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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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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
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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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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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