Spectrum Sensing Techniques and Cognitive Radio

UNIVERSITY AFFILIATION
DEPARTMENT OR FACULTY
COURSE ID & NAME
TITLE
SPECTRUM SENSING TECHNIQUES AND COGNITIVE RADIO
STUDENT NAME
STUDENT REGISTRATION NUMBER
PROFESSOR (TUTOR)
DATE OF SUBMISSION
2018

EXECUTIVE SUMMARY
Spectrum sensing in cognitive radios seeks to gain the notification on the usage of a given
spectrum that exists for the primary uses in a given region. A classical signal detection problem
where the channel gain, primary signal and noise are taken into account when tackling the
problem. The software defined radio, SDR, is set up in the software form and seeks to support a
wide range of frequencies alongside the configuration that can be modified for the users. The
SDR tend to be easily reconfigurable, easy to upgrade, have lower maintenance costs, and
responds to the changes in the operating environment. According to Mitola, the cognitive radio
cycle continually observes the environment, orients itself, creates plans and decides then acts.
The cognitive radio monitors the available spectral bands, captures the information or data
provided from these bands, and detects the spectrum holes. It focusses on the frequencies usage
and the mode identification. The cognitive users are the unlicensed users who need to keep
monitoring the spectrum. They usually seek to detect the presence of licensed or the primary
users. There are a number of merits associated with the use of cooperation in cognitive radio.
This paper looks at the implementation and testing of the cooperative cognitive spectrum sensing
within a network. The merits that stand out the in the cooperative spectrum sensing in a cognitive
radio network are the reduction of detection time and the increased agility. The cognitive users
are involved in the implementation using the proposed practical algorithm which allows
cooperation in random networks. Spectrum sensing aims at identifying the spectrum holes. The
cooperative spectrum sensing seeks to mitigate the multipath fading, shadowing and hidden
terminal problem.

TABLE OF CONTENTS
INTRODUCTION.......................................................................................................................................3
LITERATURE REVIEW............................................................................................................................4
SPECTRUM SENSING..........................................................................................................................4
DYNAMIC SPECTRUM ACCESS........................................................................................................7
TYPES OF SPECTRUM SENSING.........................................................................................................10
COOPERATIVE SPECTRUM SENSING............................................................................................10
RELATIVE PERFORMANCE MEASURES...........................................................................................13
SPECTRUM SENSING BANDWIDTH...............................................................................................13
TRANSMISSION TYPE SENSING.....................................................................................................14
SPECTRUM SENSING ACCURACY.................................................................................................14
SPECTRUM SENSING COMPLEXITIES AND LIMITATIONS...........................................................19
CONCLUSION.........................................................................................................................................23
REFERENCES..........................................................................................................................................23
APPENDIX...............................................................................................................................................23

LIST OF FIGURES
Figure 1 Matched filter decision schematic illustration..................................................................8
Figure 2 Energy detection method block diagram...........................................................................8
Figure 3 Plot of power against time - definition of spectrum holes................................................9
Figure 4 Cognitive radio architecture............................................................................................10
Figure 5 Cognitive radio implementation in a telecommunication mobile network.....................11
Figure 6 IEEE 802.22 implementation of cognitive radio prevalence for service providers........12
Figure 7 IEEE 802.22 wireless RAN classification compared to other key wireless standards. . .13
Figure 8 Hidden Network Problem solved by Cooperative Spectrum sensing.............................14
Figure 9 Basic Configuration of centralized cooperative spectrum sensing.................................14
Figure 10 Test statistics.................................................................................................................21
Figure 11 ROC - false alarm probability chart..............................................................................22
Figure 12 Test Statistic..................................................................................................................24

INTRODUCTION
It is a technology of wireless communication where the network or a user’s flexibility is
bound to change its transmitting or receiving parameters to achieve more efficient
communication performance without interfering with licensed or unlicensed users [1]. According
to Mitola, the cognitive radio cycle continually observes the environment, orients itself, creates
plans and decides then acts. The cognitive radio monitors the available spectral bands, captures
the information or data provided from these bands, and detects the spectrum holes. It focusses on
the frequencies usage and the mode identification. The cognitive users are the unlicensed users
who need to keep monitoring the spectrum. They usually seek to detect the presence of licensed
or the primary users. There are a number of merits associated with the use of cooperation in
cognitive radio. This paper looks at the implementation and testing of the cooperative cognitive
spectrum sensing within a network. The merits that stand out the in the cooperative spectrum
sensing in a cognitive radio network are the reduction of detection time and the increased agility.
The cognitive users are involved in the implementation using the proposed practical algorithm
which allows cooperation in random networks.
The cognitive radio is an advancement of the software defined radio which seeks to
achieve the significant improvements over services offered by the current wireless networks. The
cognitive users also utilize the license band which must detect the presence of licensed users in a
very short time and must vacate the band for the primary users. This paper seeks to find out how
the cognitive users sense the primary users within a given mobile network. The cognitive
spectrum sensing techniques are totally based on opportunistic spectrum sharing. The new
technology does not really rely on the license-based spectrum allocation trends as provided by
the Federal Communication Commission. The FCC provides a license to the service provider for
the SP to have authorized access to the spectrum in the defined range. Some of the service
providers do not fully utilize the spectrum leading to scarcity of the Radio Frequency spectrum.
Researchers have been quite involved in finding a newer model of the spectrum sharing
considering the frequency spectrum is a scarce resource that is required by many people. An
alternative of the cognitive radio in the spectrum sharing strategy is the ultra-wideband. The
cognitive radio is preferred over UWB as it achieves a more efficient spectrum utilization by
finding empty frequency bands unlike UWB which achieves spectrum sharing by overlaying
existing narrowband systems. The technology has the ability to unlock the hidden or unused

spectrum which may be useful for deployment of the next LTE data rate systems. One of the
newest advancement in the design of improved cognitive radio is the available resource map
which is based on similar operational principles of the conventional cellular networks. The
advancement is a real-time map that of all spectrum usages and it is updated and maintained by
the ME and BSS systems in a mobile communication network. The cognitive radio is useful in
detecting wireless intrusions and the building software for the radio is 802.11b. The scan ISM
band for different services is used to detect the unknown activity.
LITERATURE REVIEW
The cellular network is comprised of the cell and the mobile switching center. The
public telephone network and internet which could be wired connection. The cell covers a given
geographical region and is comprised of the mobile users, the air interface or the abis interface
and the base station. The base station is referenced in the IEEE 802.11 AP. The mobile switching
center connects the cells to wide area networks and manages the call setups as well as handling
the mobility of the users within the general mobile network. Within the first hop, there are two
techniques for sharing the mobile to Base station radio spectrum. The time domain multiple
access and the frequency domain multiple access are combined to ensure more efficient
communications. The code division multiple access is an alternative to the two as it improves on
the uplink and downlink data rates. The aim of improving the mobile communication
necessitates the mobility of users in the systems. Initially, all the primary users of a given mobile
network would require to be at a telephone booth to make a call but the improvements in the
access of services improved to half duplex on mobile user equipment and later on to full duplex.
The cellular networks are assigned licenses to operate in a given frequency band. The frequency
band, is thereafter, utilized exhaustively to ensure that as many users are accommodated in a
given time span as possible. The primary users of the network are registered on the system in a
resource known as the home location register and in the visitor location register while in transit.
The primary users do not use the system continuously during communication and the
network can be in idle state for a given period of time especially during the off-peak hours. The
cognitive radio takes advantage of such periods to utilize the unused segments of the signal. The
cognitive users are not licensed users hence any action or attempt to access the system while the

system is in use by the primary users may be considered a breach of privacy or a threat to the
primary users licensed network. The alternative way to utilize the network is to have the
cognitive users listen on in the network so that they can know when to use the unused frequency.
The network should equally have systems that check if the system has unused frequencies which
it can share with the cognitive users to ensure more effectiveness in the use of the frequency
band allocated to the users.
SPECTRUM SENSING
Spectrum sensing is the main enabling functionality in the Cognitive radio technology as
it is very sensitive to limit the unwanted interference. Wireless communication system design
needs higher data rates, larger channel capacity, and improved quality of service to meet the
needs of the consumers who are increasing by the day. The spectrum utilization efficiency helps
to meet the needs of the wireless users. The security issues surrounding wireless connections or
communication systems have drawn a large following as it is considered to have an open-air
nature. The frequency band is a limited resource that needs to be shared among many users.
According to statistics performed in the U.S., the utilization rate of the licensed spectrum stands
at 15-85 percent regardless of the time or location. The spectrum sensing cognitive radio detects
and utilizes unused spectrum for the non-invasive opportunistic channel access. Some of the
applications are the emergency network solutions, vehicular communications, and causes an
increase in transmission rates and distances. The cognitive radio technology is motivated by the
spectrum access and scarcity. The cognitive radio technology is a part of wireless
communication where a network or a user flexibility changes its transmitting or receiving
parameters to achieve more efficient communication performance without interfering with
licensing or unlicensed users [1].
Under cognitive radio technology lies the spectrum sensing, spectrum management,
spectrum sharing, and spectrum mobility. Unfortunately, the cognitive radio technology
encounters some caveats as the intrinsic properties of cognitive radio paradigm produce new
threats and challenges to wireless communications. A spectrum hole is a band of frequencies
assigned to a primary user but at a particular time and specific geographical location, the band is
not being utilized by that user. According to Mitola II, the cognitive radio is a radio that employs
model based reasoning to achieve a specified level of competence in radio-related domains.
Under digital systems, the cognitive radio is an intelligent wireless communication system that is

aware of its surrounding environment. It uses the methodology of understanding through a
training and learning process from its surrounding so as to adapt its internal conditions to the
statistical variations in the incoming radio frequency stimuli. The adaptation is aided by making
corresponding changes in certain operating parameters such as the transmit-power, carrier
frequency, and modulation strategy in real-time with two primary aim. The cognitive radio seeks
to provide universal, highly-reliable communication as needed while efficiently utilizing the
scarce radio spectrum. The cognitive radio can co-exist with the legacy wireless systems, uses
their spectrum resources, and does not interfere with them.
Spectrum sensing in cognitive radios seeks to obtain awareness about the spectrum usage
and existence of primary users in a geographical area. A classical signal detection problem where
the channel gain, primary signal and noise are taken into account when tackling the problem. The
software defined radio, SDR, primarily defined in software form which supports a broad range of
frequencies and its initial configurations can be modified for user requirements. The SDR tend to
be easily reconfigurable, easy to upgrade, have lower maintenance costs, and responds to the
changes in the operating environment. The cognitive radio is a combination of intelligence and
software defined radio. It is denoted as,
x ( t ) = { n ( t )
hs ( t ) +n ( t )
H o
H 1
There are several spectrum sensing methods which use transmitter detection, cooperative
detection, and interference temperature detection. The transmitter detection is achieved using the
matched filter detection, energy detection, or cyclisation detection techniques. The use of
multiantenna system model sends a single PU signal to detect and it does not require the TX
signal or noise variance knowledge. The spectrum sensing problem is formulated according to
simple binary hypothesis test. Under the transmitter detection, some detection techniques are
used to achieve the spectrum sensing required in cognitive radio technology. The matched filter
detection technique has better detection performance compared to other detection techniques and
less time to achieve processing gain. The matched filter detection, however, requires pilots and
preambles or synchronized messages. The procedure used in the matched filter detection is as
illustrated below,