chosen in an adapted mannersince the wireless channel condition varies over time. The goal is to maxi-mize the system throughput in some sense, i.e. to deliver as much data as pos-sible during a certain amount of time. If one station succeeds in deliveringdata at high rate it will also facilitate earlier data delivery from other stations.

An ideal situation for a transmitter would be to have certain “perfect” knowl-edge in advance. This knowledge would include:

• SNR at the receiving STA.

• frame error rate vs. SNR for different transmission rates at the receivingSTA.

Based on this knowledge it would be easy to choose appropriate transmissionrate. Unfortunately, in a real situation neither of these variables are known tothe transmitter. The purpose of an algorithm would therefore be to estimatethe conditions at a receiving station.

Most algorithms make use of the fact that recent transmissions have been suc-cessful or unsuccessful. History is a way to predict future events. A success-ful transmission is here defined as a data transmission followed by an error-free acknowledgement frame (ACK), see figure 6.1.

Thus, if it is possible to estimate the loss of the signal strength and predict thechannel condition along with keeping track of statistics from earlier transmis-sions and receptions it could serve as a base for choosing an appropriatetransmission rate.

Chapter 6 - Link Adaptation 97

Station A receives an error-free ACK from station B. Notice that the duration of a data frametransmission in general is longer than an ACK frame transmission. This depends on

transmission rate and frame length though.

Figure 6.1: Successful transmission

If hidden nodes are introduced the probability for collisions is increased. Thisis also the case if the traffic load is high. What is the effect of collisions whenit comes to link adaptation?

In the IEEE 802.11 standard an optional mechanism called RTS/CTS couldbe used as an attempt to prevent collisions. Easily explained, there is an addi-tional frame exchange between transmitter and receiver prior to the real frameexchange. Other stations will then know in advance of this transmission ta-king place and a positive effect of this mechanism would therefore be todecrease the probability of collisions. A negative effect is however reducedthroughput, because there are two extra frames sent before each real frame issent.

The maximum number of unsuccessful transmission attempts for an MSDUis determined by the MACMIB parameter dot11ShortRetryLimit1.When this number has been exceeded the MSDU is dropped. Some adjust-ment mechanism in a link adaptation algorithm should take care of this factand prevent this from happening again.

There are basically two types of networks in WLAN; ad-hoc networks inwhich stations transmit directly to each other and infrastructure networks inwhich stations transmit via an access point. The WOK model is an infrastruc-ture network. An interesting question that turns up is, as the WOK modelincludes both STAs and APs: will link adaptation work differently in a STAthan in an AP?

1. The default value of this parameter according to the IEEE 802.11 stand-ard is 7.

station

time

A

B

DATA

ACK


As stated before the length of the frame might be an issue in link adaptation.A recent study by Qiao and Choi [3] made use of this fact by implementingdynamic fragmentation of MSDUs, in combination with dynamic PHY modeselection, for each MPDU transmission. Analysis results show that the effectof dynamic fragmentation is much smaller than the effect of changing PHYmode, according to Qiao, Choi and Shin [4].

There are four modulation schemes supported in the IEEE 802.11a PHY;BPSK, QPSK, 16-QAM and 64-QAM, see table 6.1. A certain modulationand code rate is mapped to a certain mode and data rate.

Table 6.1. IEEE 802.11a and its eight PHY modes

It is not defined in the standard when a certain rate should be used. This iscompletely a choice for the vendor to make and implement. Yet, there aresome basic rules about multirate support that should be followed, defined inthe IEEE 802.11 standard [1].

6.1.3 LIMITATIONS

Link adaptation is implemented in an IEEE 802.11a infrastructure environ-ment under the DCF function. All STAs in the WOK model are associatedwith one and the same AP during a simulation. The RTS/CTS mechanism isnot implemented, due to the fact that it is rarely used in today’s applications.Dynamic fragmentation is not considered as well, because the expected effect

Mode Modulation CodeRate

DataRate

Bytes perSymbol

1 BPSK 1/2 6 Mbps 3

2 BPSK 3/4 9 Mbps 4.5

3 QPSK 1/2 12 Mbps 6

4 QPSK 3/4 18 Mbps 9

5 16-QAM 1/2 24 Mbps 12

6 16-QAM 3/4 36 Mbps 18

7 64-QAM 2/3 48 Mbps 24

8 64-QAM 3/4 54 Mbps 27


is too small.

Proposed link adaptation algorithm is not implemented to handle dynamicPHY mode selection when sending acknowledgement (ACK) frames. ACKframes are sent at the same rate as the incoming frame to acknowledge. Addi-tionaly, all frames may be sent at any of the eight different rates, exceptbroadcast frames that are always sent at the lowest rate.

6.2 INTEGRATION IN THE WOK MODEL

Previously mentioned study by Qiao, Choi and Shin [4] has turned aside fromthe IEEE 802.11a standard, assuming some kind of communication betweenthe transmitter and the receiver regarding the link condition. An intention inthis study has been to support interoperability between devices from differentvendors and hence to hold on to the IEEE 802.11a standard to a great extent.

How is the WOK model link adaptation algorithm integrated on MAC level inIEEE 802.11a?

One important extension to the IEEE 802.11a standard is to give the MAClevel in the WOK model an indication of SNR for a frame received. ReceivedSignal Strength (RSS) in the WOK model is a value mapped from a certainpower received. The received power in turn depends on transmit power leveland signal loss. These elements are fixed during a simulation in the WOKmodel. An SNR measurement is based on both RSS and noise level measure-ments. As the noise level may change in contrast to the RSS, an RSS meas-urement only would have been less meaningful to base a link adaptationalgorithm on.

It would have been possible to integrate the algorithm in several modules onMAC level. Yet, in order to separate this algorithm from other modules linkadaptation is implemented in a link adaptation module to which informationof traffic on MAC level is sent, see figure 6.2. Based on this information thedata rate parameter may be set in this module.


Figure 6.2: Link adaptation integrated on MAC level

6.2.1 A LINK ADAPTATION ALGORITHM

INTRODUCTION

The link adaptation algorithm proposed is an extension of a link adaptationalgorithm, implemented for an IEEE 802.11b STA in an infrastructure net-work, by Pavon and Choi [2]. Instead of using RSS measurements, SNRmeasurements are used in the WOK model. Additionaly, the algorithm isimplemented in an IEEE 802.11a PHY for STAs as well as for an AP. In orderto adapt the data transmission rate better to more rapid SNR fluctuations, thealgorithm has been somewhat adjusted. However, the basic idea is still thesame and will now be further explained for the STA as well as for the AP.

INTEGRATION IN A STA

An assumption of being able to perform SNR measurements in an IEEE802.11a PHY is made. Measurements on frames received from its AP are per-formed, as all outgoing frames from a STA are sent to its destination via anAP in an infrastructure network. Depending on SNR measurements fromframes received from the AP addressed to itself, and some other informationavailable on MAC level, the transmitting STA chooses an appropriate trans-

Protocol

Reception

LinkAdaptation

MAC


mission rate. Transmission rate chosen is in fact a function of average SNR,thresholds, frame size, number of retransmission attempts, failure/success oflast MSDU sent and some algorithm parameter settings.

INTEGRATION IN AN AP

In the AP the algorithm is working quite similarly as in a STA, but in order todecrease the probability of frame errors broadcast frames are sent at the low-est data rate. A dynamic growing table is used to handle data about differentlinks connected to each STA.

GENERAL DESCRIPTION

The overall algorithm is explained more clearly in figure 6.3. All grey markedsquares define the core of the algorithm. These functions may be triggered bythe incoming messages transmission request, MSDU failure and frame recep-tion. At the end of each branch in the figure the passive top state is re-entered.

Thresholds and average SNR values are crucial for the algorithm, why theseare briefly explained here.

Thresholds (Th) and average SNR are updated according to formulas below.Th[i,j] is defined as the minimum SNRavg value, above which transmissionof a frame within length interval1 j, at PHY mode2 i, may be performed.

For example, Th[5,2] is the estimated minimum threshold of the SNRavgvalue to ensure correct transmission of a frame of length between 100 and1000 bytes at PHY mode 5, i.e. at 24 Mbps.

1. There are three intervals implemented, defined according to Pavon andChoi [2].

2. Each mode corresponds to a certain data rate, defined in the IEEE802.11a standard [7].

Thn 1+ i j,[ ] a1 Thn i j,[ ] a2 SNRSNRavgn 1+

⋅+⋅a3 SNRavgn a4 SNR

a1 a2+⋅+⋅

1 a3 a4+, 1 a1 0 a2 0 a3 0 a4 0≥,≥,≥,≥,

==

= =


Figure 6.3: Main structure for the link adaptation algorithm

IDLE

Transmission

Request

MSDU

Failure

Frame

Reception

Basis forrate selection

updated

Transmissionrate selected

FrameTransmission

Addressedto itself

Yes

SNR_avgand moreupdated

-NoThresholds

updated

-

-

-


There are eight parameters connected to the algorithm. Usage of these para-meters are briefly explained in table 6.2.

Table 6.2. Link adaptation parameters and when they are used

6.3 SIMULATIONS

The link adaptation algorithm has been run in several different environments.In all simulations channel model A has been used, see chapter “The WirelessMedium” on page 19.

6.3.1 ENVIRONMENTS

An environment is here defined as a function f=f(a,b,c,d,e). Definitions ofvariables are explained in table 6.3.

Parameter Usage

a1 updating thresholds

a2 updating thresholds

a3 updating average SNR

a4 updating average SNR

a5 decrement of rate

a6 decrement of thresholds

a7 transition to bad state

a8 transition to good state


Table 6.3. Simulation variables

The idea has been to evaluate link adaptation for changes of each of the varia-bles listed above. An overview of the simulations is presented at the end ofthis chapter.

NUMBER OF STATIONS

The number of stations associated with an AP varies. A limit of ten stations isset as maximum in these simulations. Simulations with five and ten stationshave been run.

TRAFFIC LOAD

Traffic load is here defined as the percentage of time when the AP is not idle.If the AP is not idle it could be in one of the states {backoff, reception ortransmission}. Simulations have varied between low (5-40%) and high (40-90%) load.

BACKGROUND NOISE

Background noise has been implemented as a constant noise level affectingall channels equally during a simulation. Simulations have varied betweentwo different levels of noise power.

INTERFERENCE

A changing noise level during a simulation has been defined as some kind ofinterference present. Simulations have varied between two different ways of

Variable Description

a number of stations

b traffic load

c background noise

d interference

e hidden nodes


changing noise levels. The idea has been to switch noise level slowly or morerapidly. In this study two different switching rates have been tested.

HIDDEN NODES

Hidden nodes have been defined for some of the simulations. Either no sta-tions are hidden to each other or two stations are hidden to each other.

OVERVIEW

Table 6.4. Overview of the simulations

6.3.2 GENERAL SETTINGS

Stations and access points have fixed coordinates and fixed attenuation perlink. Positions for simulations with five and ten stations are shown infigure 6.4 and in figure 6.5. Attenuation for each link has been listed intable 6.5 and is given as a triplet of attenuation elements (distance power lawexponent, partition attenuation factor, floor attenuation factor), see chapter“The Wireless Medium” on page 19. All simulations have been run during 50seconds of simulation time.

Simulation(1-7)

Number ofstations (5/10)

Traffic load(Low/High)

InterferenceFixed (power level)/Dynamic (slow/fast)

HiddenNodes

(Yes/No)

1 5 Low Fixed (-100 dBm) No

2 5 Low Fixed (- 90 dBm) No

3 5 High Fixed (- 90 dBm) No

4 5 Low Fixed (- 90 dBm) Yes

5 10 Low Fixed (- 90 dBm) No

6 5 Low Dynamic (fast) No

7 5 Low Dynamic (slow) No


The link between sta[3] and ap[0] has been in focus.

Figure 6.4: Five stations and an access point in an office environment

The link between sta[5] and ap[0] has been in focus.

Figure 6.5: Ten stations and an access point in an office environment

−10 −8 −6 −4 −2 0 2 4 6 8

−8

−6

−4

−2

0

2

4

[m]

[m]

ap[0] sta[0]

sta[1]

sta[2]sta[3]

sta[4]

Five stations and an access point in an office environment

−15 −10 −5 0 5 10 15 20 25

−15

−10

−5

0

5

10

15

[m]

[m]

sta[9] sta[0]

sta[1]

sta[2]

sta[3]

ap[0]

sta[4]sta[5]sta[6]sta[7]

sta[8]

Ten stations and an access point in an office environment


Table 6.5. Attenuation for different links

The link adaptation algorithm parameters have been fixed according totable 6.6.

Table 6.6. Link adaptation algorithm parameter settings

6.3.3 RESULTS

The outcome of each simulation is either presented in some different figuresor in a table at the end of this chapter. Information about the simulations withfigures and their interpretation is given below.

Simulation number Attenuation Link

1-3, 5, 6-7 (3.1, 22, 0) All

4 (3.1, 33, 0) ap[0] <=> sta[0]

4 (3.1, 33, 0) sta[1] <=> sta[0]

4 (3.1, 33, 0) sta[2] <=> sta[0]

4 (3.1,34, 0) sta[3] <=> sta[0]

4 (3.1, 33, 0) sta[4] <=> sta[0]

4 (3.1, 22, 0) Others

Parameter Value

a1 0.3

a2 0.7

a3 0.5

a4 0.5

a5 2

a6 2

a7 3

a8 5


In the first figure of all simulations the transmission rate, current noise leveland SNR that was last detected is presented. This figure is from the end of thesimulation, during two seconds of simulation time. The x-axis in this figuredenotes the offset fragment number of the fragments sent, counted from thestart of this particular time gap. Stars denote successful transmissions,whereas circles denote unsuccessful transmissions. Maximum data transmis-sion rate is 54 Mbps. An SNR value of 12 dB is considered as a relatively lowvalue in these simulations, whereas an SNR value above 20 dB is relativelyhigh. The lowest noise level for all simulations has been -100 dBm.

In the second figure of all simulations statistics about the simulation is given.Transmission results shows the fraction of unsuccessful versus successfultransmissions. How many of the unsuccessful transmissions are due to colli-sions and how many are due to bit errors? This result is given under unsuc-cessful transmissions. Average mode used says something about data ratechosen and average throughput shows the average throughput for eachMSDU sent. Notice that an average throughput above 20 Mbps has to be con-sidered as good as each frame has an overhead.

In simulation 4 a more detailed description of some of the transmissions inthe first figure, of that simulation, is presented. These particular transmissionsare the ones within a square, pointed to with the text “see transmission detailsbelow”. In simulation 7 a figure of the last 20 seconds at the end of the simu-lation is published. The purpose of adding this extra figure is to demonstratehow the transmission rate adapts to a switching noise level during a longertime interval.


Simulation 1

The transmission rates for sta[3] are presented in figure 6.6. Due to differentlengths of the fragments, the transmission rate varied between 24 Mbps and54 Mbps. Fragments within interval one were sent at the highest rate. As thecurrent noise level was constant -100 dBm during this simulation the detec-tion of each SNR value on frames sent from its AP was constant about 22 dB.

Transmission rates for sta[3] during a time interval of two seconds at the end of the simulation.The noise level was constant at -100 dBm.

Figure 6.6: Transmission rates for sta[3]

Statistics for sta[3] are presented in figure 6.7. This simulation seems to havebeen a good simulation as only 7% of the transmissions were unsuccessful.Average mode was high, 6.3618, and average throughput was 21.5854 Mbps,which is good. 99% of the unsuccessful transmissions were caused by biterrors.

20

30

40

50

60

Dat

a ra

te [M

bps]

Transmission rate

−101

−100.5

−100

−99.5

−99

Noi

se [d

Bm

]

Current noise level

0 5 10 15 20 25 30 3521

22

23

24

Offset fragment number

SN

R [d

B]

Last SNR detected

different stable rates for different lengths of the fragments


Statistics for sta[3] after a simulation with a constant noise level of -100 dBm.

Figure 6.7: Statistics for sta[3]

Simulation 4

The transmission rates for sta[3] are presented in figure 6.8. Most of thetransmissions were sent with a data rate of 24 Mbps. When too many unsuc-cessful transmissions at one data rate occured the adaptation algorithmchoosed a lower rate for subsequent transmissions of that fragment. Detailsabout the three transmissions within the square are shown in figure 6.10.

Unsuccessful: 7%

Successful: 93% Bit errors: 99%

Collisions: 1%

Average mode: 6.3618

1 8

Mod

e

Average mode

Average throughput: 21.5854 [Mbps]0 54

[Mbp

s]

Average throughput

Transmission results Unsuccessful transmissions


Transmission rates for sta[3] during a time interval of two seconds at the end of the simulation.The noise level was constant at -90 dBm. In this simulation sta[0] and sta[3] were hidden to

each other.


Statistics for sta[3] are presented in figure 6.9. 72% of the transmissions weresuccessful. 9% of the unsuccessful transmissions were due to collisions.Average mode was 4.81 and average throughput was 12.3032 Mbps.

Statistics for sta[3] after a simulation where sta[0] and sta[3] were hidden to each other. Thenoise level has been constant at -90 dBm.


5

10

15

20

25

Dat

a ra

te [M

bps]

−91

−90.5

−90

−89.5

−89N

oise

[dB

m]

Current noise level

0 5 10 15 20 25 30 35 40 45 5011

12

13

14


SN

R [d

B]

Last SNR detected

see transmission details below

Transmission rate

Unsuccessful: 28%

Successful: 72%Bit errors: 91%

Collisions: 9%

Average mode: 4.81

1 8

Mod

e

Average mode


[Mbp

s]

Average throughput



Figure 6.10 shows two different transmission situations that might occur.First there were two subsequent unsuccessful transmissions due to missingacknowledgement frames from ap[0]. The last transmission attempt for sta[3]wasn’t successful because sta[0] started transmitting a fragment before sta[3]had stopped transmitting.

Detailed transmission description for sta[3] of the three transmissions within the square infigure 6.8.

Figure 6.10: Transmissions for sta[3]

Simulation 7

The transmission rates for sta[3] are presented in figure 6.11. Here, the noiselevel was the same for some fragments before switching. The changing datarate for the first ten transmissions in figure 6.11 could be explained by differ-ent lengths of the fragments. Different thresholds were used for differentlengths.

0 500 1000 1500 2000 2500

ap[0]

sta[0]

sta[1]

sta[2]

sta[3]

sta[4]

Transmissions

Offset time [us]

Sta

tions

Original frameACK frameunsuccessful transmissions

due to missing ACK frames

unsuccessful transmission due to collision between sta[0] and sta[3] sta[0] and sta[3] are hidden nodes


Transmission rates for sta[3] during a time interval of two seconds at the end of the simulation.The noise level was switching slowly in this simulation.


Statistics for sta[3] are presented in figure 6.12. 43% of the transmissionswere unsuccessful and all of them were caused by bit errors. Average modewas high, 6.4778, and average throughput was 14.4183 Mbps.

Statistics for sta[3] after a simulation where the noise level was switching slowly.


0

20

40

60

Dat

a ra

te [M

bps]

Transmission rate

−100

−95

−90N

oise

[dB

m]

Current noise level

0 5 10 15 20 25 30 35 4010

15

20

25


SN

R [d

B]

Last SNR detected

Unsuccessful: 43%

Successful: 57%

Bit errors: 100%

Collisions: 0%

Average mode: 6.4778

1 8

Mod

e

Average mode


[Mbp

s]

Average throughput



In figure 6.13 the last 20 seconds of simulation time are shown.

Transmission rates for sta[3] during the last 20 seconds of simulation time. The noise level wasswitching slowly in this simulation.


Simulation 2-3 and 5-6

Table 6.7 presents an overview of some simulation results. The data rate col-umn represents the data rate chosen for most of the fragments during the endof the simulation. In simulation 6 the data rate varied a lot, due to a switchingnoise level. Thus, no data rate value is given for this simulation. Statisticsgiven in the four columns to the right correspond to the statistics figures.

0

20

40

60

Dat

a ra

te [M

bps]

Transmission rate

−100

−95

−90

−85

Noi

se [d

Bm

]

Current noise level

0 50 100 150 200 250 300 350 400 450 5005

10

15

20

25

SN

R [d

B]

Last SNR detected



Table 6.7. Simulation results for sta[3] and sta[5]

6.4 CONCLUSION

It is very clear that different levels of background noise affect the choice ofrate differently. Simulation 1 shows that most transmissions were successfuland almost none of the unsuccessful transmissions were due to collisions.The algorithm has adapted the data rates to the lengths of the fragments. Insimulation 2 a lower rate has been chosen, in general, than in simulation 1, inorder to adapt to the raised noise power level. When a high load is introducedin simulation 3 collisions are more likely to occur apparently. 32% of theunsuccessful transmissions were caused by collisions. The average mode isalmost the same as in simulation 2. This has resulted in less successful trans-missions. Actually, as the probability for bit errors increases for higher datarates, there are not many successful transmissions at these higher rates whenthe probability for collisions is high. It could therefore be worth trying atlower rates. In simulation 4 sta[0] and sta[3] were hidden to each other. It isobvious that the amount of collisions as a cause to unsuccessful transmissionshas increased, compared to the results in simulation 2. A greater number ofstations associated to ap[0] results in lower average throughput for each sta-tion, comparing simulation 5 with simulation 2. The fact that more transmis-sions in simulation 5 than in simulation 2 were successful has to do with thelow average mode chosen. In simulation 6 there was a more rapid change ofthe noise level than in simulation 7. Worse average throughput and less suc-cessful transmissions was the direct effect. Thus, the algorithm is better toadapt to slow changes of the noise level.

Simulation Datarate

[Mbps]

Successfultransmissions

[%]

Unsuccessfultransmissions

due to collisions[%]

Averagemode

Averagethroughput

[Mbps]

2 24 72 0 4.8619 12.2289

3 24 65 32 4.7478 2.0294

5 9 92 9 2.0881 5.5864

6 39 0 6.7943 11.6713


There are several ways of implementing link adaptation mechanisms in anIEEE 802.11a WLAN. This report aimed to demonstrate one way to imple-ment such a mechanism. By implementing a link adaptation algorithm in theWOK model and evaluate this it has been shown that link adaptation in theWOK model is possible.

The link adaptation algorithm itself shows best results when the probabilityfor collisions is low and when the noise level isn’t switching too rapidly.

6.5 COMMENTS

The primary task was not to focus on the link adaptation algorithm itself,rather to show that link adaptation in the WOK model is possible. It feltnecessary to achieve some information about how link adaptation may beintegrated on MAC level in IEEE 802.11a. A guess was to find this informa-tion along with a suitable algorithm. The process of finding a suitable algo-rithm did not show to be as straightforward as expected. Public material aboutlink adaptation algorithms is rare.

Integration in the WOK model of the algorithm found was performed rela-tively easy from its function. Most effort was instead put on the extension ofthe algorithm found, in order to achieve satisfactory results.

Possible improvements could be:

• to implement link adaptation when sending ACK frames.

• to implement dynamic fragmentation.

• to adjust the algorithm better, e.g. by estimating the likelihood for colli-sions.

• to handle generation of interference and frame errors in a more realisticway.

117

7FINAL COMMENTS

This report has described a MAC-level implementation of DFS proceduresbased on the framework provided by the IEEE 802.11h draft. An exampleDFS algorithm was designed and implemented in the WOK model. The algo-rithm was based on measurements during regular quiet periods, performed bya subset of nodes in the WLAN cell. Simulations showed that increased traf-fic load following quiet periods introduces a collision problem, decreasing theperformance of the WLAN cell. Further, due to limitations in the IEEE802.11h draft, quiet measurements showed not to be sufficient to detect radarsignals satisfactory. However, upon detection of a radar signal on the operat-ing channel, the algorithm is able to select a new radar-free channel with ahigh probability. Future improvements of DFS should focus on spontaneousmeasurements, in order to decrease the radar detection time.

The report has also described an implementation of link adaptation. A linkadaptation algorithm was implemented, simulated and evaluated on MAClevel in the WOK model. Evaluation of this algorithm was performed by run-ning the algorithm in different environments. The results demonstrated thatthe algorithm adapted the transmission rate differently depending on the envi-ronment. Best results were achieved when the probability for collisions waslow and when the noise level wasn’t switching too rapidly. Further develop-ment of the WOK model may focus on other aspects regarding link adapta-tion, e.g., dynamic fragmentation or frequency selectivity.

The WOK model was built based on the IEEE 802.11a standard. By perform-ing simulations using this model both link adaptation and DFS on MAC levelhave been explored. Thus, the main goals of this master thesis were reached.

118

REFERENCES

[1] IEEE Std. 802.11-1999, Part 11

[2] Javier del Prado Pavon, Sunghyun ChoiLink Adaptation Strategy for IEEE 802.11 WLAN via Received SignalStrength Measurement.

[3] Daji Qiao, Sunghyun ChoiGoodput Enhancement of IEEE 802.11a Wireless LAN via Link Adaptation

[4] Daji Qiao, Sunghyun Choi, Kang G. ShinGoodput Analysis and Link Adaptation for IEEE 802.11a Wireless LANs

[5] E. Pop, V. Croitorum, R. AntohiSite Engineering for Indoor Wireless Spread Spectrum Communications

[6] Jean-Pierre et. al., Telecommunication Networks Group, Berlin, June 2002Measurement and Simulation of the Energy Consumption of an WLAN Inter-face.

[7] IEEE 802.11a, Part 11

[8] http://www.omnetpp.org/OMNeT++ Community Site

[9] http://www.nwfusion.com/reviews/2002/0617bg1.html, Jim Geier802.11a becomes a contender

[10] Joe Bardwell, VP of Professional ServicesConverting Signal Strength Percentage to dBm Values

[11] Bob O’Hara, Al PetrickIEEE 802.11 Handbook - A Designer’s Companion

[12] IEEE 802.11h Draft Supplement, Part 11

[13] ETSI BRAN; 5 GHz high performance RLAN;Harmonized EN covering essential requirements of article 3.2 of the R&TTEDirective

[14] www.hpl.hp.com, Jean TourrilhesPacket Frame Grouping: Improving IP multimedia performance over CSMA/CA

[15] A. Alexiou and others, Information Society TechnologiesFITNESS - D4.1 System-Level Simulation Methodology Defined

References 119

[16] Göte Andersson, Elektroniktidningen nr 11, 2003WLAN får mer utrymme i både USA och EU

[17] Mikael Hjelm, Infineon Technologies Wireless Solutions AB

[18] ITU, Document 8A-9B/89-EWorking Document Towards a Preliminary Draft New Recommendation onDynamic Frequency Selection in 5 GHz RLANs

[19] Anders Ranheim, Ericsson ERVAn Alternative Radar Detection Scheme for WLAN

[20] F. Johansson, A. Ranheim, Ericsson ERVDFS Functionality

[21] www.mobilian.com2.4 GHz and 5 GHz WLAN: Competing or Complementary?

[22] Magnus Janson, Magnus KarlssonAppendix

[23] Peterson, L.L. and Davie, B.S.Computer Networks, A System Approach, Morgan Kaufmann Publishers,Inc., 1996


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