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CHAPTER 1

INTRODUCTION

The enduring growth of wireless digital communications, as well as the increasing

number of wireless users, has raised the spectrum shortage in the last decade. With

this growth, the accessibility of high quality wireless communication spectrum

becomes severely inadequate [1]. Inflexible spectrum management approach

implemented by the government regulatory agencies in assigning specified frequency

band and allowed operator to strictly bind within the band. This approach is termed as

fixed spectrum allocation scheme. Most of the prime radio spectrum is assigned

exclusively for existing services and applications. So it is becoming very hard to find

empty band [2] to deploy new services or enhancing the existing services or providing

services to the new users entering into the existing system. This kind of problem is

severe in metropolitan areas. However, measurements carried out in various countries

shows that most of the radio spectrum is utilized inefficiently. In fact, the Federal

Communications Commission (FCC), United States of America has reported the

temporal and geographical variations in spectrum utilization in the range of 15% to

85%. Particularly spectrum allocated for Television (TV) bands in India is utilized in

the range of 10% to 50% that varies from one geographical area to other [3].

Therefore the real problem is not spectrum scarcity but inefficient spectrum allocation

and usage. This is due to

Fixed spectrum allocation for applications

Firm regulations

Rigid radio functions and

Restricted network conditions

1.1 India’s National Frequency Allocation Plan

The National Frequency Allocation Plan (NFAP) outline the basis for

development of wireless equipment and spectrum utilization in the country

[4, 5]. Frequency bands allocated to various types of radio services in India are

as follows:

1 - 87.5 MHz is used for marine and aeronautical navigation, short and

medium wave radio, amateur (Ham) radio and cordless phones.

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87.5 - 108 MHz is used for FM radio broadcasts.

109-173MHz used for Satellite communication, aeronautical

navigation and outdoor broadcast vehicles.

174 - 230 MHz not allocated.

230 - 450 MHz used for Satellite communication, aeronautical

navigation and outdoor broadcast vehicles.

450- 585 MHz is not allocated.

585-698 MHz is used for TV broadcast.

698-806 MHz not allocated.

806-960 MHz is used by GSM and CDMA mobile services.

960-1710 MHz is used for Aeronautical and space

1710- 1930 MHz is used for GSM mobile services.

1930-2010 MHz is used by defence forces.

2010-2025 MHz is not allocated.

2025-2110 MHz is used for Satellite and space communications.

2110-2170 MHz is not allocated.

2170-2300 MHz is used for Satellite and space communications.

2300-2400 MHz is not allocated.

2400- 2483.5 MHz used for Wi-Fi and Bluetooth short range services.

2483.5-3300 MHz Space communications.

3300-3600 MHz not allocated.

3600-10000 MHz Space research, radio navigation.

10000 MHz used for satellite downlink for broadcast and DTH

services.

From the above plan, it is clear that the spectrum is not utilized completely. That is

the reason why Joseph Mitola coined cognitive radio technology [1]. The static

frequency band allocation scheme currently followed cannot accommodate the latest

requirements of band headed for development of applications and addition of users in

the existing services.

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1.2 Growth of Mobile Services and Users in India

India has the fastest growing telecom network in the world with its high population

and development potential. The major operators in India are BSNL, Airtel, Vodafone,

Idea, Uninor, Reliance, Tata docomo, Aircel, Tata Indicom and MTNL. However,

rural India stills lacks strong infrastructure. India's public sector telecom

company BSNL is the 7th largest telecom company in world.

Table 1.1 provides the details of mobile network operators of India and technologies

used by them. This table also gives information on subscribers in India for various

operators till mentioned period.

Table 1.1: Mobile network operators of India

Operator's Name Technology Subscribers in crores

Bharti Airtel GSM, EDGE HSPA+, TD-LTE

22.97 (May 2015)

Idea Cellular GSM, EDGE, HSPA+ 21.15 (May 2015)

Reliance Communications

CDMA2000,EVDO, GSM, EDGE,HSDPA,

HSPA+, WiMAX 13.4 (September 2014)

BSNL GSM, EDGE, HSDPA, HSPA+, CDMA2000

EVDO, WiMAX, WiFi 8.67 (September 2014)

Aircel GSM, EDGE HSDPA, TD-LTE

7.58 (September 2014)

Tata Docomo CDMA2000, EVDO, GSM, EDGE, HSPA+

6.42 (September 2014)

MTS India CDMA2000, EVDO 0.91 (September 2014)

MTNL GSM, HSDPA, CDMA2000

0.33 (September 2014)

In addition to voice services the major value added services provided by the various

operators in India are:

Data

Mobile TV & OTT Services

Ring Back Tone

Music Tracks Play, download and Ring Tones

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Sports, Information and Entertainment Services

Location Based Services

Missed Call Alerts and Voice Mail Box

Online Gaming

Live Streaming

Devotional Applications

Mobile Money & M-commerce based services

Mobile Advertisements

Contests & Voting

Phone Backup and Security Services

Outbound Dialer Services

WAP content downloads

Utility Services

Stickering

Table 1.2 illustrates the addition of mobile subscriber for various operators in India

since January 2002 [9]. This survey was conducted by a private agency with the help

of Department of Telecommunications, India.

Table 1.2: Monthly and annual mobile subscriber additions

Year Average Monthly Additions

(in millions) Annual Additions

(in millions)

2002 0.44 5.23

2003 1.46 17.49

2004 1.62 19.49

2005 2.32 27.86

2006 5.35 64.14

2007 7.11 85.27

2008 9.44 113.26

2009 14.85 178.25

2010 18.93 227.12

2011 11.80 148.32

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Another survey was conducted during November 2014 by the Department of

Telecommunication. The details of the survey are shown in Fig. 1.1. The mobile user

additions are very high in urban areas rather than rural areas. The graph shows there

was an exponential growth during 2012 to 2013.

Fig. 1.1: Mobile user growth chart in India

1.3 White Spaces

White spaces refers to portions of licensed radio spectrum that do not use all of the

time or in all geographical locations. The other name for white spaces is spectrum

holes. Fig.1.2 shows the white spaces in time and frequency domain.

Fig. 1.2: White Spaces in time and frequency domain

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1.3.1 TV White Spaces in India

The white spaces in the TV spectrum are located in VHF (54-216 MHz) and

UHF (470-698 MHz) bands which has characteristics that make it highly desirable for

wireless communications. Presently, some channels are being also used for other

services in sharing with broadcasting services.

The frequency allocated for TV broadcasting in very high frequency (VHF) and ultra

high frequency (UHF) bands are shown below.

Freq. 54 72 76 88 108 174 216 470 698 (MHz)

Almost 50% of the band is unoccupied and whereas the occupied band is also not

utilizing all the time in all geographical areas. Doordarshan is the only terrestrial TV

broadcaster in India with 7MHz Radio Frequency (RF) bandwidth in VHF & 8MHz

in UHF. More than 30 carriers have been assigned to Doordarshan. Except metros,

transmission is still analog. BSNL, MTNL and Reliance Communication are the

major mobile TV operators in India [3]. Government of India has taken a step to

switch the analog transmissions to digital in four phases.

For this work, the White spaces data in India is collected from IITB, Mumbai during

16-17 December, 2012. The data was focused on TV bands VHF & UHF, FM

broadcasting, De-licensed bands and ISM bands. The data was provided by Dr. Ashok

Chandra, Wireless Advisor, The Wireless Planning and Coordination (WPC),

Ministry of Telecommunications, Government of India [111].

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1.3.2 Other White Spaces in India

Other than TV broadcasting, there are FM and digital audio broadcasting in India. The

frequency allocation for these broadcasting is as follows:

FM Broadcasting: 91.5-95 MHz.

Private FM Broadcasting: 88 – 100 MHz and 103.8 – 108 MHz.

Digital Audio Broadcasting: 174 – 230 MHz.

Digital broadcasting services: 585 – 698 MHz.

1.3.3 De-licensed Bands in India

In India, there are some bands neither licensed nor unlicensed. These bands are

reserved for special applications are strictly restricted for sharing with other services.

The frequency allocations of such bands are given below:

Low power RF devices: 13.553- 13.567 MHz.

Wireless equipment (Effective Radiated Power- 5 W): 26.957- 27.283 MHz.

Medical wireless devices (Power - 25 mW): 402-405 MHz.

Low power short range (10 mW, BW=10 KHz): 433-434 MHz.

Low power cordless telephone system: 926-926.5 MHz.

1.3.4 Un-licensed Bands in India

The Industrial, Scientific and Medical (ISM) radio bands are reserved internationally

for the use of radio frequency energy for industrial, scientific and medical purposes

other than commercial telecommunications. The details of frequencies allocated and

bandwidth available for ISM bands are specified in Table 1.3.

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Table1.3: ISM Frequency bands

Frequency range Bandwidth Center frequency

6.765 MHz 6.795 MHz 30 kHz 6.78 MHz

13.553 MHz 13.567 MHz 14 kHz 13.56 MHz

26.957 MHz 27.283 MHz 326 kHz 27.12 MHz

40.66 MHz 40.7 MHz 40 kHz 40.68 MHz

433.05 MHz 434.79 MHz 1.74 MHz 433.92 MHz

902 MHz 928 MHz 26 MHz 915 MHz

2.4 GHz 2.5 GHz 100 MHz 2.45 GHz

5.725 GHz 5.875 GHz 150 MHz 5.8 GHz

24 GHz 24.25 GHz 250 MHz 24.125 GHz

61 GHz 61.5 GHz 500 MHz 61.25 GHz

122 GHz 123 GHz 1 GHz 122.5 GHz

244 GHz 246 GHz 2 GHz 245 GHz

1.4 Cognitive Radio Technology

Realizing the truth that the licensed bands are underutilized most of the time, FCC

proposed a novel solution called Cognitive Radio Technology to overcome this

problem by allowing an opportunistic utilization of unused licensed spectrum

resources by the unlicensed users, which are referred to as secondary users. The

unused licensed spectrum or band is commonly referred as White Spaces or Spectrum

Holes. This is a paradigm shift on spectrum allocation policy towards the adoption of

unlicensed, rule based strategies for convinced bands of frequency.

Cognitive radio is a radio or system that senses its operational electromagnetic

environment and can dynamically and autonomously regulate its radio operating

parameters to modify interference, facilitate interoperability, and access secondary

markets. In this a licensed user named primary user or legacy user who is the legal

user has higher rights on that spectrum band [6, 7]. On the other hand, unlicensed user

named secondary user with lower priority is called cognitive user can access spectral

resources of PU when it is found idle (white space) with a condition that it has to

vacate that band as soon as PU arrive to active mode with very low interference. Such

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access is called Dynamic Spectrum Access. Even a SU can opportunistically utilize

different spectrum holes corresponding to different Pus in order to satisfy its

bandwidth requirement without causing interference to the PUs.

Spectrum Sensing is the key enabler for DSA in Cognitive radios. It obtains the

awareness of radio spectrum and identifies the unused spectrum. It enables the SUs to

search and make use of the white spaces.

As an enabling technology for DSA, the ultimate objective of the cognitive radio is to

efficiently utilize the available spectrum through cognitive capability and

reconfigurability. These characteristics of CR can be defined as [8]:

Cognitive Capability: Through real-time interaction with the radio

environment, the spectrum holes at a specific time or location can be

identified. The tasks required for adaptive operation in open spectrum are

[8, 9]:

Spectrum sensing: Determine which portions of the spectrum are available

for transmission and detect the presence of licensed users when a CR user

operates in a licensed band by estimating the interference levels of the

radio environment.

Spectrum analysis: Includes the estimation of channel state information

(CSI); and the prediction of channel capacity for use by the CR

transmitter.

Spectrum decision: a CR determines the data rate, the transmission mode

and the bandwidth of the transmission. The appropriate spectrum band is

then chosen according to the spectrum characteristics and user's

requirements.

Reconfigurability: A CR can be programmed to transmit and receive on a

variety of frequencies and using different access technologies supported by its

hardware design. There are several reconfigurable parameters that can be

incorporated into the CR such as operating frequency, modulation, signal

transmission power and communication technology. According to the

spectrum characteristics, these parameters can be reconfigured such that the

CR is switched to a different spectrum band. Therefore the transmitter and

receiver parameters are reconfigured with the appropriate communication

protocol and modulation schemes.

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If spectrum sensing is done by an individual SU then it is called as Single User

Sensing or Local Detection. Local detection becomes complicated in challenging

propagation environments like

Multipath fading

Doppler spread and

Shadowing

With above scenario, it is difficult to distinguish between white space (PU absence)

and deep fade (PU presence but unable to detect). Fading, in particular shadowing

results in the hidden node problem, where one node in the network may not be able to

sense a TV signal within TV signal protection region which is shown in Fig. 1.3. If a

Consumer Premise Equipment (CPE) initiates transmission using the channel, it will

cause interference to the TV receiver.

Fig. 1.3: CPE can cause interference to TV receiver within TV service contour when CPE fails to

detect TV signal due to shadowing.

To overcome the hidden node problem, the network may utilize the results of

spectrum sensing from multiple CPEs in order to make a reliable decision as to

whether the network is inside or outside the TV protection contour. Thus, multiple

user sensing would be more effective in solving the hidden node problem.

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1.5 Cooperative Spectrum Sensing

The limitations of single user sensing are overcome with cooperative spectrum

sensing (CSS). In this a group of secondary users are involved in sensing the spectrum

for making a combined decision to detect the presence of a PU. It helps to mitigate the

effects of multipath fading and shadowing. The sensing performance is improved by

exploiting the spatial diversity in the observations of spatially located CR users. The

probability of all the users in challenging environment like multipath fading, Doppler

spread and shadowing are negligible. The CR users share information using

centralized approach. A central entity called Fusion Centre coordinate and assists all

SUs to perform individual spectrum sensing and reporting to it. It takes decision that

which user has to sense which frequency band. After sensing, the local decision is

sent to FC. At FC all local decisions are combined and finally determine the status of

presence of PU based on fusion rule.

In the geolocation method, a centralized database is maintained where PUs register

the data related to coverage area; transmit power and duration of transmission. Then

SUs are allowed to access the database to determine the availability of white spaces in

different geographical locations. In the beacon method, a beacon signal is

continuously transmitted by the primary in a fixed frequency which is treated as

control signal stating that white space of the TV band. The secondary users receives

control signal while sensing then start utilizing the TV band in that particular

geographical area.

The above two methods are not reliable because dedicated standardized channel is

needed to broadcast the beacons. Modification to the current licensed systems and

their deployment is costly. Additional connectivity is needed to access database. If

modification in the functionality of PU changes the database has to be update

immediately in every geographical area to avoid interference. In spectrum sensing

method, SUs as an individual, detects the presence of PU signal by utilizing partial

band of TV spectrum. It requires low infrastructure cost and it is more compatible

with the network infrastructure. Chapter 2 provides detailed overview of all the

methods available in the literature.

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The FCC has already articulated its interest in permitting unlicensed access to white

spaces in TV spectrum. An example to CR based DSA network in commercial sector

is IEEE 802.22 WRAN (Wireless Regional Area Network) [11] which is the first

worldwide effort to define a novel common air interface standard based on CR.The

IEEE 802.22 WRAN utilizes the unused TV spectrum for its operational band. TV

spectrum is attractive because of its deterministic channel allocation and excellent

radio propagation characteristics [12] and their relatively predictable spatio-temporal

usage characteristics. In addition, the TV bands are heavily underutilized; most TV

channels are unoccupied most of the time. The methods employ to identify the white

spaces are geolocation combined with access to database, beacons, spectrum sensing

or a combination of any of those methods.

1.6 Motivation for the Work

Inefficient spectrum utilization is the motivating force behind cognitive radio and

adopting CR technology to address the spectrum scarcity problem in terms of better

utilization of the spectrum resources. The cognitive radio presents a very productive

area of the research field. Spectrum Sensing examine the frequency spectrum for

empty bands forms the foremost part of the cognitive radio. There are number of

schemes for spectrum sensing like Energy detector, Cyclostationary and Matched

filter. But they require prior knowledge of PU except in energy detector.

Previous works on CSS rely a lot on the idea of sequential spectrum sensing in which

multiple secondary users cooperate to sense a single channel in each sensing period.

However, this traditional cooperative sensing technique [13] may limit the overall

sensing efficiency, which refers to the number of channels or spectrum access

opportunities that can be discovered in each sensing period. Therefore, it is important

to investigate other cooperative sensing techniques that can enhance the sensing

efficiency by simultaneously detecting multiple distinct channels within each sensing

period. This enhancement can result in higher opportunistic throughput for secondary

users.

In co-operative sensing, number of users lead to more overhead [6] and thus takes

time for final decision. Lowering the detection threshold increases the detection as

well as the chances of false detection. Thus one cannot lower the threshold value. This

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work presents an algorithm for finding an optimal number of users and a couple of

threshold optimization schemes.

The cyclostationary detection method is considered without prior knowledge of

primary user called blind approach [14] at very low Signal-to-Noise Ratio (SNR) for

better performance of detection probability with various peak detection techniques

which discriminate signal from noise. The performances of the proposed schemes are

studied using analytical methods and extensive MATLAB simulations.

1.7 Objectives

It is proposed to use the energy and cyclostationary detection techniques for

sensing the spectrum without prior knowledge of primary user.

To develop undemanding and computationally efficient sensing algorithm

which overcome the drawbacks of techniques proposed in literatures.

To improve the performance, the number of cognitive radio user’s decisions is

optimized for determining the presence or absence of primary user.

Proper time bandwidth product is proposed for better performance of sensing

with less sensing duration.

It is proposed to determine the best threshold fixing in determine the

probability of detection.

To realize and implement various peak detection techniques after evaluating

cyclic domain profile for phase modulation signal to determine the primary

user status of presence or absence at low SNRs.

The conventional and proposed methods of spectrum sensing will be

compared with the performance metrics: probability of detection, detection

threshold and optimal number of cognitive users.

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1.8 Organization of the Thesis

The entire thesis is organized into six chapters and the contents dealt with are as

follows:

Chapter 1: It deals with the introduction, necessity, motivation and objectives of thesis

work.

Chapter 2: This chapter describes the literature review in the area of Cooperative

spectrum sensing in cognitive radio networks and also provides white

spaces in Indian TV spectrum.

Chapter 3: In this chapter, the Energy detection technique is employed which optimize

the number of cognitive radios involved in cooperative spectrum sensing.

The optimal decision voting rule is chosen to minimize the total error

probability. The performance of the detection is improved by adapting

gradient descent algorithm.

Chapter 4: This chapter explains the signal detection technique subject to a constraint

on the global probability of false alarm and detection. Two models are

formulated. First model is an Energy efficient setup which determines the

minimum number of cognitive radios that satisfies the global probabilities.

Second model Throughput enhancement setup where the throughput of the

cognitive radio network is maximized with optimal number of CR users

and sensing duration.

Chapter 5: This chapter proposes Cyclostationary signal detection techniques without

prior knowledge using peak factor of cycle frequency domain profile or

cyclic domain profile (CDP). The performance is evaluated for the

Absolute Threshold, Standard Deviation and Filtfilt techniques to show the

superiority in terms of probability of detection.

Chapter 6: Summary, conclusions of the research work and scope for future work is

discussed in this chapter.