Spectrum Underlay Method

7/27/2019 Spectrum Underlay Method

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MAKERERE UNIVERSITY

COLLEGE OF ENGINEERING, DESIGN, ART

AND TECHNOLOGY

SCHOOL OF ENGINEERING

DEPARTMENT OF ECLECTRICALENGINEERING

KEVIN ACUNGKENA

09/U/550

Submitted in the fulfillment of the requirements for the award of the degree of Bachelor

of Science in Telecommunications Engineering of Makerere University

ACUNGKENA KEVIN | YEAR 4 PROJECT | May 31, 2013

QoS PERFORMANCE OF MIMO COGNITIVE

RADIO NETWORKS


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I

DECLARATION

I, Kevin Acungkena, to the best of my knowledge, hereby declare that the work herein is

my own and has not been presented for another degree in this or any other university or

institution of higher learning for the award of a degree.

.

Kevin Acungkena

Dr. Roseline Akol Ms. Sheila Mugala

Main supervisor Co. Supervisor

Date: Date:


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DEDICATION

I dedicate this report to my close friends, and my family. They have helped me come this

far with my education.


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III

LIST OF ABBREVIATIONS

Probability of detection

Probability of false alarm

PU transmit power

Maximum SU transmit power

CR Cognitive Radio

DSA Dynamic Spectrum Access

DSS Dynamic Spectrum Sharing

FCC Federal Communications Commission

IEEE Institute of Electronic and Electric Engineers

IP Internet Protocol

MIMO Multiple Input Multiple Output

MTBF Men Time Between Failure

MTRS Mean Time to Restore Service

NPMs Network Performance Matrices

PU Primary User

Q PU interference temperature

Qos Quality of Service

SISO Single Input Single Output

SNR Signal to Noise Ratio

SU Secondary User

UWB Ultra Wide Band


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IV

Contents

DECLARATION ........................................................................................................................................... i

DEDICATION .............................................................................................................................................. ii

LIST OF ABBREVIATIONS ..................................................................................................................... iii

LIST OF TABLES....................................................................................................................................... vi

LIST OF FIGURES.................................................................................................................................... vii

ACKNOWLEDGEMENT ........................................................................................................................ viii

ABSTRACT ................................................................................................................................................. ix

CHAPTER ONE: INTRODUCTION .......................................................................................................... 11.1 PROJECT BACKGROUND .............................................................................................................. 1

1.2 PROBLEM STATEMENT ................................................................................................................. 2

1.3JUSTIFICATION................................................................................................................................ 3

1.4 OBJECTIVES...................................................................................................................................... 3

1.5 METHODOLOGY ............................................................................................................................. 4

CHAPTER TWO: LITERATURE REVIEW............................................................................................. 5

2.1 COGNITIVE RADIO SYSTEM FUNDAMENTALS...................................................................... 5

2.1.1 COGNITI VE RADIO DEF INI TIONS......................................................................................... 5

2.1.2 COGNITI VE RADI O CHARACTERISTICS............................................................................... 7

2.1.3 COGNITI VE RADIO NETWORK ARCHI TECTURE............................................................... 9

2.2 MIMO SYSTEMS ............................................................................................................................. 10

2.2.1 HOW MIMO WORKS ................................................................................................................... 11

2.3 SPECTRUM UNDERLAY AND OVERLAY TRANSMISSION ................................................. 12

CHAPTER 3: METHODOLOGY ............................................................................................................. 14

3.1 INTRODUCTION ............................................................................................................................. 14

3.2 SYSTEM MODEL............................................................................................................................. 14

3.3 ANALYSIS OF SYSTEM MODEL ................................................................................................. 17

3.3.1 CAPACITY OF A COGNITI VE RADI O SYSTEM WHEN TH E PU I S SENSED ABSENT. 17

3.3.2 CAPACITY OF TH E COGNITI VE RADI O SYSTEM WHEN THE PU IS SENSED

PRESENT............................................................................................................................................. 19

3.3.3 CAPACITY OF A M IMO CHANNEL ........................................................................................20


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3.3.4 CAPACITY OF THE M IMO CR CHANNEL WHEN THE PU IS SENSED ABSENT.......... 23

3.3.5 CAPACITY OF TH E M IMO CR CHANNEL WH EN TH E PU IS SENSED PRESENT....... 24

3.4 RESULTS ........................................................................................................................................... 27

3.4.1 GENERATION OF TH E M IM O CHANNEL ............................................................................ 27CHAPTER 4: ACHIEVEMENTS, CHALANGES FACED, RECOMMENDATION, CONCLUSION,

....................................................................................................................................................................... 31

4.1 ACHIEVEMENTS ............................................................................................................................ 31

4.2 CHALANGES FACED ..................................................................................................................... 31

4.3 RECOMMENDATIONS .................................................................................................................. 31

4.4 CONCLUSION .................................................................................................................................. 32

BIBLIOGRAPHY ......................................................................................................................................... 33

APPENDIX .................................................................................................................................................. 35


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VI

LIST OF TABLES

Table 1: Parameters used for simulation ................................................................................ 28


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VII

LIST OF FIGURES

Figure 1: Spectrum Hole concept................................................................................................. 2

Figure 2: Cognitive Cycle ........................................................................................................... 8

Figure 3: Cognitive Radio Architecture ..................................................................................... 10

Figure 4: Multiple data streams transmitted in a single channel at the same time ......................... 11

Figure 5; system model ............................................................................................................. 14

Figure 6: General operation sequence of a cognitive radio system with quiet period for sensing

being inserted in between normal data transmission intervals...................................................... 15

Figure 7: Transmit and Receiver Shaping .................................................................................................. 21

Figure 8 : Constellation diagram for BPSK ............................................................................................ i6

Figure 9: Variation of throughput of a Cognitive radio system with respect to Primary User

activity in overlay and a combination of overlay and underlay modes when 2X2 MIMO

conditions are applied and when they are not applied. ............................................................................. 297

Figure 10 : Increase in through put with increase in the number of channels from SISO, 2X2

MIMO, and 4X4 MIMO......................................................................................................................... 308
http://f/Books/Project/project/Chapter%203.docx%23_Toc357583461http://f/Books/Project/project/Chapter%203.docx%23_Toc357583461


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VIII

ACKNOWLEDGEMENT

I would like to sincerely thank the Almighty God for the blessings and favor He has

continuously bestowed upon me. It is by His grace that I have successfully accomplished

this project and more so all the four years of my course.

Special thanks go to our main supervisor Dr. Roseline Akol and Ms.Sheila Mugala, our

co-supervisor. In the midst of all their preoccupations they found the time to offer all the

advice that my project partner and I needed and for that I am grateful. My deep

appreciation is extended to my parents for all the support they gave me not only duringthe course of this project but throughout my school years especially my mother.

I cannot forget to give a special thanks to my project partner Joshua Waiswa without

whose help it would have been almost impossible for me to start this report. I thank her

for the all the support she gave me during the project especially at times when things did

not seem to go our way and also for all her contributions during the course of the project.


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IX

ABSTRACT

Todays wireless networks are characterized by fixed spectrum assignment policy. Given

the limitations of the natural frequency spectrum, it becomes obvious that the current

static frequency allocation schemes cannot accommodate the ever increasing spectrum

frequency demand. According to the FCC, temporal and geographical variations in

spectrum usage range from 15% to 85% causing spectrum regulatory bodies to seek for

innovative techniques that can offer new ways of exploiting the available spectrum are

needed.

Cognitive radio (CR) technology is envisaged to solve the problems in wireless networks

resulting from the limited available spectrum and the inefficiency in the spectrum usage

by exploiting the existing wireless spectrum opportunistically. CR networks, equipped

with the intrinsic capabilities of the cognitive radio, will provide an ultimate spectrum

aware communication paradigm in wireless communications. CR networks, however,

impose unique challenges due to the high fluctuation in the available spectrum as well as

diverse quality-of-service (QoS) requirements


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CHAPTER ONE: INTRODUCTION

The lack of communication resources especially because of overloaded frequencies

has been seen during the last years when wireless communications has been increasingly

taken into use by consumers.

Wireless operators are now continuously looking for solutions to avoid overloading their

frequencies. Much can be done by using existing resources more effectively by taking

cognitive radio systems into use. A cognitive radio system (CRS) is aware of its

environment and makes decisions considering the performance of the whole radio system

and is able to learn of its environment and performance.

The spectral efficiency in bit/s/Hz of modern systems in a given frequency band is rather

high. The performance of the CRSs is measured in terms of spectrum occupancy which is

defined as the percentage of the total bandwidth that is used on the average.

1.1 PROJECT BACKGROUND

The idea behind a Cognitive Radio (CR) in Wireless Networks are to enable a cognitiveprotocol for a Secondary (unlicensed) User to access and use temporarily the spectrum

unused by the Primary (licensed) User, which is referred to as spectrum hole or white

space, in an intelligent way without causing any harmful interference with primary users.

If this band is further used by the licensed user, the cognitive protocol can move to

another spectrum hole or stay in the same band altering the transmission power level or

using another modulation scheme to avoid the interference. Spectrum sensing can be

considered as the main issue that has to be done to enable the cognitive radio users to

explore white space opportunities and to avoid interference with the primary users.

Moreover, Dynamic spectrum access (DSA), Dynamic spectrum sharing (DSS) are the

major goals of cognitive radio techniques and have responsibility of enabling cognitive

radio users to share the spectrum resources by determining who will and when can access


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the channel to win the availability of sending or receiving data through the white spaces.

F igure 1: Spectrum Hole concept

1.2 PROBLEM STATEMENT

A CR system dynamically senses bands and uses a band if its usage does not affect a

primary user (PU). Given that the CR system should not disturb the PU who has usage

rights to the band, the CR system should carefully and frequently sense the spectrum. If

the PU is detected in a certain band when the CR system is utilizing it, then the CR

system should immediately stop using the band and find another band to use. Otherwise,

the performance of both the CR system and the PU will be greatly deteriorated.

CR networks, however, impose unique challenges due to the high fluctuation in the

available spectrum as well as diverse quality-of-service (QoS) requirements

Quality of Service parameters in cognitive radio networks are mainly data throughput and

delay to accessing a channel.

Cognitive radio systems operate in a way that transmission only takes place if the PU is

sensed absent and transmission has to be stopped if the PU is sensed present. This can

lead to increased transmit time for the SU, thus reducing the user experience of the

service (reduces the QoS of the SU communication system).


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The switching on and off of transmission can lead to information los for real-time

applications for example voice communication or real-time gamming.

1.3JUSTIFICATIONIncreasing wireless networks use - enabled with new technologies, services, and devices,

puts pressure on network operators to develop new business models and new ways to

earn in a situation where the lack of available radio resources turns to be a bottleneck for

increase in the business.

A survey made by the Federal Communications Commission (FCC) indicates that the

actual licensed spectrum is largely underutilized in a vast temporal and geographical

dimensions [1]. Cognitive Radio finds white spaces which it can transmit its information.

Increasing spectrum usage would lead to higher data rates, better quality of service and

higher channel capacity. In this project, the SU is allowed to transmit in both overlay and

underlay modes of transmission and then MIMO radio technology is used to significantly

increase the available capacity.

1.4 OBJECTIVES

General Objective

To increase the Quality of Service (QoS) performance of the Cognitive Radio system

(SU)

Specific Objective

Achieve an increase in throughput of the SU by allowing him to transmit even in when

the PU is sensed present and also using MIMO techniques to further increase throughput,

thus increasing the QoS of the SU transmission


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1.5 METHODOLOGY

The methodology used to execute the project included coming up with the specific

problem statement which were addressed by the project. The problem statements

included:

1 Finding the capacity of Cognitive overlay and underlay transmission modes2 Finding the capacity of a MIMO radio channelTheoretical review of the underlying CR and MIMO systems were carried out using

information contained in journals, published papers from IEEE, reports and the internet.

MIMO technology is employed in CR in order to improve the capacity of the CR radio

system

A MIMO CR network was then modeled using the knowledge obtained and simulated

using MATLAB software. Results were then generated for the SISO CR overlay transmit

mode, SISO CR overlay-underlay transmit mode, MIMO CR overlay transmit mode,

MIMO CR overlay underlay transmit mode.


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Make use of location awareness to ensure that radio emissions do not interferewith licensed broadcasters.

Understand and follow the actions and choices taken by their users to becomemore responsive and anticipate user needs over time.

Formulate and issue queries, one radio to another. Execute commands sent by another radio. Fuse contradictory or complementary information.

The fact that there is an increase in research on cognitive radio and many industries are

interested in this concept, there is a need for a common terminology to define cognitive

radio for manufacturers, regulators, researchers, and users all to be able to advance the

development of cognitive radios.

The following definitions are some of the most commonly used:

Simon Haykin defines a cognitive radio as: An intelligent wireless communication

system that is aware of its surrounding environment (i.e., outside world), and uses the

methodology of understanding-by-building to learn from the environment and adapt its

internal states to statistical variations in the incoming RF stimuli by making

corresponding changes in certain operating parameters (e.g., transmit-power, carrier

frequency, and modulation strategy) in real-time, with two primary objectives in mind:

[3]

Highly reliable communications whenever and wherever needed;

Efficient utilization of the radio spectrum.

The broader IEEE tasked the IEEE 1900.1 group to define cognitive radio which has the

following working definition [IEEE 1900.1]: A type of radio that can sense and

autonomously reason about its environment and adapt accordingly. This radio could

employ knowledge representation, automated reasoning and machine learning

mechanisms in establishing, conducting, or terminating communication or networking


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functions with other radios. Cognitive radios can be trained to dynamically and

autonomously adjust its operating parameters.[3]

From the above definitions, cognitive radios have key features associated with them and

these include: [4]

Awarenessa) Theperception and retention of radio-related information

b) The functionality with which a radio maintains internal information about its location,

spectrum environment, or internal state, and is able to detect changes in that information.

Radio awareness is required for supporting the cognitive control mechanism.

c) The perception and retention of information by a radio. Typical types of information

used in a cognitive radio include location, environmental information, and internal states. Perception

The process of acquiring, classifying, and organizing information.

ReasonThe application of logic and analysis to information.

The term cognitive radio comes in part from the combination of awareness and

reasoning capabilities.

CognitionThe capacity toperceive, retains, and reason about information.

AgencyThe capacity to make and implement choices.

IntelligenceExhibiting behavior consistent with a purposeful goal.

While a system could be cognitive without exhibiting agency (e.g., a brain in a jar), or

could have cognition and agency without intelligence (e.g., a person who makes all of

his/her choices by a flip of a coin), all three aspects are critical to the cognitive radio

design paradigm.

2.1.2 COGNITIVE RADIO CHARACTERISTICS

These are majorly cognitive capability and reconfigurability


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1. Cognitive capabilityThis is the ability of the Cognitive Radio to capture information from its radio

environment. By this, portions of unused spectrum at a specific time and location can be

identified and best spectrum and operating parameters can be identified. [5]

F igure 2: Cogni tive Cycle

Source (B. W. a. K. .. R. Liu, "Advances in Cognitive Radio Networks: A Survey," IEEE

Journal Of Selected Topics in Signal Processing, vol. 5, no. 1, pp. 1-15, 2011.)

Spectrum sensing: The cognitive radio monitors available spectrum bandscapturing there information and then detects spectrum holes.

Spectrum analysis: The characteristics of the detected spectrum holes areestimated

Spectrum decision: the radio determines the data rate, transmission mode and thebandwidth of transmission. The appropriate spectrum band is chosen according to

spectrum characteristics and user requirements.

Spectrum mobility: This is performed it the current spectrum band in use becomeunavailable or during transmission to provide a seamless transmission. This can

be triggered by the appearance of a primary user, user movement or traffic

variation.


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2. ReconfigurabilityThe Cognitive radio can be programed to transmit and receive on a variety of frequencies

and use different transmission access technologies supported by its hardware design

enabling the CR to adapt easily the dynamic radio environmnet.

Operating frequency: A CR is capable of changing the operating frequency. Basedon information about the radio environment, the most suitable operating

frequency can be determined and the communication dynamically performed on

this appropriate operating frequency.

Modulation: A CR should reconfigure the modulation scheme adaptive to theuser requirements and channel conditions. For example, in the case of delay

sensitive applications, the data rate is more important than the error rate. Thus, themodulation scheme that enables the higher spectral efficiency should be selected.

Conversely, the loss-sensitive applications focus on the error rate, which

necessitate modulation schemes with low bit error rate.

Transmission power: Transmission power can be reconfigured within the powerconstraints. Power control enables dynamic transmission power configuration

within the permissible power limit. If higher power operation is not necessary, the

CR reduces the transmitter power to a lower level to allow more users to share the

spectrum and to decrease the interference.

Communication technology: A cognitive radio can also be used to provideinteroperability among different communication systems.

2.1.3 COGNITIVE RADIO NETWORK ARCHITECTURE

The Cognitive Radio network can be classified in the primary network and the

secondary network. The primary network has exclusive rights to a certain spectrum

band while the secondary network doesnt have a license to operate in the desired band.

There are three different access types over heterogeneous networks which show different

implementation requirements;

Primary Network Access. A CR user can access the primary base station throughthe licensed band.


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Cognitive radio Network Access. A CR user can access his own CR base stationboth in the licensed and unlicensed spectrum band. The medium access scheme is

independent of the primary network as all interactions occur inside the CR

network.

Cognitive radio Ad Hoc Access. Users can communicate with each other throughan ad hoc connection on both the licensed and unlicensed spectrum bands. The

CR users can have their own medium access technology.

F igure 3: Cognitive Radio Ar chitecture

Source: B. W. a. K. .. R. Liu, "Advances in Cognitive Radio Networks: A Survey," IEEE

Journal Of Selected Topics in Signal Processing, vol. 5, no. 1, pp. 1-15, 2011.

2.2 MIMO SYSTEMS

Wireless communication using multiple-input multiple-output (MIMO) systems enables

increased spectral efficiency for a given total transmit power. Increased capacity is


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achieved by introducing additional spatial channels that are exploited by using space-time

coding.

MIMO systems are a natural extension of developments in antenna array communication.

Systems with multiple antennas at the receiver and transmitter are referred to as multiple

input multiple output systems. The multiple antennas can be used to increase data rates

through multiplexing or to improve performance through diversity.

2.2.1 HOW MIMO WORKS

MIMO takes the advantage of multipath using multiple antennas to send multiple parallel

signals from the transmitter. In urban environments, these signals bounce off trees,

buildings etc. and continue on their way to the receiver but in different directions.

Multipath occurs when the signals arrive at the receiver at various times.

MIMO uses an algorithm to sort out the multipath signals to produce on signal that has

the originally transmitted data. This delivers simultaneous speed, coverage and reliability

improvements.

F igure 4: M ul tiple data streams transmitted in a single channel at the same time

Source [6]

2.2.1 TYPES OF MIMO [7]


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Space Time Transmit Diversity (STTD) - The same data is coded andtransmitted through different antennas, which effectively doubles the power in

the channel. This improves Signal Noise Ratio.

Spatial Multiplexing (SM)- delivers parallel streams of data to the receiver byexploiting multi-path. It can double (2x2 MIMO) or quadruple (4x4) capacity and

throughput. SM gives higher capacity when RF conditions are favorable and

users are closer to the BTS.

Uplink Collaborative MIMO Link- Two devices can collaboratively transmiton the same sub-channel which can also double uplink capacity.

2.3 SPECTRUM UNDERLAY AND OVERLAY TRANSMISSION

Radio regulatory bodies are recognizing that the rigid spectrum assignment granting

exclusive use to licensed services is highly inefficient, due to high variability in traffic

statistics across time, space and frequency.

The most appropriate approach to tackle the great spectrum variability as a function of

time and space calls for dynamic access strategies that adapt to the electromagnetic

environment. Cognitive radio originated as a possible solution to this problem usingdifferent paradigms to allow secondary users to dynamically access the licensed spectrum

under the constraint of not inducing quality of service degradations intolerable to the

primary users.

Three basic approaches have been considered to allow concurrent communications:

spectrum overlay, spectrum underlay and hybrid, interweave.

In overlay systems, secondary users allocate part of their power for secondary

transmission and the remainder to assist (relay) the primary transmission. By exploiting

sophisticated coding techniques, based on the knowledge of the primary users message

and/ or codebook at the cognitive transmitter, these systems offer the possibility of

concurrent transmission without capacity penalties. [8]


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In underlay CR systems, secondary users (SU) are admitted to access spectrum bands

originally allocated to primary users (PU) only if interference caused by the secondary

users is regulated below a predetermined level, i.e., interference temperature. The

interference constraint for the primary users may be met by using multiple antennas to

guide the cognitive signals away from the primary receivers, or by using a wide

bandwidth over which the cognitive signal can be spread below the noise floor, then

despread at the cognitive receiver. The latter technique is the basis of both spread

spectrum and ultra-wideband (UWB) communications. The interference caused by a

cognitive transmitter to a primary receiver can be approximated via reciprocity if the

cognitive transmitter can overhear a transmission from the cognitive receivers location.

Alternatively, the cognitive transmitter can be very conservative in its output power toensure that its signal remains below the prescribed interference threshold. In this case,

since the interference constraints in underlay systems are typically quite restrictive, this

limits the cognitive users to short range communications. [9]

In the hybrid/ interweave scheme, the underlay approach is incorporated in the frame of

the overlay CR system. The CR system is normally working in an overlay mode and thus

the secondary transmitter opportunistically accesses access the licensed spectrum when a

primary user is idle. However, when a secondary user makes its throughput to maximizeand maintains secondary users queue to be stable, the CR system operates in an underlay

mode and a secondary transmitter is allowed to send their packets to its destination even

though the primary user is also transmitting. [10]


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CHAPTER 3: METHODOLOGY

3.1 INTRODUCTION

The focus of this chapter is to determine how MIMO systems impact the Quality of

service of the Cognitive radio users, the QoS parameter of concern is capacity of the

system. Knowing that cognitive Radio systems have the ability to change transmission

parameters like power, there is a possibility of the SU to transmit information even when

the PU is present increasing the average capacity and also reduction in traffic delay, thus

a better QoS for the SUs.

In this project, the SUs can transmit information under interference temperature

constraints of the PUs making it possible to transmit information even when the PU is

present. This reduces on delay experienced by the SUs.

3.2 SYSTEM MODEL

F igure 5; system model

In this model, the SUs are equipped with a transmitter having multiple antennas, same as

the receiver. The PU is has a single antenna. The SU is allowed to switch from overlay

(transmission in absence of the PU) to underlay (transmission in the presence of the PU)

in order to increase the average capacity over time. First a scenario when the SU is


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equipped with a single transmit and receive antenna and then apply MIMO conditions

which increase the capacity of the system.

SUs transmit information over a defined frame period T. This frame period contains a

sensing time tand data transmission time T-tand at the end of each frame, the SU knows

whether the PU is present or not allowing it to decide whether to transmit using the same

power or change transmit power.

F igure 6: General operation sequence of a cogni tive radio system wi th quiet peri od for

sensing being inserted in between normal data transmission in tervals

Source (Interference-constrained adaptive simultaneous spectrum sensing and data

transmission scheme for unslotted cognitive radio network by Xianjun Yang, Xiaofeng

Tao, Qimei Cuiand Y Jay Guo )

In MIMO systems, multiple data streams are transmitted across the MIMO channel using

the Alamouti space time block code [11] which combines all copies of the received signal

in an optimal way to extract as much information as possible.

At a given symbol period, two signals are simultaneously transmitted from the two

antennas. The signal transmitted from antenna is denoted by and from antenna

by . During the next symbol period signal is transmitted from antenna , and

signal is transmitted from antenna where is * the complex conjugate operation.For

a 2X2 MIMO system


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space

Tim

e

The received signal is denoted as;

(1)

(2)

This can be represented in matrix notation as;

(3)

The received signal can be represented by the equation:

(4)

Where H is the channel matrix. The additive noise, n is assumed to be a white Gaussian

random variable with zero mean and unit variance.


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3.3 ANALYSIS OF SYSTEM MODEL

Suppose that we are interested in the frequency band with carrier frequency fc and

bandwidth W and the received signal is sampled at sampling frequency fs, which is

greater than the Nyquist rate. When the primary user is active, the discrete received signal

at the secondary user can be represented as [12]:

(5)

Which is hypothesis .

When the primary user is inactive, the received signal is given by:

(6)

This is hypothesis .

The following assumptions are made.

The primary signal is an iid random process with man zero and variance . The primary signal is independent of the noise

3.3.1 CAPACITY OF A COGNITIVE RADIO SYSTEM WHEN THE PU IS

SENSED ABSENT

This takes place under Hypothesis . , where the SU receives only noise from the

channel.

IfC0is the throughput of the SU operating in the absence of the PU with an SNR of

SNRsand C1the throughput when the SU operates in the presence of the PU with SNRp

as the SNR of the PU received at the receiver of the SU transmission link, then [12]


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(7)

And

(8)

If the PU is not present and no false alarm is generated by the SU, the achievable

throughput is:

(9)

When the primary user is active but not detected by the secondary user, the achievable

through put is:

(10)

If P (H1) is the probability for which the primary user is active in the band of interest, the

achievable through put of the cognitive system is:

(11)

Where

(12)


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3.3.2 CAPACITY OF THE COGNITIVE RADIO SYSTEM WHEN THE PU IS

SENSED PRESENT

To obtain the available through put of the system when the PU is sensed present, we

consider the outage probability of the SU taking into consideration the interference

temperature of the PU. The mode of data transmission when the PU is sensed present is

known as underlay transmission.

In underlay CR systems, Secondary Users (SU) are admitted to access the spectrum

bands originally allocated to the Primary Users (PU) only if the interference caused by

the SU is regulated below a predetermined level interference temperature [13].

The SU can transmit data under the conditions of a false alarm or detection of the PU. For

a MIMO system, we find the capacity on each channel under interference temperature

constraints of the PU and then sum up for all channels to obtain the total capacity for the

MIMO CR channel

The capacity the SU is given by [13],

(13)

Where the departure rate is for the SU in underlay mode, is the hybrid rate,

is the penalty term caused by periodically sensing the interference channel in an underlay

mode.

(14)

is the outage probability of the SU link in overlay mode when there is no

interference from the PU.


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is the outage probability of the SU link in overlay mode when there is

interference for the PU

(15)

(16)

Denotes an exponential integral function

3.3.3 CAPACITY OF A MIMO CHANNEL

How to obtain independent channels from a MIMO Link

Using Alamouti space time Block Codes, a MIMO channel can be obtained between the

transmitter and receiver, in order to measure the capacity of the MIMO link, the capacity

of each individual channel has to be obtained and then summed up.

Considering a MIMO channel with channel gain matrix H known to both the

transmitter and receiver. Let RH denote the rank ofH, from matrix theory, we can obtain

the Singular Value Decomposition (SVD) ofH as [14]:


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Where the matrix U and matrix V are unitary matrices and is an

diagonal matrix of singular values of H which have the property that

for being the ith eigenvalue of the matrix HHH ,and RH of these singular

values are nonzero. RH is the rank of the matrix H.

Parallel decomposition of a channel is obtained by defining a transformation on the

channel inputx and outputy through transmit precoding and receiver shaping.

In transmit precoding, the input to the antennas x is generated through a linear

transformation on the input while receiver shaping performs a similar operation at the

receiver as shown in the diagram below

F igure 7: Transmit and Receiver Shaping

Transmit precoding and receiver shaping transform the MIMO channel into RH parallel

independent channels with the ith channel having a channel gain . Channel with these

gains are independent since the resulting parallel channels dont interfere with each other

and are linked only though the power constraint and the performance of each channel is

dependent on its gain.

Channel known at the transmitter

MIMO decomposition allows for characterization of the MIMO channel capacity for a

fixed channel matrix H known at the transmitter and receiver where the capacity equals

the sum of capacities on each of the independent parallel channels with transmit power

optimally located between these channels.


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Optimization of transmit power across the independent channels results from optimizing

the input covariance matrix to maximize the capacity formula. Using SVD and the

properties of unitary matrices, the capacity of the MIMO channel under CSIT and CSIR

is given as [15];

(17)

Since , the above capacity can be expressed in terms of the power allocation Pi to

the ith parallel channel as:

(18)

Where and is the SNR associated with the ith channel at full

power. Solving the optimization leads to a water filling power allocation for the MIMO

channel

(19)

The SNR of the signal becomes

(20)


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For some cutoff value , the resulting capacity is given as

(21)

3.3.4 CAPACITY OF THE MIMO CR CHANNEL WHEN THE PU IS SENSED

ABSENT

Capacity of the ith MIMO Link

Considering frame structure of the Cognitive Radio system to be made up of a sensing

slot and a data transmission slot. If the sensing duration is tand the framed duration is T,

then the capacity of the ith MIMO link is given as;

(22)

Equation 22 is obtained by substituting for SNR in equation 7 with the value of SNR in

equation 20.

(23)

Equation 23 is obtained by substituting for SNR in equation 8 with the value of SNR in

equation 20.

If the primary user is not present and no false alarm is generated by the secondary user,the achievable throughput on the ith MIMO link is:

(24)


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When the primary user is active but not detected by the secondary user, the achievable

through put on the ith MIMO link is:

(25)

If P (H1) is the probability for which the primary user is active in the band of interest, the

achievable through put on the ith MIMO link of the cognitive system is:

(26)

Where

The total through put of the MIMO system is the summation of the throughput from

individual channels of the MIMO system

(27)

3.3.5 CAPACITY OF THE MIMO CR CHANNEL WHEN THE PU IS SENSED

PRESENT

Equations used are modified equations of section 3.3.2 taking into account MIMO

conditions

Capacity of the ith MIMO link


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Outage probability of the ith link when the SU switches to underlay mode when the PU is

sensed present under false alarm conditions

(28)

Where Ps is the SNR of the SU, Rs is the minimum transmission rate of the SU and is

the channel gain from the SU transmitter to the SU receiver. Prout1 being the outage

probability of the SU when transmitting under the conditions of false alarm.

Employing MIMO conditions for the ith channel,

(29)

Substituting equation 20 in equation 15 for SNR

Outage probability of the ith link when the SU switches to underlay mode when the PU is

detected present and is present. When the PU exists, then the SU experiences more

interference due to the presence of the PU [13].


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Where Pp is he SNR of the PU signal and is the interference channel gain from the PU

transmitter to the SU receiver.

Employing MIMO conditions for the ith MIMO channel,

(30)

Substituting equation 20 in equation 16 for SNR

Where Q is the interference temperature and Pp is the transmit power of the PU

The outage probability for the ith MIMO channel due to false alarm and when the PU is

sensed present and is present is given by:

(31)

Where the probability of is false alarm and is the probability of missed detection.

The capacity of the ith MIMO CR link is then given by the equation


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(32)

Capacity of the MIMO channel

The total capacity of the MIMO CR link is a summation of the individual capacities of

each link.

Where T is the frame duration and t is the sensing time of the frame.

3.4 RESULTS

Application of both spectrum undelay and overlay methods of SU transmission are seen

to improve the average capacity of SU transmission which is enhanced by the application

of MIMO systems to the CR system as shown by the results below.

The results are got by varying average capacity of the SU over a period of 10 frames withthe activity of the PU.

3.4.1 GENERATION OF THE MIMO CHANNEL

Binary Phase Shift Keying is used for modulation of information in the model. It uses

two phases separated by 180. It takes the highest level of noise or distortion making it

the most robust form of modulation. Its however only able to modulate 1bit/symbol and

not suitable for high data rate applications [16].

Figure 8: Constellation Diagram for BPSK


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The two symbols generated using BPSK are then transmitted over the channel generated

using Alamouti Space time Block code.

Parameters used for simulation

Table 1: Parameters used for simulation

Parameter Value

Frame duration T 100ms

Frame sensing time t 2.5ms

SNR of the PU 10dB

SNR of the SU 10dB

Interference temperature of the PU 2dB

The MATLAB code used to generate results is shown in the appendix.


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Figure 9: Var iati on of th roughput of a Cogni tive radio system with respect to Primary

User activity in overl ay and a combination of over lay and under lay modes when 2X2

M IMO conditions are appli ed and for SISO

The graph in figure 9 indicates that the average throughput of a CR system drops with

increase in PU activity. In overlay mode, the average throughput drops to zero when PU

is active for all time of measurement. However when a combination of both overlay and

underlay is used, the SU still has a throughput even when the PU is present for all time. It

is also shown that there is a general increase in throughput when both overlay and

underlay are used.

The throughput of SISO channel is generally less than that of any MIMO channel. This is

illustrated in graphs of both figures 9and 10.


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Figure 10: Increase in through put with increase in the number of channels from SISO,

2X2 MIMO, and 4X4 MIMO

In figure10, the increase in average throughput from SISO to 2X2 to 4X4 MIMO is

shown as expected as the capacity is directly proportional to number of channels in any

given system.


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CHAPTER 4: ACHIEVEMENTS, CHALANGES FACED, RECOMMENDATION,

CONCLUSION,

4.1 ACHIEVEMENTS

As a telecommunications engineering student, some of the of radio communications

seamed complicated, however, during the project research, a lot of information exposed

lead to understanding what seamed obscure for example various radio network aspects

like conventional radio systems to MIMO and then CR technology.

QoS improvement of the CR system was achieved by improving the available capacity of

the SU. The project allowed the SU to transmit even in the presence of the PU, thus

having an increase in available capacity. MIMO systems were also employed to further

achieve an increase in the available capacity.

4.2 CHALANGES FACED

During the course of the project, some challenges were encountered, these are listed

below

1 Performance was only evaluated for a single MIMO CR user due to limited time andaccess to information. The results due to the performance of multiple CR users could

be therefore be different from those shown in the project.

2 It was difficult to define a MIMO communications channel3 The PU is only equipped with a single antenna as it was difficult to achieve results

when the PU is equipped with a MIMO system antenna.

4.3 RECOMMENDATIONS

How MIMO cognitive systems affect other QoS parameters should be studied in

order to have more conclusive results.

These include:

1. Availability2. Delivery


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3. Latency4. MTBF (Mean Time Between Failure)5. MTRS (Mean Time to Restore Service)

4.4 CONCLUSION

Radio frequency spectrum and channel capacity efficiency are one of the major concerns

in wireless communication systems today. Cognitive radio is a promising solution which

enables spectrum sensing for opportunistic spectrum usage by providing a means

for the use of spectrum holes.

In this project, the cognitive system has been allowed to send information even when the

PU is present considering interference temperature constraints of the PU. With this, therehas been an increase in the capacity of the Cognitive system compared to when the SU

only transmits if the PU is absent. Also the Cognitive system capacity has been enhanced

through the application of MIMO techniques.

It has been seen that with a Cognitive system operating in both overlay and underlay

modes equipped with a MIMO system, the average capacity of the SU is improved

compared to a case when the SU has a single channel and uses an overlay transmit mode.

Increase in capacity consequently reduces the transmit delay time of the SUs information


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BIBLIOGRAPHY

[1] F. CommunicationsCommission, "Spectrum Policy Task Force," Rep. ET Docket no. 02-135,

November 2002.

[2] VTT, "Cognitive Radio Systems, Enabler for Intelligent Wirelss Telecommunications," VTT, 29

March 2012. [Online]. Available:

http://www.vtt.fi/files/research/other/VTT_whitepaper_cognets_march2012.pdf.. [Accessed 14

November 2012].

[3] J. O. Neel, "Analysis and Design of Cognitive Radio Networks and Distributed Radio Resource

Management Algorithms," Blacksburg, VA, 2006.

[4] T. S. Forum, "Cognitive Radio Definitions and Nomenclature,"," SDR, 10 September 2008.

[Online]. Available: http://www.sdrforum.org/pages/documentLibrary/documents/SDRF-06-.

[Accessed 29 May 2013].

[5] B. W. a. K. .. R. Liu, "Advances in Cognitive Radio Networks: A Survey," IEEE Journal Of

Selected Topics in Signal Processing,vol. 5, no. 1, pp. 1-15, 2011.

[6] D. J. Sharony, "sunysb," [Online]. Available: www.ieee.li/pdf/viewgraphs/wireless_mimo.pdf.

[Accessed 12 November 2012].

[7] "http://en.wikipedia.org," [Online]. Available: http://en.wikipedia.org/wiki/MIMO. [Accessed12 November 2012].

[8] D. P. P. a. S. B. Gesualdo Scutari, "Cognitive MIMO Radio " Competitive optimality design

based on subspace projections"," IEEE Signal processing Magazine, pp. 46-50, 2008.

[9] S. A. J. I. M. S. S. Andrea Goldsmith, Breaking Spectrum Gridlock with Cognitive Radios: An

Information Theoretic Perspective, 2011.

[10] J. O. a. W. Choi, "A hybrid Cognitive Radio System of Underlay and Overlay Approach," IEEE ,

vol. 6, no. 10, pp. 1-5, 2010.

[11] F. Gregorio, Space Time Block codes for MIMO systems, 2005.

[12] Y. Z. E. P. a. A. T. H. Ying-Chang Liang, "Sensing-Throughput tradeoff for Cognitive Radio

networks," 2007.


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[13] J. O. a. W. Choi, "A Hybrid Cognitive Radio system: A combinaton of Underlay and Overlay

Approaches," Korea, 2010.

[14] A. Goldsmith, Wireless Communications, Cambridge University Press, 2005.

[15] A. Goldsmith, Wireless Communications, Cambridge University Press, 2005, pp. 117-118.

[16] T. E. R. A. D. O. Solomon Muhumuza, "Performance of MIMO Cognitive Radio Networks,"

2012.

[17] D. P. P. S. B. Gesualdo Scutari, "Cognitive MIMO Radio," Competitive optimality design based

on subspace projection, pp. 46-59, November 2008.

[18] A. R. S. Saeedeh parsaeefard, "Robust Distributed Power Control in Cognitive RadioNetworks," IEEE Transactions on mobile computing,vol. 12, no. 4, pp. 609-620, 2013.

[19] W. C. Jinhyung Oh, "A Hybrid Cognitive Radio System: A combination of Underlay and

Overlay Approaches," IEEE transactions on vehicular technology,vol. 6, no. 10, pp. 1-5, 2010.

[20] P. M. Torlak, "utdallas.edu," [Online]. Available:

http://www.utdallas.edu/~torlak/courses/ee6391/lectures/lecture5.pdf. [Accessed 19 March

2013].


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APPENDIX

MATLAB CODE FOR GENERATING GRAPHS

%%%%QoS Performance of MIMO Cognitive Radio Systems

%%%By: Acungkena Kevin and Joshua Waiswa

%%%Supervisors: Dr. Roseline Akol and Ms. Sheila Mugala

clear;

clc;

N = 2; %Number of channels between the transmitter and receiver

ip = rand(1,N)>0.5; %Generating 0 and 1 with equal proberbility

s = (2*ip-1); %Applying Bpsk mdulation to the symbols 1 and 0

%%Gnerating a channel between transmitter and receiver using alamouti Space

%%time Block

H = (1/sqrt(2))*[s(1),s(2);conj(s(2)),-conj(s(1))]

l = H*H'

R = eig(H*H');

%% If the channel has a threshold value of 0dB

yo = 10^0.1;


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%%If the signal power of the PU and SU is

SNRp = 10^1; %% SNR of the PU

SNRs = 10^1; %%SNR of the SU

%%%%Capacity of the MIMO CR channel

%%Frame duration of T and sensing time t

T = 100;

t = 2.5;

F = (T-t)/T;

%%Probability of false alram and detection of the PU by the SU

Pf = 0.2; %Probability of false alrm

Pm = 0.25; %Probability of missed detection

PH0 = [0,0.1,0.2,0.3,0.4,0.5,0.6,0.7,0.8,0.9,1]; % Probability for which the PU is active

in the band of interest

PH1 = 1-PH0; % Probability for which the PU is in-active in the band of interest

z=[1,0.9,0.8,0.7,0.6,0.5,0.4,0.3,0.2,0.1,0]; % PU activity factor

%%%Capacity of the MIMO_CR_Underlay Link

i = 1;


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while i


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Pr = Pf*Pr1 + (1-Pm)*Pr2;

%%%Capacity of the ith MIMO_CR_Underlay link

C(i) = F*(1-Pr)*log2(1+k);

i = i+1;

end

%%Total Underlay MIMO capacity of the link

C_U = sum(C)*z;

%%%Capacity of the MIMO_CR_Overlay link

i = 1;

while i


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C0(i)=C0(i)*0;

C1(i)=C1(i)*0;

end

i=i+1;

end

%%Total Overerlay MIMO capacity of the link

C_O = (PH0*sum(C0) + PH1*sum(C1)).*(1-z);

%%%Capacity of the MIMO_CR_Overlay_Underlay for a period of one frame

C_MIMO = C_O + C_U;

%%%%Throughput of the SISO link

%Throught put of the overlay SISO link

SNR2 = SNRs/(1+SNRp); % SNR of the SU when the PU is present but sensed absent

C_0 = log2(1+SNRs);% Capacity of a Cognitive system in when the PU is absent and

sensed absent

C_1 = log2(1+SNR2); % Capacity of the CR system when the PU is present but sensed

absent


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%Acheived through put under different scenarios

R0 = F*(1-Pf)*C_0; % Achieved through put when the PU is absent and sensed absent by

the CR system

R1 = F*(1-Pm)*C_1;% Acheived through put when the PU is present but sensed absent

by the CR system

%Total through put of the CR system

Rt = PH0*R0 + PH1*R1; % Total through put over the time interval concerned

Rpu = Rt.*(1-z); %Average through put of the CR system over a period of 10 frames

%%Overlay of the SISO link

%%Capacity = ((T-t)/T)(1-Pout)Blog2(1+SNR)

Q = 10^0.2; %PU interferenc temperature of 2dB

Rs = 2; %Maximum rate for the SU is 2bit/second/Hertz

Psmax = SNRs; %Maximun transmit power for the SU is 10dB

Pp =10^1; %PU transmit poer of 10dB

A = Q/Psmax;

B = (2^Rs)-1;

SNR = 10^0.5; %SNR of the SU in underlay is 5dB

%%Outage probability under false alarm

Pout1 = (1 - exp(-A))*(1-exp(-B/Psmax))+exp(-A)-(exp(-A*(1+B/Q))/(1+B/Q));

%%Outage probablity when the PU is detected

C = B/Psmax;


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D = expint(((Q+B)*(Psmax+Pp*B))/(Pp*Psmax*B));

Pout2 =(1-exp(-A))*(1-(exp(-C))/(1+Pp*C))+exp(-A)-

(exp((1/Pp)+Q/(Pp*B)))/(Pp*B)*D;

%%Total outage Probability

Pouttotal = Pf*Pout1 + (1-Pm)*Pout2;

%%Capacity of the system in underlay mode

R = F*(1-Pouttotal)*log2(1+SNR);

%%%Variation of through put over the transmit duration

R3 = z*R;

%%%Total throughput of the SISO link over the period of 10 frames

C_SISO = Rpu+R3;

%%%Ploting the curves

plot(z,Rpu,'k:*',z,C_O,'k-.d')%,z,C_SISO,'k--v',z,C_MIMO,'k-o');

title('Through put of CR against PU activity ');

legend('Through put of SISO CR Overlay','Through put of 2X2 MIMO CR

Overlay');%,'Through put of SISO Overlay-Underlay','Through put of 2X2 MIMO CR

Overlay-Underlay');

xlabel('Primary user activity over a time interval of 10 frames');

ylabel('Average through put in bps/Hz');

clear;


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Documents

Spectrum Underlay Method