A Cross Layer Scheduling and Resource Allocation Algorithm for OFDMA Wireless Networks

8/7/2019 A Cross Layer Scheduling and Resource Allocation Algorithm for OFDMA Wireless Networks

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IEEE 802.16

(UGS)(rtPS)(nrtPS)

(BE)

(MAC layer)

(frame)


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A Cross Layer Scheduling and Resource Allocation

Algorithm for OFDMA Wireless Networks

Advisor: Dr. Yung-Fang Chen Student: Iao-Tin Lin

Abstract

As multimedia communications develop rapidly in the recent years,

in order to maximize the capacity of wireless networks, scheduling plays

an important role in supplying quality of service (QoS) requirements to

broadband wireless communications. The IEEE 802.16 standard provides

four different scheduling services: Unsolicited Grant Service (UGS),

real-time Polling Service (rtPS), non-real-time Polling Service (nrtPS),

and Best Effort (BE). In this paper, we formulate the optimal problem by

maximizing the average utility function of all active users and then

propose a cross-layer algorithm to achieve the higher throughput by

allocating resources dynamically. Our scheme is aimed at designing

jointly dynamical subchannel assignment (DSA)and capacity planning

(CP) solutions. The simulation focuses on IEEE 802.16 wireless systems

working in Orthogonal Frequency Division Multiple Accesses (OFDMA)

and Point-to-Multipoint (PMP) mode, with one single cell serving many

Mobile Stations (MSs) in downlink transmission. Finally, the numerical

result shows that the cross-layer algorithm approaches a higher

throughput and improves extremely the performance of BE and nrtPS

services while supporting the quality of rtPS services at acceptable levels.


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/


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IV

Contents

..................................................................................................... IAbstract.................................................................................................... II

..........................................................................................................III Contents .................................................................................................. IV

List of Figures.........................................................................................VI

List of Table...........................................................................................VII

Chapter 1 Introduction.............................................................................1

Chapter 2 System Model ..........................................................................5

2.1 Traffic Models for QOS Architecture at the MAC layer ..............5

2.2 Wireless Networks configuration................................................11

2.2.1 Subcarrier allocations in Wimax OFDMA ........................11

2.2.2 Two-dimensional subchannel-mapping structure ..............20

2.2.3 Specifications of the entire system ....................................21

Chapter 3 .................................................................................................22

Cross-Layer Resource Allocation Algorithm .......................................22

3.1 Concepts of the present priority algorithm .................................22

3.2 Best Channel First (BCF) scheduling algorithm with Best

Channel First (BCF) subchannel allocation policy......................24

3.3 Proportional Fair (PF) scheduling algorithm with Best Channel

First (BCF) subchannel allocation policy....................................29

3.4 Priority function (PRF) for scheduling algorithm with Best

Channel First (BCF) subchannel allocation.................................32

3.5 Modified capacity priority algorithm..........................................37

3.6 Subchannel allocation algorithm for OFDMA systems..............44

3.6.1 Problem formulation ..........................................................44


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Chapter 4 Simulation Results ................................................................48

4.1 Simulation models for multi-user OFDMA................................48

4.1.1 Parameters of MSs Generation Model...............................48

4.1.2 Channel Models of IEEE 802.16 OFDMA systems..........48

4.1.3 AMC Design at the PHY....................................................50

4.1.4 Physical Layer parameters .................................................52

4.1.5 Transmission Power ...........................................................52

4.2 Simulation results for multi-user OFDMA ...............................54

Chapter 5 Conclusions............................................................................62

Reference..................................................................................................64


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VI

List of FiguresFigure 2.1 near Real-Time Video Traffic Model. ......................................6

Figure 2-2 Non Real-Time FTP Traffic Model ..........................................8

Figure 2.3 Best Effort HTTP Traffic Model. ..............................................9

Figure 2.4 Cluster Structure for Downlink PUSC. ...................................16

Figure 2.5 Downlink Frame Structure in IEEE 802.16............................20

Figure 3.1 Flowchart of Best Channel First (BCF) scheduling algorithm

with Best Channel First (BCF) subchannel allocation policy 28

Figure 3.2 Proportional Fair (PF) scheduling algorithm with Best Channel

First (BCF) subchannel allocation policy...............................31

Figure 3.3 Priority Function (PRF) scheduling algorithm with Best

Channel First (BCF) subchannel allocation policy ................36

Figure 3.4 A Brief Topology of Our Cross Layer System........................37

Figure 4.1 Total Throughput of The System versus Total Number of

Mobiles ...................................................................................54

Figure 4.3 Average Transmission Rate to Minimum Data Rate Ratio for

Video Streaming versus Total Number of Mobiles. ...............57

Figure 4.4 Empty Ratio for Video Streaming versus Total Number of

Mobiles. ..................................................................................58

Figure 4.5 Average Data Rate of FTP Service versus Total Number of

Mobiles. ..................................................................................59

Figure 4.6 Average Transmission Rate per Mobile per Sec of FTP Service

versus Total Number of Mobiles. ...........................................60

Figure 4.7 Average Data Rate of HTTP Service versus Total Number of

Mobiles. ..................................................................................61


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VII

List of TableTable 2-1 near Real-Time Video Traffic Model Parameters.......................7

Table 2-2 FTP Characteristics.....................................................................8

Table 2-3 HTTP Traffic Model Characteristics ........................................10

Table 2-4 2048-FFT OFDMA Downlink Carrier Allocations- PUSC......12

Table 2-5 1024-FFT OFDMA Downlink Carrier Allocations- PUSC......13

Table 2-6 512-FFT OFDMA Downlink Carrier Allocations- PUSC........14

Table 2-7 128-FFT OFDMA Downlink Carrier Allocations- PUSC........15

Table 2-8 MCS Modes in The IEEE 802.16 Standard..............................21

Table 4.1 SUI 2 Channel Model Parameters ............................................49

Table 4.2 Required SNR for Different Modulations ................................51

Table 4.3 Physical Layer Parameters........................................................52


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Chapter 1 Introduction

In the recent years, the number of users who are familiar with

accesses to high-quality and high-data-rate multimedia applications, such

as peer-to-peer applications, internet accesses, IP telephony, and video

conferences, grows rapidly all over the world. Some solutions are

proposed to improve the performance of high-speed communication with

distinct Quality of Service (QoS) requirements in Broadband Wireless

Access (BWA) systems. The IEEE Project 802 working group 16, also

referred to as IEEE 802.16, is developing standard for fixed [1] and

mobile [2] BWA systems, which assume OFDM-based technology to be

the radio interface basis. However, the IEEE 802.16 standard formulates

a set of specifications for different classes of QOS architectures, but

reserves scheduling and connection admission control (CAC) strategies

for developers. Although many wire-line scheduling algorithms are

obtainable already from the published articles, the mechanisms could not

be really applied to wireless networks. In wireless networks, channel

quality affected by multipath fading and Doppler spreads is time varying.

If the wireless channel of a connection meets serious fading, it is wasteful

to assign any bandwidth to the connection; in wireline networks, the

designers only care about traffic services and queuing conditions. In [3],

there was an overview of the fundamental definitions and classifications

for scheduling techniques and we can find the differences between

wireless and wireline scheduling mechanisms. In [17], the article has

presented some important resource-allocation problems and then

described the proposed solutions for IEEE 802.16 wireless networks.


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OFDM techniques divide the total transmit channel into many

orthogonal subchannels, which are composed of subcarriers. The

resources of OFDM systems are displayed by two-dimensional matrix,

where the dimensions are subchannels and OFDM symbols in the time

domain, respectively. The OFDMA system in the IEEE 802.16 defines

three subcarrier allocation schemes, which are named FUSC, PUSC, and

AMC modes, individually. The subcarrier allocation schemes specify

how to distribute the subcarriers for a certain subchannel in OFDMA

symbols. Among the allocation schemes, the number of data subcarriers

grouped into a subchannel is identical, but the subcarriers are distributed

in totally different way according to different allocation algorithms. More

details of FUSC and PUSC modes are shown in [1-2]. Furthermore, those

subchannels can be allocated to different users in non-overlapping

manners in order to provide a flexible multiuser access scheme and

exploit multiuser diversity. In [4], the author provided several

two-dimensional mapping approaches implementing the OFDMA mode

of the IEEE 802.16 standard. In this thesis, we use PUSC mode to

perform our subcarrier allocation strategy. A tradeoff between fairness

and efficiency needs to be considered in wireless communications. A fair

system may decrease total throughput and bandwidth efficiency because

of some users with serious propagation loss or bad fading channel

conditions. However, an efficient system may only consider the users

with good channel conditions. Finding the balance between fair and

efficient resource allocations is a very crucial work for wireless

systems/networks. In [5] and [6], the authors have provided a theoretical

framework for cross-layer optimization for OFDM wireless systems.


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They have proved that OFDM networks/systems with dynamic subcarrier

assignment (DSA) and adaptive power allocation (APA) can significantly

improve the performance. And then they have focused on an effective and

practical algorithm for efficient and fair resource allocation depending on

the theoretical framework established in [5]. However, in these studies,

they didnt include different classes of QoS services in their simulations.

All the services in wireless networks are managed at the medium

access control (MAC) layer. We can review the detail of the MAC

mechanisms defined by IEEE 802.16 standard in [7-8]. In [8], multimedia

applications have been simulated by following the IEEE 802.16 MAC

protocol and the authors have discussed the trade off between average

delay and throughput with respect to frame durations size in duplex

transmission. The IEEE 802.16 standard provides four different

scheduling services: Unsolicited Grant Service (UGS), real-time Polling

Service (rtPS), non-real-time Polling Service (nrtPS), and Best Effort

(BE). In [9], the scheduler assigned strict priority from high to low in the

order of rtPS, nrtPS, and BE, and guaranteed QOS requirements for high

rate multimedia data in OFDM systems. On the other hand, conditionally

high priority scheduling and cross-layer simulations have been

investigated in [10] and [11], respectively. They have proposed that the

performance of non-strict requirement scheduling services, e.g. BE and

nrtPS services, is obviously improved by giving conditional high priority

to strict requirement scheduling service, e.g. the rtPS service.

In [10], the authors have proposed a packet scheduler and a CAC

algorithm and shown that the scheduler and the CAC scheme would

greatly improve the performance of BE and nrtPS services while


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maintaining the quality of video service at an acceptable level in OFDMA

systems. In [11], the authors have developed a low complexity cross-layer

scheduling algorithm at the MAC layer for multiple connections. The

scheduler assigned a priority of each connection depending on its channel

quality in an OFDM system. However, the dynamic subcarrier

assignment and adaptive power allocation schemes have not been

proposed in these studies.

In this thesis, we propose a cross-layer-based scheduler at the MAC

layer with diverse QoS requirements for multiple connections, where

each connection employs a near optimal subchannel allocation at the

physical layer (PHY). We compute a priority for each connection and

update it dynamically depending on channel quality and QoS-service

satisfaction. Furthermore, we offer a resource allocation unit (RAU)

mapping algorithm to allocate the resource more efficiently and fairly in

OFDMA systems. In Chapter 2, we describe the system model under our

consideration and specify the characteristics of the four QoS services. In

Chapter 3, we investigate a proposed cross-layer algorithm, for

scheduling blocks and 2D mapping blocks, respectively. In Chapter 4, we

describe the simulation environment and parameter values of the system

model and present the performance of the developed algorithm compared

with the other algorithms specified in chapter 3. Finally, Chapter 5

concludes this thesis.


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Chapter 2 System Model

2.1 Traffic Models for QOS Architecture at theMAC layer

The IEEE 802.16 standard defines four difference-scheduling services

to meet the QoS requirements of multimedia applications according to

packet arrival patterns (e.g., fixed/variable size of a data packet or

periodic/aperiodic packet time interval) and QoS service requirements

(e.g., applications with maximum delay requirements or minimum

guaranteed bandwidth). In the following, we describe each scheduling

service supporting a specific class of multimedia applications. In this

thesis, we use the traffic models defined in [12] and [13] and only

simulate the rtPS, nrtPS, and BE services in our system.

Unsolicited Grant Service (UGS):

UGS generates fixed-size data packets at periodic intervals to

support real-time applications with fixed throughput, strict latency, and

tolerated jitter. The UGS services apply to T1/E1 and voice over IP (VoIP)

without silence suppression. A UGS connection never requests bandwidth

to the base station. Therefore, the BS computes the minimum amount of

data transported for the UGS connection to satisfy its requirement at the

setup duration. In this thesis, we do not simulate the conditions of UGS

connections.

Real-Time polling service (rtPS):

Real-Time polling service (rtPS) generates variable-size data packets


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at periodic intervals to provide real-time applications with less strictness

on delay than UGS, such as VoIP with silence suppression and Moving

Picture Expert Group (MPEG) video conferencing. The maximum

latency (i.e. bounded waiting time for a packet at the MAC layer) and the

minimum traffic data rates are the key QoS requirements for the rtPS

service. Because of the variable size of packets, rtPS connections need to

report their current bandwidth requirement to the BS. A packet of the

rtPS connection will be dropped when exceeding the maximum delay.

Traffic Model of rtPS service for video streaming:

Figure 2.1 near Real-Time Video Traffic Model.

A video streaming session is defined as the entire video simulation

time. The session time is divided into buffering windows, which have a

regular interval T and are composed of a fixed number of packets. A

buffering window consists of eight packets with variable sizes and arrives

at the base station every 100 ms. The size of packet is distributed as

truncated Pareto with a mean of 50 bytes and a maximum of 125 bytes. In

our simulation, we follow the parameters in [10] to set the packet size

with a mean of 500 bytes and a maximum of 1400 bytes, which has video

data rate of 300 kb/s. Packet coding delay is the inter-arrival time

between two packets in a buffering window. The distribution of the


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packet coding delay is determined as a mean of 6 ms and a maximum of

12.5 ms according to truncated Pareto.

Table 2-1 near Real-Time Video Traffic Model ParametersInformation

types

Packet size Interval time between two

packets in a frame

Distribution Truncated Pareto

(mean= 500 B,

Max=1400B)

Truncated Pareto

(mean= 6ms, Max=12.5 ms)

Distribution

parameters

Note: Subtract k from the

generated r.v. to get

packet size (bytes)

Note: Subtract k from the

generated r.v. to get Interval

time (ms)

Number of packets per buffering widows: 8

Buffing window size: 100 ms

Nonreal-time polling service (nrtPS):

Nonreal-time polling service (nrtPS) guarantees a minimum traffic

rate and has no delay requirement. The nrtPS connections are suitable for

time-insensitive and bandwidth-intensive applications, such as File

Transfer Protocol (FTP).

Traffic Model of nrtPS service for File Transfer Protocol (FTP):

,1

,

1 .2 , 20, 1420

k k x mfxx

kx mfx

m

k m

=


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Figure 2-2 Non Real-Time FTP Traffic Model

In FTP applications, a session time alternates between a file

transmission and the reading time. The distribution of one FTP file size is

according to a lognormal distribution, which is given as a mean of 2 M

bytes and a maximum of 5 M bytes. On the other hand, the reading time,

i.e. the time interval between two download files, is an exponential

distribution with a mean of 60s. Every file is divided into fixed sizes of

packets, with 76% using 1500 bytes and 24% using 576 bytes.

Table 2-2 FTP CharacteristicsComponent Distribution Parameters pdf

File size Truncated

lognormal

Mean= 2 MB

Maximum= 5

MB

Reading

time

Exponential Mean=60 sex

Note for truncated lognormal:

A r.v. generated according to the truncated pdf will be discarded and another

one is regenerated when the r.v. is outside the availd interval.

Reading

timePackets of file1 Packets of file2 Packets of file3

Reading

time

Packet calls

time

2

1 (ln )exp[ ], 0

22

0.35, 14.45

x

xf x

x

=

= =

, 00.017

x

xf e x

= =


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Best Effort Service (BE):

Best Effort service (BE), which is used for electrical mail (E-mail)

and Hypertext Transport Protocol (HTTP), does not guarantee any delay

or throughput. Typically, the BE connections can not use the bandwidth

of the system until the connections supported by the above three services

are allocated.

Traffic Model of BE service for HTTP:

Figure 2.3 Best Effort HTTP Traffic Model.

The session of BE service alternates between packet-download time

and reading time. In Figure 2-3, the packet downloads are defined as a

packet call which consists of a main object and Nd embedded objects. At

beginning, a web-browser sends a main object containing the initial

HTML page, and then parses the HTML page for additional embedded

files such as graphs or buttons. Both main and embedded objects are

distributed as truncated lognormal with different means of 10710 and

7758 bytes, and the same maximum values of 2 MB. The number of

embedded objects per packet call (per page) is determined as a truncated

Pareto with a mean of 5.64 and a maximum of 53. A parsing time

between main and embedded objects is exponential distribution with a

mean of 0.13 sec. Finally, the reading time alternates between two packet

A session time

time

A packet call A packet call A packet call

Reading timeReading

timeMain object

embedded objects

Nd

Parsing time

Time interval between

main and embedded

objects


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calls distributed as exponential distribution with a mean of 30 sec.

Table 2-3 HTTP Traffic Model CharacteristicsComponent Distribution Parameter pdf

Main object Mean=10710

bytes

Std. dev=25032

Min.=100 bytes

Max.=2 M bytes

Embedded

objects

Truncated

Lognormal Mean=7758 bytes

Std dev=126168

Min.=50bytes

Max.=2 M bytes

Number of

embedded

object per

call

Truncated

Pareto

Mean= 5.64

Max.=53

Parsing time Mean=0.13 sec

Reading time

Exponential

Mean=30 sec

69.7

0,

=

= xex

fx

55,2,1.1

,

,

1

===

=

=


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2.2 Wireless Networks configuration

2.2.1 Subcarrier allocations in Wimax OFDMA

There are FFTN subcarriers allocated in one OFDMA symbol, which

consists two sets of subcarrier blocks, guard tones and used

subcarriers usedN . The standards define three different types of subcarrier

allocations, which are named Fully Usage of Subchannel (FUSC),

Partially Usage of Subchannel (PUSC), and AMC to distribute the used

subcarriers. Among the three subcarrier-allocation schemes, FUSC and

PUSC are kinds of distributed subcarrier permutations, and AMC is a

kind of adjacent subcarrier permutation. The number of OFDMA symbols

that the subcarriers within one subchannel are distributed over is different

between uplink and downlink transmissions. For downlink, we can select

any one of the three subcarrier allocations to generate subchannels. In the

FUSC and AMC mode, the algorithm distributes the subcarriers

belonging to the same subchannel over one OFDM symbol but over two

OFDM symbols in the PUSC mode. On the other hand, for uplink, it is

only one subcarrier permutation, i.e. PUSC mode, whose subchannels

consisting of subcarriers distributed over three OFDMA symbols.

Because the downlink loads in OFDMA wireless networks are

exactly higher than the uplink ones, we focus on the downlink

transmission. But, our scheme can be used to the uplink as well. In this

thesis, we consider the downlink PUSC mode of a single cell, which

consists of multiple mobile stations (MSs) connecting to a base station

(BS) or relay station. Because we use the PUSC subcarrier permutation,

we only develop the algorithm of PUSC permutation in IEEE 802.16e

OFDMA mode and leave the other permutation schemes aside in this


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thesis.

Symbol structure for Downlink PUSC:In the downlink PUSC, the standard defines four FFT sizes, FFTN i.e.

2048-FFT, 1024-FFT, 512-FFT and 128-FFT, which is specified in the

following tables.

Table 2-4 2048-FFT OFDMA Downlink Carrier Allocations- PUSCParameter Values Comments

Number of DC subcarriers 1 Index 1024

Number of Guard subcarriers, left 184 -

Number of Guard subcarriers, right 183 -

Number of Used Subcarriers (Nused)

including all possible allocated pilots

and the DC subcarrier

1681Number of all

subcarriers

usedwithin a

symbol.

renumbering sequence 6, 108, 37, 81, 31, 100,

42, 116, 32, 107, 30, 93,

54, 78,10, 75, 50, 111,

58, 106, 23, 105, 16,

117, 39, 95, 7,115, 25,

119, 53, 71, 22, 98, 28,

79, 17, 63, 27, 72,

29,86, 5, 101, 49, 104,9, 68, 1, 73, 36, 74, 43,

62, 20, 84, 52, 64, 34,

60, 66, 48, 97, 21, 91,

40, 102, 56, 92, 47,90,

33, 114, 18, 70, 15, 110,

51, 118, 46, 83, 45, 76,

57,99, 35, 67, 55, 85,

59, 113, 11, 82, 38, 88,19, 77, 3, 87,12, 89, 26,

Used to

renumber

clusters before

allocation to

subchannels.


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65, 41, 109, 44, 69, 8,

61, 13, 96, 14, 103,

2,80, 24, 112, 4, 94, 0

Number of carriers per cluster 14 -Number of clusters 120 -

Number of data subcarriers in each

symbol

per subchannel

24 -

Number of subchannels 60 -

PermutationBase12

(for 12 subchannels)

6,9,4,8,10,11,5,2,7,3,1,0

-

PermutationBase8(for 8 subchannels)

7,4,0,2,1,5,3,6 -








841Number of all

subcarriers

usedwithin a

symbol.

renumbering sequence 6, 48, 37, 21, 31, 40,

42, 56, 32, 47, 30, 33,54, 18,10, 15, 50, 51,

58, 46, 23, 45, 16, 57,

39, 35, 7, 55,25, 59, 53,

11, 22, 38, 28, 19, 17,

3, 27, 12, 29, 26,5, 41,

49, 44, 9, 8, 1, 13, 36,

14, 43, 2, 20, 24, 52,4,

34, 0

Used to

renumberclusters before

allocation to

subchannels.


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Number of carriers per cluster 14 -

Number of clusters 60 -


symbol per subchannel

24 -


PermutationBase6 (for 6

subchannels)

3,2,0,4,5,1 -

PermutationBase4 (for 4

subchannels)

3,0,2,1 -

Table 2-6 512-FFT OFDMA Downlink Carrier Allocations- PUSC

Parameter Values Comments







421Number of all

subcarriers

usedwithin a

symbol.

renumbering sequence12, 13, 26, 9, 5, 15, 21,

6, 28, 4, 2, 7, 10, 18,

29,17, 16, 3, 20, 24, 14,

8, 23, 1, 25, 27, 22, 19,

11, 0

Used to

renumber

clusters before

allocation to

subchannels.




symbol

per subchannel

24 -


PermutationBase54,2,3,1,0

-


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(For 5 subchannels)








85Number of all

subcarriers

usedwithin a

symbol.

renumbering sequence2, 3, 1, 5, 0, 4

Used to

renumber

clusters before

allocation to

subchannels.




symbol

per subchannel

24 -


Downlink PUSC subcarrier-allocation algorithm:Each of the four-downlink PUSC permutations has the same number

of data subcarriers in one subchannel, which is equal to 48.

We specify the downlink PUSC subcarrier-allocation algorithm step by

step as the following:


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Step 1: Dividing the subcarriers into physical clusters

First, we define a cluster structure as Figure 2.4:

According to the cluster structure and the symbol indexes, we divide the

used subcarriers into physical clusters. The number of clusters, ClustersN , in

an OFDM symbol varies with the FFT sizes. Every 14 consecutive used

subcarriers are separated into a cluster and a physical index is given to the

cluster.

Figure 2.4 Cluster Structure for Downlink PUSC.

Step 2: renumbering the physical clusters into logical clusters

After assigning a physical number to each cluster, we renumber the

physical indexes of clusters into logical cluster indexes by:

Logical index= renumbering sequence ((physical index +13*IDcell)

mod ClustersN ),

where IDcell is the base station index.

Step 3: dividing the clusters into groups

All FFT-size allocation algorithms divide the clusters into six groups,

but the size of each group varies with the FFT sizes. We specify the

group sizes versus FFT sizes as following:

even symbols

odd symbols

data subcarrier

pilot subcarrier


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For 2048-FFT size:

Group0: cluster 0-23, Group1: cluster 24-39, Group2: cluster 40-63,

Group3:cluster6 4-79, Group4 cluster 80-103 and Group5: cluster

104-119

For 1024-FFT size:

Group0: cluster 0-11, Group1: cluster 12-19, Group2: cluster 20-31,

Group3: cluster 32-49, Group4 cluster 40-51 and Group5: cluster 52-59

For 512-FFT size:

Group0: cluster 0-9, Group1: null, Group2: cluster 10-19,

Group3: null, Group4 cluster 20-29 and Group5: null

For 128-FFT size:

Group0: cluster 0-1, Group1: null, Group2: cluster 2-3,

Group3: null, Group4 cluster 4-5 and Group5: null

Step 4: Allocating subcarriers to subchannel

In PUSC subcarrier allocation, pilot subcarriers within each cluster are

firstly allocated into OFDMA symbols and then the remaining data

subcarriers within those symbols are allocated group by group as

following procedure:

( , ) { [ mod ] }modsubchannel s subchannel subchannelSubcarrier s N n P n N IDcell N = + + (2.1)

where

( , )Subcarrier s is the permutated subcarrier index of the present group

corresponding subcarrierin subchannel s, where is


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running index 024 and s is running index0 TSN,

where TSN is the total subchannels in one OFDMA

symbol.

subchannelN

is the number of subchannels in each group,

subcarrierN is the number of subcarriers for one subchannel

allocating in one OFDMA symbol, i.e. 24subcarrierN = ,

IDcell is identifies of the particular BS segment,

[ ]s

P j means the jth

element obtained by rotating {Permutation-

Base} cyclically to the left s times,

n is defined as ( 13 ) mod subcarriern s N = +

For 2048-FFT size:

From Table 2-4, the algorithm uses (2.1) to partition 24 data subcarriers

into each subchannel per OFDMA symbol with PermutationBase12, i.e.

subchannelN =12, for even numbered major groups, and PermutationBase8, i.e.

subchannelN =8, for odd numbered major groups.

For 1024-FFT size:


into each subchannel per OFDMA symbol with PermutationBase6, i.e.

subchannelN =6, for even numbered major groups, and PermutationBase4, i.e.

subchannelN =4, for odd numbered major groups.

For 512-FFT size:


into each subchannel per OFDMA symbol only with PermutationBase5,


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i.e. subchannelN =5, for even numbered major groups.

For 128-FFT size:


into each subchannel of each OFDMA symbol.

For example:

We set the parameters of subchannel as IDcell=2, FFT size=1024,

3S = subchannel index belongs Group0, 6subchannelN = , 24subcarrierN = .

We permute the subcarriers of 3-th subchannel over one OFDM symbol

by:

( , ) { [ mod ] }mod , {0,1,.., 1}subchannel s subchannel subchannel subcarrier Subcarrier s N n P n N IDcell N N = + +

Take subcarrier (0, 3) for example:

Thus, the subcarrier index 0 of the 3-th subchannel would be mapping

into the 96-th data subcarrier index in Group0.

The details of the other subcarrier allocation algorithms are specified

in IEEE 802.16 standards, and omitted here.

3

3

(0,3) 6 { [ mod 6] }mod6

6 [((0 13*3)mod24)] { [((0 13*3)mod24)mod6] 2}mod6

6 15 { [3] 2}mod690 {40 2}mod6

90 6 96

sSubcarrier n P n IDcell

P

P

= + +

= + + + +

= + += + +

= + =


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2.2.2 Two-dimensional subchannel-mapping structure

Figure 2.5 Downlink Frame Structure in IEEE 802.16

Following the PUSC subcarrier allocation in the IEEE 802.16

standard, we employ a forward error control (FEC) block as a basic unit

for resource allocations. One FEC block (i.e. one subchannel in

OFDMA-based system) consisted of the subcarriers over two consecutive

OFDMA symbols. We define the number of several consecutive FEC

blocks as a resource allocation unit (RAU). In this thesis, an RAU is set

to be the size of one-subchannel. The example of a downlink IEEE

802.16 frame structure is shown in Figure 2.5. Furthermore, we use

PUSC allocation with the sizes of 1024-FFT in the simulation. Every two

OFDMA symbols have 30 subchannels with 48 data subcarriers in each

subchannel for a downlink transmission mode in Wimax systems. A

frame structure is grouped into several data bursts that are composed of

consecutive RAUs in the frequency domain and FEC blocks in the time

domain. The data burst is built in the form of rectangularity with one type

of modulation and coding mode and assigned to only one user.

Preamble

OFDMA

symbol

time

FEC

Block

frequency

Downlink Frame

Subchannel 1

Subchannel 2

Subchannel

Ns

Subchannel 3

Subchannel 4

k k+1 k+2 k+3 k+4 k+5 k+6 k+7 k+8 k+9

Data Burst

time

FCH

DL

MAP

UL

MAP

RAU

RAU with 3 FEC blocks


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2.2.3 Specifications of the entire system

In this thesis, each MS can support one connection for convenience,

and each connection only belongs to one type of the three typical Internet

services. All connections communicated with the base station use the

time-division duplex (TDD) mode in the system. The performance of the

IEEE 802.16 wireless system is assessed in Point-to-Multipoint (PMP)

mode. We apply a buffer for each connection, which is connected with

the BS to request bandwidth, and operate a first-input-first-output (FIFO)

mode to transmit packets. In the time domain, the transmission time is

divided by a frame time consisting of fixed OFDMA symbols.

Adaptive modulation and coding (AMC) scheme, with a pair of one

specific error-correcting coding and one modulation, is available for each

subchannel in the frame duration under the above framework. We assume

six modulation and coding schemes (MCS) with M-ary quadrate

amplitude modulation (MQAM) and convolutional codes (CC) in Table

2-8. The channel quality of each MS can be either reported from MS or

estimated by BS itself. Suppose that the base station knows the channel

gains of all users subcarriers. When the algorithm is performed, the BS

selects an appropriate MCS for each data burst.

Table 2-8 MCS Modes in The IEEE 802.16 StandardMCS mode 1 2 3 4 5 6

Modulation QPSK QPSK 16QAM 16QAM 64QAM 64QAM

CC coding rate 1/2 2/3 1/2 3/4 2/3 3/4

FEC Block

size(bits)

96 144 192 288 384 432

Rn (bits/symbol) 1.0 1.5 2.0 3.0 4.0 4.5


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Chapter 3Cross-Layer Resource Allocation Algorithm

3.1 Concepts of the present priority algorithm

For the cross-layer resource allocation algorithm design, we only care

about three viewpoints, which are, maximum total throughput, fair

transmission among users, and satisfaction with the QoS requirements of

each user. However, its difficult to achieve all benefits in the

above-mentioned viewpoints. For example, suppose that one user with

bad fading channel quality asks for strict QoS requirement. If the base

station chooses the user to be transmitted, the total performance of the

system will degrade seriously; if the base ignores the users request, the

unfair transmission will occurs. In the following section, we will

introduce three scheduling algorithms, which have been proposed in the

recent years, and we illustrate the pros and cons of each algorithm. We

use the three different scheduling algorithms to be compared with our

proposed mechanism in this thesis.

The best channel first (BCF) scheduling with best channel first (BCF)

allocation algorithm, which is specified in section 3.2. This scheme

selects those unassigned RAUs with the best average received SNR to

one user. The algorithm may have an advantage of better total throughput,

but may not satisfy the QoS requirement of each connection on the

contrary. This algorithm is proposed in [10].

The second algorithm is the proportional fair (PF) scheduling with the

best channel first (BCF) allocation algorithm. This PF algorithm has been

designed to achieve equal average data rate between users. Because this


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scheme only cares about impartial transmissions, it may cause low total

throughput and un-satisfaction with QoS requirements. The detail

algorithm is specified in section 3.3.

The third cross-layer scheduling algorithm is first proposed in [11].

The authors have designed a low complexity priority function to assign

the priority to each connection. In the algorithm, they have considered

about the QoS requirements with each mobiles channel quality to figure

out a priority factor for each user. The method can look after both side of

performance and diverse QoS requirements. The more detail description

of the method is in section 3.4.


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3.2 Best Channel First (BCF) scheduling

algorithm with Best Channel First (BCF)

subchannel allocation policy

I. Estimate of Data Volume in Video Buffer

The video packets have the strictest requirement in time latency

and minimum data rate. We consider received video packets are stored in

a video buffer at each video mobile. Delay will occur when the data in the

buffer is empty. Therefore, the base needs to estimate the remaining

video data at each buffer to avoid delay conditions. The scheduling

algorithm is published in [10].

First, the authors have defined ( )iB t to be the remaining data (in bits)

in the video buffer of thethi mobile at time frame t. The value of ( )iB t

will be updated before they perform the scheduling algorithm at each

frame time by:

( ) max{ ( 1) ( 1) ,0}rtpSi i i i f B t B t D t R T = + i (3.1)

where rtpSi

R is the video playback rate of connection i, which the video

mobile informs the base at the initial connection setup time. The traffic

data, ( 1)iD t , is the data that are successfully transmitted to the mobile i at

frame time t-1. Each frame time duration is denoted by fT.

II. Transmission Priority of Traffic

Transitionally, most schedulers would give highest priority to rtPS

service, which is ahead of nrtPS, and BE services. However, the authors

brought up a new concept that the rtPS packets are treated as the same

priority level as nrtPS and BE services until the deadline condition of


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rtPS service is achieved.

The priority mechanism has only two priority levels, that is, high and

low. The nrtPS and BE services are always set in low priority level; On

the other hand, the rtPS packets have low priority in default , and become

high priority level when the video buffers belonging to users are going to

be empty.

For any mobile i, the authors set two levels of threshold values to

decide which priority level of the mobile is and how many packets will be

transmitted for this mobile. First, the two threshold levels have been

denoted 1THQ and 2THQ (for this thesis, we set 1 0.1THQ = and 2 0.05THQ = ).

At each frame, the base decides the priorities for those video mobiles

according to the following three conditions:

(1) (3.2)

The priority of all video packets for mobile i remains low.

Let ( )i

M tbe data in bits that will be transmitted to the mobile i at the

present frame and set default value of ( )i

M t to be the size of one packet.

We define one packet containing 576 bytes for convenience.

(2)

The base gives high priority with the first one packet to the mobile i.

Thus, we can define ( ) 576*8iM t= (in bits).

(3)

1 2

( )iTH TH rtPS

i f

B t

Q QR T >i

2

( )iTH rtPS

i f

B tQ

R T

i

1

( )i

THrtPS

i f

B tQ

R T

>i


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* arg max{ ( )}ii

i SNR t =

The base station gives high priority for the first two packets to the video

mobile i. At the same way, we assign ( ) 576*8*2i

M t= (in bits).

Every packet, which is given high priority, will be mapped as the

amount of resource allocation units (RAUs). In this thesis, one RAU

represents one PUSC subchannel in Wimax OFDMA network. We define

FNto be the total number of RAUs within a frame structure. ( )

iR tis the

number of RAUs that are assigned to high-priority packets of mobile i at

frame time t.

III. Best Channel first subchannel allocation

After the base has separated packets in transmission queues for all

mobiles into two groups, i.e. low-priority and high-priority levels, the

scheduler allocates the RAUs depending on the downlink channel quality

of each mobile and performs the resource allocation from the

high-priority group to the low-priority group in order.

If there are still some available RAUs after allocating for high-priority

packets, the allocation mechanism will distribute the available RAUs to

low-priority packets until all of the RAUs in a frame are all assigned.

Performing by iterations in each group, the base choose one mobile i*

with the best average SNR of unsigned subchannels over frame t, that is:

(3.5)

where ( )iSNR trepresents the average SNR of the total available

subchannels over frame t.

After choosing a mobile i* to be transmitted at the MAC, the base


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continues allocating RAU one by one for mobile *i until the

transmission data at the present frame duration is larger than * ( )i

M t.

The allocation algorithm chooses the best average-SNR from the

available RAUs for mobile i* as:

(3.6)

where

is the index of RAU

* ( , )iSNR t is the average SNR value of theth

RAU at frame t for

mobile i*.

The system operation of the BCF scheduling with BCF allocation

scheme is illustrated in Figure 3.1.

*

*arg max{ ( , )}

ik SNR t

=


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Figure 3.1 Flowchart of Best Channel First (BCF) scheduling algorithm

with Best Channel First (BCF) subchannel allocation policy

rtPS connectionsnrtPS connections

Be connections

High Priority

connections

Low Priority

connections

1

( )i

THrtPS

i f

B tQ

R T>

else

High-priority allocation

allocate until

By

* arg max{ ( )}i

ii SNR t =

*i

* ( ) 0iM t

*

* arg max{ ( , )}i

k SNR t

=

Choose a new *i

If all RAUs over this frame

are assigned

End

Low-priority allocation

allocate until

By

* ( ) 0iM t

*

* arg max{ ( , )}i

k SNR t

=

* arg max{ ( )}ii

i SNR t =

*i

If

(1) all RAUs over this frame

are assigned

or

(2)no high-priority packets

waiting for tansmission

no high-priority packets


else

Choose a new *i


are assigned

else


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3.3 Proportional Fair (PF) scheduling algorithm

with Best Channel First (BCF) subchannel

allocation policy

I. Estimate of Data Volume in Video Buffer and

Transmission Priority of Connections

The Proportional Fair (PF) algorithm proposed in [10] has the same

concept of the high-priority and the low-priority assignment as BCF

scheduling describing in section 3.2. That is briefly specified as the

following:

At each frame, the base decides the priorities for video mobiles

according to the following three conditions:

(1) (3.7)

The priority of all video packets for mobile i remains in low priority.

Let ( )i

M tbe data in bits that need to be transmitted for mobile i and set a

default value of ( )i

M t to be one-packet size, which we define one packet

containing 576 bytes for convenience.

(2) (3.

The base gives high priority with the first one packet to mobile i.

Thus, we can define ( ) 576*8iM t= (in bits).

(3)

The base station gives high priority with the first two packets to the video

1

( )i

THrtPS

i f

B tQ

R T>

1 2

( )iTH TH rtPS

i f

B tQ Q

R T >

2

( )iTH rtPS

i f

B tQ

R T


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mobile i. As the same way, we assign ( ) 576*8*2i

M t= (in bits).

II. Best Channel first subchannel allocation

Proportional Fair (PF) scheduling algorithm is designed to achieve fair

transmission between any mobile regardless of its channel quality.

Consider ( )i

r tto be the instantaneously transmitted data rate of mobile i

at frame t and ( )i

R tto be the estimate of the average data rate of mobile i

from initial time to the present frame t. Thus, the average rate is updated

frame by frame as:

( 1) (1 ) ( ) ( )i i i

R t R t r t + = + (3.10)

In this thesis, we set the update-coefficient 0.001= .

Performing as the mechanism in section 3.3, we use the following

formula to choose a mobile *i for transmission. However, not similar to

the BCF scheduling considering maximizing the total throughput, the PF

scheduling is an algorithm, which cares about the fair transmission for

every user connected on the network. The base selects a suitable mobile

i* to transmit as the following:

(3.11)

After selecting a fitted mobile*

i , the mapping block allocates the

traffic data belonging for mobile *i until * ( ) 0i

M t , and then continues to

seek for a new mobile *i if the present frame has any available RAUs

unallocated. The base also uses best subchannel first algorithm to allocate

subchannel for a selected mobile *i by:

(3.12)

* ( )arg max{ }( )

i

ii

r ti

R t=

*

* arg max{ ( , )}i

SNR t

=


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Where is the available subchannel index of mobile *i .

Figure 3.2 Proportional Fair (PF) scheduling algorithm with Best Channel

First (BCF) subchannel allocation policy

rtPS connectionsnrtPS connections

Be connections

High Priority

connections

Low Priority

connections

1

( )i

THrtPS

i f

B tQ

R T>

else

High-priority allocation

allocate until

By

*i

* ( ) 0i

M t

*

*arg max{ ( , )}

ik SNR t

=

Choose a new *i


are assigned

End

Low-priority allocation

allocate until

By

* ( ) 0iM t

*

*arg max{ ( , )}

ik SNR t

=

*i

If

(1) all RAUs over this frame

are assigned

or(2)no high-priority packets


no high-priority packets


else

Choose a new *i


are assigned

else

* ( )arg max{ }( )

i

ii

r ti

R t=

* ( )arg max{ }

( )

i

i i

r ti

R t

=


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32

3.4 Priority function (PRF) for scheduling

algorithm with Best Channel First (BCF)

subchannel allocationThe scheduling algorithm was published in [11]. Initially, the

mechanism was designed for OFDM systems. The authors introduced a

low-complexity priority function (PRF) for multiple connections with

diverse QoS requirements. They defined the PRF for each connection and

updated it dynamically depending on the wireless channel quality and

QoS satisfaction. In this thesis, we will modify the PRF to be fitted for

OFDMA system. At the MAC layer, the scheduler simply assigns the

order of mobiles per frame by deciding the priority of each connection as

following:

(3.13)

where ( )i t is the PRF functionfor connection i, at frame t, and we will

specify below. If any connections have the same value of( )i t , the

scheduler will randomly select one of them. In the following, we

introduce how to update the PRF ( )i t for those connections with

different QoS requirements:

I. For rtPS connections:

(3.14)

where,

* arg max{ ( )}i

ii t=

( ) 1, ( ) 1, ( ) 0

( )

( ) , ( ) 1, ( ) 0

0 , ( ) 0

irt i i

N i

i rt i i

i

R tif F t R t

R F t

t if F t R t

if R t

= < =


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1

( )iF t

rt is the rtPS-class coefficient in the range of [0,1]

( )i

F tis the rtPS-rate satisfaction indicator, defined as

(3.15)

with ( )iX tbeing the estimated video data in mobile i at frame time t.

The definition is the same as ( ) max{ ( 1) ( 1) ,0}rtpSi i i i f B t B t D t R T = + i in

section 3.2.

( )iR tis the AMC level according to average SNR of the remaining

available RAUs of mobile i at frame t.

NR is the maximum AMC level in the system, and we set 4.5NR = in

this thesis.

Depending on the PRF for rtPS connections, if( ) 1iF t< , that is, the

packets of connection i need to be sent immediately in order to avoid

playback delay and packet drop and the PRF will be rt, which the

highest priority is given. However, if ( ) 1iF t , the video data in mobile i

are enough to be played in next frame duration. Then, the priority is

affected on the value of. and the channel quality factor :

(3.16)

The channel factor is the normalized channel quality for mobile i. ThertPS connections, which satisfy their QoS requirements, have higher

priority depending on high-received SNR. Therefore, the values of PRF

for rtPS connections are ( ) [0, ]i rtt . Finally, we can notice that the

priority of each rtPS connection is according to its channel quality and

estimated volume of rtPS data that are stored in the buffer of the mobile

station.

( )( ) ii rtPSi f

B tF tR T=

( )[0,1]i

N

R t

R


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[0,1]nrt

1

( )iF t

II. For nrtPS connections:The PRF for nrtPS has the same definition as

(3.17)

When an nrtPS connection sets up the connection initially, it will ask

for a minimum transmission rate to the base. That is, the average data rate

of an nrtPS connection should be greater than the minimum required rate.

Thus, we define the average data rate for nrtPS connection of mobile i

as ( )i t . At the iteration, we update ( )i t as

(3.18)

where the updated factor is 0.001= and ( )ic tis the traffic data that are

transmitted to mobile i successfully at frame t. We can define the rate

satisfaction indictor as

(3.19)

The PRF for each nrtPS connection also has nrtPS-class coefficients rate

satisfaction indictor ( )iF t, andchannel quality factor.

If( ) 1iF t , the average transmission rate is satisfied, and its priority

depends on the effect of channel quality, and nrt.

If ( ) 1iF t< , the scheduler will give the connection a highest priority in

nrtPS class to satisfy the requirement as soon as possible.

Thus, the boundary of the PRF in this class is ( ) [0, ]i nrt t

( ) 1 , ( ) 1, ( ) 0( )

( ) , ( ) 1, ( ) 0

0 , ( ) 0

inrt i i

N i

i nrt i i

i

R t if F t R t R F t

t if F t R t

if R t

= < =

( )( ) ( 1) (1 ) i

i i

f

c tt t

T = +

( )( ) ii nrtPS

i

tF t

R

=

( )i

N

R t

R


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III. For BE connections:The BE service has no delay requirements and no minimum data rate

guarantee, thus the PRF for a BE connection may simply be

(3.20)

where BE is the BE-class coefficient and has a value in the range of [0,1].

Because the normalized channel quality and the BE-class coefficient are

both smaller than 1, the priority function of a BE connection ( )i t is

in[0, ]BE .

IV. Coefficient setting:If multiple connections have the same value of( )i t , the scheduler will

randomly choose one of them. In each iteration, the base select one user

i* for transmission at the MAC, and the mapping block will use the best

channel first (BCF) scheme to distribute RAUs to mobile i* until the data

volume for mobile i* in this frame has achieved one-packet size or no

packet belonging to mobile i* waits for transmission in the buffer at the

base station. The different classes of those three service coefficients play

important roles in giving discriminating priorities for each connection. If

we want the system to be strict priority assignment, i.e., the priority order

to be rtPS>nrtPS>BE classes, we can set the service-class coefficients to

be rtPS nrtPS BE > > . In other words, we can change the priority order

between those services. In this thesis, we set the service-class coefficients

under the constraint:

1.0 0.8 0.6rtPS nrtPS BE = > = > = . (3.21)

( )( ) ii BE

N

R tt

R =


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Figure 3.3 Priority Function (PRF) scheduling algorithm with Best

Channel First (BCF) subchannel allocation policy

rtPS connections nrtPS connections

Calculate PRF

( )i t

( ) 1, ( ) 1, ( ) 0

( )

( ) , ( ) 1, ( ) 0

0 , ( ) 0

irt i i

N i

i rt i i

i

R tif F t R t

R F t

t if F t R t

if R t

= < =

( ) 1, ( ) 1, ( ) 0

( )

( ) , ( ) 1, ( ) 0

0 , ( ) 0

inrt i i

N i

i nrt i i

i

R tif F t R t

R F t

t if F t R t

if R t

= < =

Be connections

( )( ) i

i BE

N

R tt

R =

Choose a user i** arg max{ ( )}

ii

i t=

Mapping Block

Best channel First (BCF)

End

If all RAUs over this framehave been assigned

If else

1.

If the total data that transmit to mobile

i* is smaller than one-packet size.

OR

2. No packets in buffer for mobile i* at

the base

If else

Select a new

i*


have been assigned


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3.5 Modified capacity priority algorithm

Figure 3.4 A Brief Topology of Our Cross Layer System

In the above section 3.1, we address that there is a trade-off between

achievement of total throughput and QoS requirements. If we want to

increase the transmission data rate, the users with highest average

received SNR values should be selected; if we want to achieve all the

users QoS requirements, we should transmit the traffic data regardless of

users channel conditions but may decrease the performance.

In this section, we modify the above algorithms and develop our

cross-layer scheduler to improve the network performance and satisfy

diverse requirements, respectively.

Figure 3.4 illustrates a brief topology of the cross layer system in this

thesis. At the AMC, each connection with either rtPS, nrtPS or BE

service asks the base for some bandwidth. Then, the base assigns

differentiable connection identification (CID) index for this connection.

rtPS connections

nrtPS connections

BE connections

Active

Connection

List

rtPS data

required data per Connection

nrtPS data

BE data

Data

burst

Frame Structure

Scheduler data slot Mapping

&

power assignment

2D Mapper

Channel Quality

Connection Mapping Turning

FEC block indexes

1 2 3 4 5 6 7 1

2

3

4

5

6

7

subchannel

The connections in highest channel quality area, that is, the average SNR of the connections in the highest level of modulationA:

B: A B = The connections that are within active List but not belong to A, that is,

i A

i B

i B

i A

i ActiveList


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The information of a connection will be written into the active list only if

the buffer for the connection at the base is not empty. In our model, the

scheduler decides the priority of a connection according to the channel

quality, the service type, and the required transmission data (in bits) per

frame. After the scheduling block, one user would be selected from our

algorithm and the following is the mapping block at the PHY layer. The

users transmission data would be translated directly to some RAUs,

determined by the mapping block. By estimating the average SNR

measurements of each mobile, the mapping block uses our allocation

algorithm to map suitable RAUs for the selected mobile.

I. QoS-satisfied factor ( , )R i for each connectionIn order to share the resource more fairly and to satisfy the QoS service

requirements, the base should know how many data each connection

needs to transmit at the present frame, or it would not achieve its QoS

requirement. For example, the PRF scheduler designed in section 3.4

gives the same service-class factor to each QoS-unsatisfied connection.

Therefore, if there are two connections with the same service-class factor,

and the connection A has more data needing to be transmitted than the

connection B, according to the PRF algorithm, the base would randomly

choose one user within the connection having the same service-class

factor. At the result, the PRF algorithm would uncertainly choose the

connection A. Thus, we design a QoS-satisfied factor ( , )R i to estimate

the average required trafficdata for connection i at frame period.

For an rtPS connection, the mobile stores the received packets and


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then plays the packets in order. When video data are getting empty, the

continuous playback of video streaming begins to lag. Therefore, the BS

needs to transmit sufficient packets to avoid the buffer being empty. The

scheduler estimates the amount of videodata ( , )vC i in the buffer of each

mobile at frameby:

( , ) ( , 1) ( , 1) ( )v v v v F C i C i D i R i T = + (3.22)

The QoS-satisfied factor ( , )R i for rtPS connection i is:

( , ) max{ ( ) 2 ( , ),0}R v F vi R i T C i =

(3.23)

where

( )vR i is the minimum data rate of rtPS connection i.

FT is the length of frame time in the system.

For an nrtPS connection i, its average transmission rate should be

greater than the minimum reserved rate ( )fR i . We compute the

QoS-satisfied factor ( , )R i per frame by:

( ) ( , )( , ) ( )

( , )

f f i

R f

f

R i C ii i

N i

= + (3.24)

where

( )f

R i is the minimum transmitted data rate for ith

nrtPS connection.

i

is past time in sec from the connection set up

i.e. if the initial connection-set time isi

s and then ( )i i

floor t s=

( , )f i

C i is the traffic data that has been transmitted successfully to the


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mobile i within ith

sec.

( )f

i the accumulated data from the initial setting time to 1i sec,

should be transmitted in order to satisfy QoS requirement for connection

i.

After all RAUs in frame block are all assigned, we update ( , )f i

C i

by:

( , ) ( , ) ( , )f i f i

C i C i D i = + i index in ActiveList (3.25)

where ( , )D i is the actually transmitted bits for connection i to its mobile

in frame block.

1min( ( , 1) 1,1) mod( , ) 0

( , )1 1

mod( , ) 0

if

F F

f

i

F F F

t sN i if

T TN i

t sif

T T T

=

=

i index of nrtPS connections (3.26)

where x represents the smallest integer equal to or smaller than x. be

if1

mod( , ) 0i

F F

t s

T T

=

fori index of nrtPS connections occurs, the

base updates the value in ( , )f i

C i and ( )f

i by:

( ) ( ) [ ( ) ( , )]f f f f ii i R i C i = + (3.27)

( , 1) 0f i

C i + = (3.28)

For each BE connection, guaranteeing no throughput or delay causes

serious latency and unfair resource management to the users. In this thesis,

we design a scheme to notice the base not to forget the feeble BE service.

( )hT i denotes the deadline for the base to transmit all BE data to the


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connection i. The QoS-satisfied factor ( , )R i for connection i at the

frame is:

( , )( , )

( , )

h

Rh

R ii

N i

= (3.29)

,where

( )0

( , )

min( ( , 1) 1,1) 0

h

h F

h

T iif t

N i T

N i if t

= =

>

(11)

( , 1) ( , ) ( , )h h

R i R i D i + = (3.30)

( , )h

R i is the remaining data waiting for transmission at the frame .

II. Hierarchical Scheduling SetAfter the base computes the QoS-satisfied factor ( , )R i for each

connection selected into the Active List. We design a hierarchical

scheduling algorithm to choose suitable users for transmission. We

propose a hierarchical cross-layer scheduling algorithm to improve the

efficiency of the system. We divide the connections on the active list into

three parts:

Part I

A set of the rtPS and the nrtPS connections whose average SNRs are

higher than the threshold of best MCS level, i.e. 64QAM 3/4, are grouped

into part I

Part II

A group of rtPS connections except those in part I.

Part III


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The remaining connections except from those in part Part II and I.

III.Scheduler DesignTo improve the total throughput, each users channel quality and the

traffic volume of each connection are necessary to be considered. The

algorithm consists of two steps, priority scheduling and 2D resource

allocation. First, the priority assignment function, which is updated

dynamically depending on the wireless channel quality and required data

volume, is defined as:

* arg max{ ( , ) ( , )}R j

ii i i =

(3.31)

where ( , )j

i is the channel quality coefficient and expressed as follows:

1

( )( , )

1( )

1

j

j M

lll j

i

M

=

=

(3.32)

The channel quality coefficient quantifies the channel condition by the

average capacityj

of all unassignedRAUs to the mobile j.

That is,

(3.33)

where

N is the number of all unassigned RAUs in the frame block.

( , )j

k is the average SNR value of k-th RAUs of the mobile j.

By introducing the parameter ( , )j i , the channel conditions will

2

1

1( ) log ( ( , ) 1)N

j j

k

kN

=

= +


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significantly affect the priority decision, especially in the case of high

SNR.

The key idea of the 2D mapping algorithm is to allocate bits and therequired power efficiently and maximize the total throughput at the PHY.

After the proposed scheduler has selected a suitable connection i* for the

mapping block, the mapping block will choose a RAU reserved for the

connection i*. According to the IEEE 802.16 standard, we assume that a

maximum of 30 subchannels can be used simultaneously in a cell. The

mapping algorithm is shown as follows:

We use one-order stage approach, which is proved in section 3.6 to

assign RAUs to users by

(3.34)

Where

is RAU index in frame structure

( )i

c is average capacity of RAU index k belonging to user i

*

1

1arg max{ ( ) [ ( )]}

1

M

i a

aa i

c cM

=

=


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3.6 Subchannel allocation algorithm for

OFDMA systems

3.6.1 Problem formulation

In order to obtain the cross-layer maximum throughput, we extend

the orthogonal subcarriers to the infinite-horizon case in frequency

domain. There are M users in a single cell with an entire bandwidth B.

Consider all system bandwidth divided into M non-overlapping frequency

sets. We assign a frequency setjR for user i. Then, we assign G

consecutive subchannels as an allocation unit, which is one RAU. Then

2

1 ( 1)

1( ) log (1 ( ) ( ))

lG

i i i

a l G

C k p a aG

= +

= + (3.35)

Let ( )iC kbe the average capacity for the i-th user at the k-th RAU

with average transmission power ( )ip a and the average signal-to-noise

ratio ( )i a , where a denotes a subchannel index. Therefore, we can

express the transmission rate of user i as

( )

i

i i

R

r C k dk = (3.36)In order to maximize system throughput, we denote the utility

function ( )U r r= and ( )i iU r r= to be a utility for user i. We obtain a

formula from the following theorem for the optimal cross-layer

subchannel assignment, and prove it.

Theorem: For a system with M users, if the RAU assignment is

optimal for all users, i.e.*, {1,2,..., }iK i M is optimal, and then we

formulate an N-order stage approach as:

* * *

1 1 1 1 1

1( ) [ ( ) ( )]

1

N N M N N

a a b a c a

a a b a cb all a N c a

C k C k C k M

= = = = =

+

(3.37)


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Proof of theorem:

Case 1: one-order approach:

For system with two users

Assume that if the base chooses an optimal RAU index*for user 1, the

throughput of the system would get to maximum value. However, if any

other index

is chosen, the performance will decrease. Therefore, we

define 1 1( )r C =

as the decrease value of data rate for user 1,

where 0k . Thus, the utility function can formulate as:

* * * *

1 1 1 2 2 2 1 1 2 2

( ( )) ( ( )) ( ) ( )U r C U r C U r U r + + +(3.38)

which is equal to

* * * *

2 2 2 2 2 1 1 1 1 1( ( )) ( ) ( ) ( ( ))U r C U r U r U r C + +

dividing by , we obtain* * * *

2 2 2 2 2 1 1 1 1 1( ( )) ( ) ( ) ( ( ))U r C U r U r U r C

+

according to

( ) ( )i i

C =

,

0 0i

r

,i=1,2

2

1

* *

2 2 2 2 22

02

* *

1 1 1 1 11

01

( ) ( )lim ( )

( ) ( )lim ( )

r

r

U r r U r c k

r

U r U r r c

r

+

since* *( ) '( ) 1

i i i i iU r r U r = = , we define that

*will satisfy 2 1( ) ( )c k c

For system with three users* * *

1 1 1 2 2 2 3 3

* * *

1 1 1 2 2 3 3 3

* * *

1 1 2 2 3 3

1{ ( ( )) ( ( )) ( )}

2

1{ ( ( )) ( ) ( ( ))}

2

( ) ( ) ( )

U r C U r C U r

U r C U r U r C

U r U r U r

+ + + +

+ + +

+ +

which is equal to

* * * *

2 2 2 2 2 3 3 3 3 3

* *1 1 1 1 1

[ ( ( )) ( )] [ ( ( )) ( )]

2[ ( ) ( ( ))]

U r C U r U r C U r

U r U r C

+ + +


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The same way in system with two users, we obtain that*satisfy

1 2 3

1( ) [ ( ) ( )]

2c c c +

(3.39)

It is the same way to approach one-order stage with M user, and then we

have a general formula of one-order stage when assigning a slot to user i:

* *

1

1( ) [ ( )]

1

M

i a

aa i

c cM

=

(3.40)

Case 2: two-order approach:

For system with three users

Let*

1and*

2be optimal granularity indexes for user 1and user 2. If we

select another 1

, 2

that will decrease the total data rate of system. Thus,

* *

1 1 1 1 1 2 2 2 2 2 1 2 1

*

3 3 2 3 2

* *

1 1 1 1 1 2 2 2 2 2

*

3 3 1 3 1 2 3 2

*

1 1 1 1 1 2 1 2

*

2 2 2 2 2 1

1{ ( ( )) ( ( ) ( ))

4( ( ))}

1{ ( ( )) ( ( ))

4

( ( ) ( ))}

1{ ( ( ) ( )))

4

( ( )

U r C U r C C

U r C

U r C U r C

U r C C

U r C C

U r C

+ +

+ + +

+

+ + + +

+ +

+ *2 1 3 3

*

1 1 1 1 1 2 1 2

* *

2 2 2 2 2 3 3 1 3 1

* * *

1 1 2 2 3 3

( )) ( )}

1{ ( ( ) ( )))

4

( ( )) ( ( ))}

( ) ( ) ( )

C U r

U r C C

U r C U r C

U r U r U r

+ +

+ +

+ +

+ + (3.41)

which is equal to


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* * * *

1 1 1 1 11 2 2 2 2 221 1 2 2

11 2 1 22

* *

3 3 31 32 3 3 313 2

1 32* * * *

3 3 31 3 3 3 3 32 3 33 1 3 2

31 2 1 32

*

1 1 11 12

( ) ( ) ( ) ( )4 ( ) 4 ( )

( ) ( )( )

( ) ( ) ( ) ( )2 ( ) ( )

(2

U r U r r U r U r r c c

r r

U r r r U r r c

rU r r U r U r r U r

c cr r

U r r r

+

+ + + +

+ + + +

+ *1 1 111 2

1 12

* *

2 2 22 21 2 1 222 1

21 2

) ( )( )

( ) ( )2 ( )

U r rc

r

U r r r U r r c

r

+

+

where we define

( )ij j i jr c =

The above inequality can be simplified

3 2 3 11 1 2 2 1 2 2 1

2 1 1 2 1 2

( ) ( )( ) ( ) ( ) ( )4 4 2 2 2 2

c cc c c c

+ + + +

where we define1

i =

for the digital system because the minimum

interval of granularity index is one.

That is,

1 1 2 2 3 2 3 1 1 2 2 1

1( ) ( ) [ ( ) ( ) ( ) ( )]2

c c c c c c + + + +(3.42)

where*

1and*

2satisfies the above inequality.

By the similar method, we approach a two-order stage with M users as

general formula:

2 2 2* * * *

1 1 2 2

1 1 1 11,2

1( ) ( ) [ ( ) ( )]1

M

b a b a

a b a bb b a

c c c cM

= = = =

+ +

(3.43)

Case 3: N-order approach:

* * *

1 1 1 1 1

1( ) [ ( ) ( )]

1

N N M N N

a a b a c a

a a b a cb all a N c a

C k C k C k M= = = = =

+ (3.44)

The approach is similar with the above proof.


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Chapter 4 Simulation Results

4.1 Simulation models for multi-user OFDMA

4.1.1 Parameters of MSs Generation Model

We perform a single cell to be hexagonal in shape with the length of

each side being one km. M users connect with the BS which is located at

the center of the cell. Each MS is randomly distributed in service area of

the cell. We consider two types of mobility for users that are pedestrian

and vehicular modes. The probabilities of the two mobility types are 0.5

identically at initialization. The moving direction is changed with

probability 0.05 per 10 sec. The moving speeds of the vehicular-type and

the pedestrian-type users are both generated as uniformly distribution.

The distribution of the pedestrian-type is with a mean of 3 (km/h) and a

variance of 0.25 (km/h), and that of the vehicular-type is with a mean of

60 (km/h) and a variance of 100 (km/h). Finally, we change the moving

speed of all MSs every 10 sec. We follow [10] to set all the parameters of

the MSs.

4.1.2 Channel Models of IEEE 802.16 OFDMA

systems

In this thesis, we evaluate the path loss and the fast fading channel in

a Multipath environment.


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Path Loss:

The path loss is defined in [14] and modeled by

10( ) 128.1 37.6 log ( ) [ ]PL d d dB= +

(4.1)

where d is the distance between the BS and a MS in kilometer. We

update the path loss every frame time.

Fast Fading:

The short-term fading gain is generated by the Jakes fading model

in [15] to be a single path. The transmission of the system works at the

carrier frequency 2 GHz. We update the short-term fading gain every

frame time. The moving speed of each MS will be illustrated in section

IV-E.

Multipath:

The Stanford University Interim (SUI) channel models with six

different scenarios (from SUI1 to SUI 6) are widely used for simulating

the multi-path environments of IEEE 802.16 systems [16]. We select SUI

2 channel model to simulate the multi-path environment with the

parameters in the omni-antenna situation in Table 4.1. The perfect

channel estimation is performed in the system.

Table 4.1 SUI 2 Channel Model ParametersTap1 Tap2 Tap3 Unit

Delay 0 0.5 1 s

Power (omni. ant.) 0 -12 -15 dB


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2

0

BN

N=

4.1.3 AMC Design at the PHY

We consider the downlink of a single cell consisting of M users. The

channel conditions are assumed to be known at the BS. [ ]jx denotes a

set of data symbols and [ ]j

is the transmission power at the kth

subcarrier of the jth

user in a frame.[ ]

j

is an estimate of the channel

transfer function combined with path loss and fast fading for any mobile i

of subcarrier k. The receive signal can be written as

[ ] [ ] | [ ] | [ ]j j j j n

R H x = + (4.2)

ndenotes the additive white Gaussian noise with zero mean and

variance , where B is assumed to be total available bandwidth

with N subcarriers per OFDMA symbol and N0 is the noise

power spectral density. Therefore, we can compute the signal-to-noise

ratio (SNR) for th subcarrier of jth

user by

(4.3)

We define the SNR per slot to be the average SNR of the subcarriers

in th subchannel. That is

(4.4)

where Ns is the total data subcarriers in the th subchannel.

We use the below formulas for FFT and IFFT to make sure that the value

of the computed SNR are identical in both the time domain and the

frequency domain.

2

0

[ ] [ ][ ]

j j

j

H

BN

N

=

1

( )( )

Nsj

jNs

=

=


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(4.5)

(4.6)

where

The BS selects the MCS modes (see Table I) of a MS using the

average SNR valued from the BS. The SNR requirement depending on

the different modulation types for a BER less than 10-6

is defined from

the figures 4 to 5 in [10]. We separate the entire SNR range over

transmission channels into N+1 (N=6) non-overlapping consecutive

intervals with boundary threshold defined in Table 4.2 and denoted as

1{ }n N

n n== which represents SNR threshold value from high to low according

to n=6 to n=1 for modulation modes.

The modulation mode n is selected when the average SNR of a specific

subchannel 1[ , )n n + for 1,...,n N= -1. When 1 < occurs, no data

will be sent because of the critical fading channel condition. On the other

hand, when N occurs, the MCS selector will choose mode N to be

transmitted.

Table 4.2 Required SNR for Different ModulationsModulation and Coding Required SNR

QPSK 1/2 6 dB

QPSK 3/4 9 dB

16 QAM 1/2 12 dB

16 QAM 3/4 18 dB

64 QAM2/3 21 dB

64 QAM3/4 30 dB

( 1)( 1)

1

1( ) ( )

Nj k

N

j

X k x jN

=

=

( 1)( 1)

1

1( ) ( )

Nj k

N

k

x j X k N

=

=

( 2 ) / exp

i NN =


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4.1.4 Physical Layer parameters

We consider only a single-hexagonal cell for convenience. The

length of each side of one cell is 1 km. A base is located at the center in

the cell. In Table 4.3, we show the physical layer parameter values in the

simulation of the system.

Table 4.3 Physical Layer ParametersPhysical Layer Parameter Value

Bandwidth (M Hz) 7

Number of data subcarriers per subchannel per

OFDM symbol

24

Number of data subcarriers per subchannel 48

Number of subchannels per OFDM symbol 30

Ratio of cyclic prefix time to useful time per

OFDM symbol

OFDM symbol per frame 30

Thermal noise density (dBm/Hz) -164

Total transmit power of a

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A Cross Layer Scheduling and Resource Allocation Algorithm for OFDMA Wireless Networks