CHAPTER 1 INTRODUCTION

Transcription

1 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: MHz is used for marine and aeronautical navigation, short and medium wave radio, amateur (Ham) radio and cordless phones. 1

2 MHz is used for FM radio broadcasts MHz used for Satellite communication, aeronautical navigation and outdoor broadcast vehicles MHz not allocated MHz used for Satellite communication, aeronautical navigation and outdoor broadcast vehicles MHz is not allocated MHz is used for TV broadcast MHz not allocated MHz is used by GSM and CDMA mobile services MHz is used for Aeronautical and space MHz is used for GSM mobile services MHz is used by defence forces MHz is not allocated MHz is used for Satellite and space communications MHz is not allocated MHz is used for Satellite and space communications MHz is not allocated MHz used for Wi-Fi and Bluetooth short range services MHz Space communications MHz not allocated MHz Space research, radio navigation 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. 2

3 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 7 th 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 (May 2015) Idea Cellular GSM, EDGE, HSPA (May 2015) Reliance Communications BSNL Aircel Tata Docomo CDMA2000,EVDO, GSM, EDGE,HSDPA, HSPA+, WiMAX GSM, EDGE, HSDPA, HSPA+, CDMA2000 EVDO, WiMAX, WiFi GSM, EDGE HSDPA, TD-LTE CDMA2000, EVDO, GSM, EDGE, HSPA (September 2014) 8.67 (September 2014) 7.58 (September 2014) 6.42 (September 2014) MTS India CDMA2000, EVDO 0.91 (September 2014) MTNL GSM, HSDPA, CDMA (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 3

4 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)

5 Another survey was conducted during November 2014 by the Department of Telecommunication. The details of the survey are shown in Fig 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 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 5

6 1.3.1 TV White Spaces in India The white spaces in the TV spectrum are located in VHF ( MHz) and UHF ( 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 (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 December, 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]. 6

7 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: MHz. Private FM Broadcasting: MHz and MHz. Digital Audio Broadcasting: MHz. Digital broadcasting services: MHz 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: MHz. Wireless equipment (Effective Radiated Power- 5 W): MHz. Medical wireless devices (Power - 25 mw): MHz. Low power short range (10 mw, BW=10 KHz): MHz. Low power cordless telephone system: MHz 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

8 Table1.3: ISM Frequency bands Frequency range Bandwidth Center frequency MHz MHz 30 khz 6.78 MHz MHz MHz 14 khz MHz MHz MHz 326 khz MHz MHz 40.7 MHz 40 khz MHz MHz MHz 1.74 MHz MHz 902 MHz 928 MHz 26 MHz 915 MHz 2.4 GHz 2.5 GHz 100 MHz 2.45 GHz GHz GHz 150 MHz 5.8 GHz 24 GHz GHz 250 MHz GHz 61 GHz 61.5 GHz 500 MHz GHz 122 GHz 123 GHz 1 GHz 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 8

9 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. 9

10 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 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. 10

11 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. 11

12 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 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 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 12

13 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. 13

14 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: Chapter 3: 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. 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: Chapter 5: 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. 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. 14