TRIBHUVAN UNIVERSITY INSTITUTE OF ENGINEERING PULCHOWK CAMPUS

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1 TRIBHUVAN UNIVERSITY INSTITUTE OF ENGINEERING PULCHOWK CAMPUS THESIS NO.: 069/MSICE/610 DYNAMIC SPECTRUM CO-ACCESS (DSCA) WITH DIRTY PAPER CODING (DPC) FOR COGNITIVE RADIO NETWORK BY NASHIB ACHARYA A THESIS SUBMITTED TO THE DEPARTMENT OF ELECTRONICS AND COMPUTER ENGINEERING IN PARTIAL FULFILMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE IN INFORMATION AND COMMUNICATION ENGINEERING DEPARTMENT OF ELECTRONICS AND COMPUTER ENGINEERING November 2014

2 DYNAMIC SPECTRUM CO-ACCESS (DSCA) WITH DIRTY PAPER CODING (DPC) FOR COGNITIVE RADIO NETWORK Submitted By: Nashib Acharya (069/MSICE/610) Thesis Supervisor Dr. Nanda Bikram Adhikari A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science in Information and Communication Engineering Department of Electronics and Computer Engineering Institute of Engineering, Pulchowk Campus Tribhuvan University Lalitpur, Nepal November 2014

3 ACKNOWLEDGEMENT I am very much thankful to the Department of Electronics and Computer Engineering, IOE, Pulchowk campus for providing the opportunity for presenting myself with this Thesis entitled Dynamic Spectrum Co-Access (DSCA) With Dirty Paper Coding (DPC) For Cognitive Radio Network I express my deepest appreciation to my thesis supervisor Dr. Nanda Bikram Adhikari, who has the attitude and the substance of a genius. I am very thankful for his expert guidance, suggestions and coordination. Without his guidance and persistent help this dissertation would not have been possible. I would like to express special thanks of gratitude to the Head of Department of Electronics and Computer Engineering, IOE, Pulchowk Campus, Assistant Professor Dr. Dibakar Raj Pant, for his guidance and support. I am very grateful to our Program Coordinator of Masters of Science in Electronics and Communication Engineering, Assistant Professor, Mr. Surendra Shrestha for his kind support and valuable coordination. It would be injustice without acknowledging our Former Program Coordinator of Masters of Science in Electronics and Communication Engineering and Vice Campus Chief,Assistant Professor, Mr. Sharad Kumar Ghimire for his precious coordination. I would like to express my gratitude to all the Professors and Teachers of Institute of Engineering (IOE) who have helped and guided me directly or indirectly. Finally, I would like to thank all the faculty member of Kathford International College of Engineering and Management, friends and colleagues of MSICE for their precious encouragement and support. i

4 ABSTRACT In the current architecture of dynamic spectrum access, which is also known as opportunistic spectrum access, secondary users only opportunistically access the spectrum of primary users. The resurgence of primary users disrupts on going communication of secondary users, which can result in poor performance for secondary users. In this thesis, an architecture for dynamic spectrum access, termed Dynamic Spectrum Co-Access (DSCA), is implemented to enable the primary user and the secondary user to simultaneously access licensed spectrum. With DSCA, secondary users transparently incentivize primary users through increasing the primary user performance, so that secondary users can access spectrum simultaneously with primary users; hence there is no disruption to secondary communications due to the resurgence of primary users. A mathematical model is formulated to calculate the minimum incentives for the spectrum co-access between the primary user and the secondary user, and the region of co-access is computed to determine the secondary users that can co-access with a given primary user. 900 Mhz band is used for the study purpose, especially for the power allocation of the secondary user. Special pre coding techniques called Dirty Paper Coding (DPC) is used to preserve signal over the interference for secondary network. A mathematical model is formulated to determine the minimum incentives for the spectrum co-access, computational analysis of region of co-access is done to determine where the secondary users can co-access with a given primary user. Keywords: Dynamic spectrum Co-Access; simultaneous access of spectrum; cognitive radio network; resurgence; disruption. ii

5 RECOMMENDATION The undersigned certify that they have read and recommended to the Department of Electronics and Computer Engineering for acceptance, a thesis entitled Dynamic Spectrum Co-Access (DSCA) With Dirty Paper Coding (DPC) For Cognitive Radio Network, submitted by Nashib Acharya in partial fulfillment of the requirement for the award of the degree of Master of Science in Information and Communication Engineering. Supervisor: Dr. Nanda Bikram Adhikari Assistant Professor Department of Electronics and Computer Engineering Institute of Engineering Pulchowk campus iii

6 TABLE OF CONTENTS ACKNOWLEDGEMENT..i ABSTRACT..ii RECOMMENDATION iii TABLE OF CONTENTS..iv LIST OF FIGURES... v LIST OF TABLES...vii ABBREVIATIONS viii CHAPTER 1: INTRODUCTION Background Problem Statement Objectives..5 CHAPTER 2: LITERATURE REVIEW...6 CHAPTER 3: RELATED THEORY Existing Cognitive Network Paradigm Interweave paradigm Underlay paradigm Overlay paradigm Interference Channel: An Overview Dynamic Spectrum Co-Access Co-Access Encoding Techniques...14 CHAPTER 4: RESEARCH METHODOLOGY.15 iv

7 4.1 One PU Node Pair and One SU Node Pair At PU transmitter At SU transmitter At PU receiver At SU receiver Co Access Incentive Acceptable SU SINR Region of Co-Access...22 CHAPTER 5: SIMULATION RESULTS AND INTERPRETATION Simulation Parameters Achievable Rates Region of Co-Access...30 CHAPTER 6: EPILOGUE Limitations Future Enhancements Schedule Conclusions..34 CHAPTER 7: REFERENCES 35 v

8 LIST OF FIGURES Figure 1.1 Basic Cognitive Cycle.3 Figure 3.1 Conceptual illustration to show interference channel.13 Figure 3.2 An incentivized co-access architecture...14 Figure 4.1 Basic Incentivized Architecture with a PU and a SU node pair. 16 Figure 4.2 Architecture to determine region of co-access consisting three PU node and a SU node Figure 5.1 Plot of maximum achievable PU rate with increasing γ while PU transmitting 5 watt and SU transmitting 7 watt Figure 5. 2 Plot of maximum achievable SU rate with increasing γ while PU transmitting 5 watt and SU transmitting 7 watt Figure 5.3 Figure showing the comparative change in maximum achievable rate of PU and SU with change in γ Figure 5.4 Effect of change in transmit power level of SU on maximum achievable rate of SU network Figure 5.5 Effect of change in transmit power level of SU on maximum achievable rate of PU network Figure 5.6: Region of co-access where SU can located between any two PU node 31 vi

9 LIST OF TABLES Table 4.1: Major notations used to formulate the mathematical model...18 Table 5.1: Table showing values of transmit power level of base station in dbm and watt for GSM Table 6.1: Time schedule.33 vii

10 LISTS OF ABBREVIATIONS CRN DPC DSA DSCA FCC GSM PU QoS SU SINR SNR TV UHF VHF Cognitive Radio Network Dirty Paper Coding Dynamic Spectrum Access Dynamic Spectrum Co-Access Federal Communication Commission Global System of Mobile Primary User Quality of Service Secondary User Signal to interference Plus Noise Ratio Signal to Noise Power Ratio Television Ultra High Frequency Very High Frequency viii

11 CHAPTER ONE INTRODUCTION 1

12 1.1 Background Broadcasting is done through Radio. Thus, large number of users coexists in same frequency band which interfere each other. As numbers of users increased exponentially over last few decades, the availability of spectrum becomes severely constraint. This shows that almost all the frequency bands have been assigned. On the other hand, user demands are increasing exponentially. Thus, it is obvious that the availability of the spectrum becomes severely constraint. In recent years, significant effort has been applied to better utilize the wireless communications spectrum. The existing model for spectrum allocation by FCC has been to give licenses for the major part of usable spectrum to the commercial licensed user and named them as primary user. The purpose of these unlicensed bands is to encourage innovation without the high cost to entry associated with purchasing licensed spectrum through auctions. The unlicensed bands have been proven a great vehicle for innovation, and the 2.4 GHz unlicensed band currently host systems such as Bluetooth, b/g/n Wi-Fi, and cordless phones. Unfortunately, the unlicensed bands can be killed by their own success, since the more devices that occupy these bands, the more interference they cause to each other. As PU pay for the spectrum, the total right over this spectrum will be of PU. However, many studies have shown that a large portion of licensed spectrum is underutilized. There exist abundant spectrum opportunities in the temporal, spatial, and frequency domains. The exploitation of these spectrum opportunities is currently an area of significant research known as DSA or CRN. Researchers consider cognitive radio as the best solution for the problem of spectrum scarcity, since a large portion of spectrum in the UHF/VHF bands are becoming available on a geographical basis after analog to digital TV switchover [1]. There exist very little new bandwidth available for emerging wireless products and services. Cognitive radio is born as the idea to solve this spectrum scarcity problem. As stated by Andrea Goldsmith, Syed Ali Jafar and 2

13 Ivana Maric, A cognitive radio is a wireless communication system that intelligently utilizes any available side information about the (a) activity, (b) channel conditions, (c) codebooks or (d) messages of other nodes with which it shares the spectrum. This is the most famous and widely proposed cognitive radio cycle. However, it is the concept which is basically used in opportunistic cognition. The CR devices will utilize advanced radio and signal processing technology along with new spectrum allocation policies to support new users in existing crowded spectrum without degrading the QoS of the existing users of the spectrum. A CR must pose advanced sensing and processing capabilities Thus CR needs the intelligence software which can sense, gather and process all the information about the spectrum that exists around it [2]. Thus CR is a concept that allows wireless system to sense the environment, adapt, and learn from previous experience to improve the communication quality. Figure 1.1 Basic Cognitive Cycle In opportunistic spectrum access, SU opportunistically access the licensed spectrum of PU, whereas PUs has privileged access of the licensed band. The 3

14 compulsion to vacate the band immediately by SU after resurgence of primary user traffic in the band made ongoing communication of secondary user to be disrupted. The requirement that Secondary users cannot access spectrum simultaneously with Primary users results in significant overhead on spectrum sensing and spectrum handoff, which in turn results poor performance for cognitive radio networks. In my Thesis, A novel architecture is developed for dynamic spectrum access, called DSCA, which enables SU simultaneously access licensed spectrum with PU through transparently incentivizing PU network. It differs than opportunistic spectrum access in a way that it allows simultaneous access not time based sharing. DPC is incorporated as a precoding technique with cooperative cognitive radio to implement this. It is well understood that PUs are not willing to share their licensed spectrum without incentives. The novelty of DSCA is that the secondary user communication can provide a significant performance improvement to the PUs communication as incentive. Hence PU is incentivized to welcome the co-access of spectrum with SUs [3]. 1.2 Problem Statement Cognitive radio was first born to solve the spectrum scarcity problem, however in existing opportunistic spectrum access as the traffic of primary user reappear in the licensed band, it compels secondary transmitter to terminate its ongoing communication which result very poor quality of service of cognitive network as the resurgence of PU is very obvious and frequent. Following are some of the problem statements that led situation for dissertation to develop. 1. Higher data rate demand of wireless users. 2. The resurgence of primary user in traffic band disrupts ongoing communication of secondary users. 4

15 3. Primary users are not willing to share their spectrum without any incentives. 4. Lack of simultaneous access of spectrum in opportunistic spectrum access architecture. 1.3 Objectives In contrast to opportunistic spectrum access, this thesis aims to implement simultaneous access of PU and SU to the spectrum. The main objectives of this thesis that enables the simultaneous access of spectrum are as follows: 1. To implement incentivized Spectrum access among Primary user and Secondary User. 2. To calculate the achievable rate of both PU and SU while SU Co-Access with PU. 3. To determine the Region of Co-Access where SU can Co-Access with PU. 5

16 CHAPTER TWO LITERATURE REVIEW 6

17 The concept of cognitive radio was first proposed in 1998 in the seminar of Royal Institute of Technology of Stockholm. It describes that if the network is intelligent enough to gather the information about the co-users, then the radio resources can be adaptively changed to meet users need and demand. The cognitive radio is defined as the goal towards software defined radio platform [4]. A lot of researchers have stated in their article that the available white space of the TV band could be increased to 120 MHZ for cognitive users after the analog to digital TV switchover [5]. This shows the possibility of cognitive radio. In the past there have been extensive studies on opportunistic spectrum access architecture and cognitive radio networks. Good general overview of the cognitive radio can be found in [6] and [7]. Different paradigm of the cognitive network is briefly discussed and concluded various aspects of the paradigm which are already mentioned in introduction section. Underlay and Overlay allows concurrent transmission of both primary and secondary user in Along with it, this paper also explain various encoding techniques and error control techniques for the interference cancellation during concurrent transmission. This suggests dirty paper coding as the best candidate for encoding in the cognitive radio network in known interference scenario [2]. The network coding technique is discussed and implemented to incentivize PU to cooperate with SU in spectrum access, so that SUs can access spectrum even when PU is active. Nevertheless, the spectrum access of SUs is not transparent to PUs in this scheme. The PUs must have the knowledge of SUs, and need to listen to the packets from SU [3]. Contrary to the scheme in [3], the spectrum access of SU in DSCA architecture in this thesis is transparent to PUs, i.e. PU does not need to have any knowledge of SU. The DSCA architecture utilizes the DPC technique to achieve transparent incentivizing of PU. DPC was first introduced by Costa as a proof for maintaining SINR at the receiver given the transmitter had prior knowledge of the interference state. It was shown that DPC could achieve the largest known capacity region for cognitive radio networks in a channel model with one PU node pair and one SU node pair, as long as the SU transmitter had a priori knowledge of the PU messages. Several later studies have 7

18 shown that SUs can coexist with PUs without degrading the PU channel capacity.however the success of DPC in a cognitive radio network relies on the SU transmitter having a priori knowledge of the PU transmitted packet [8]. This is a nontrivial problem and there have been several proposed methods for achieving this. In traditional one-hop infrastructure networks the authors proposed using DPC for interference reduction between base stations, by leveraging the high bandwidth of the wired backbone to obtain a priori knowledge of base stations downlink data. However the PU is unlikely to share a wired high-bandwidth backbone with SUs [9]. More importantly, the Dirty Paper Coding have been implemented to cancel the joint interference for the cognitive users. In their architecture primary codebooks are known to the secondary base station and interference cause by the primary base station on the secondary users is canceled using DPC [10]. In this thesis, DSCA for transparent incentivizing of primary user by secondary user has been implemented. PU need not to be aware of existence of secondary user. Moreover, secondary user operate themselves in such a way that it improves the performance of primary user instead of interfering them. This now enables Primary and secondary user to have simultaneous access of the spectrum which significantly reduces the sensing and handoff overhead ensuring the QoS of cognitive radio network. 8

19 CHAPTER THREE RELATED THEORY 9

20 3.1 Existing Cognitive Networks Paradigms There are three main cognitive radio network paradigms: Underlay, Overlay, and Interweave. In interweave paradigm the cognitive radios opportunistically exploit spectral holes to communicate without disrupting other transmission. In contrast to that, the underlay paradigm allows concurrent transmission of primary and secondary users. In underlay, cognitive users are allowed to operate if the interference by them caused to non-cognitive users is below a given threshold i.e. interference temperature is acceptable for primary users. In overlay systems the cognitive users use sophisticated signal processing and coding to maintain or improve the SINR of noncognitive radios while also obtaining some additional bandwidth for their own communications. Underlay and overlay are sometimes also called cooperative cognitive radios Interweave paradigm The interweave Paradigm is based on the principle of opportunistic communication, which was the basic motivation of the cognitive radio. This was born after the study conducted by FCC [11] and industry [12] which showed that the major part of the spectrum is not utilized most of the time. This temporarily exist space time frequency voids, referred as spectrum holes which are sensed and communication is performed using these spectrum holes. This spectrum holes are further conditionally termed as white space. Generally 1 MHz bandwidth available for ten minute, then it is called white space. The nature of spectrum holes will change according to the time and geographic location and thus can be exploited by cognitive users which finally increase the spectrum utilization. This technique requires the knowledge of the side activity of the non-cognitive users. Thus interweave technique can be defined as the intelligence system that detects the occupancy of the spectrum periodically and utilizes the spectrum holes with minimal acceptable interference to the active users or 10

21 primary users. The periodic sensing should be done due to changing nature of the spectrum holes Underlay paradigm In an underlay paradigm, the major motivation of this paradigm is that it allows simultaneous cognitive and non-cognitive communication under the constraints that the cognitive users are assumed to have the knowledge of the interference caused by the cognitive transmitter to the non-cognitive user. So in this paradigm the cognitive user (often called secondary user) cannot significantly interfere with the existing communication device (often called primary user). Being specific, the concurrent non-cognitive and cognitive transmission is allowed only if the interference level caused by secondary user is below the acceptable threshold for the primary user Overlay paradigm Unlike interweave paradigm, it also allows simultaneous transmission in the same frequency band. In an overlay paradigm, the cognitive transmitter is assumed to have knowledge of the non-cognitive users codebooks and its messages as well. This is possible if the uniform standard is followed by the non-cognitive user or they could transmit their codebooks periodically. Knowledge of a non-cognitive user s codebooks and messages can be exploited in various ways to either cancel or mitigate the interference seen at the cognitive and non-cognitive users. On the other part, this information can be used to completely cancel the interference due to non-cognitive signals at the cognitive receiver by various techniques [2]. The cognitive users can utilize the knowledge they have about the non-cognitive communication and use part of their power for their own communication and the remainder of the power to relay the non-cognitive transmission. By careful choice of power split, the increase in the signal to noise ratio power ratio of primary user due to the additional signal from the 11

22 cognitive radio relaying. This increased SINR will guarantees that the interference level created by remaining of the transmit power of cognitive users to non-cognitive receiver does not change the non-cognitive user s rate. This paradigm can be used in both licensed and unlicensed band. In licensed bands, Cognitive users would be allowed to share the band with licensed users since they do not interfere or even might improve their communication. In unlicensed bands cognitive users would enable a higher spectral efficiency by exploiting message and codebook knowledge to reduce interference. Overlay cognitive radio networks allow concurrent cognitive and non-cognitive transmissions, also in contrast to underlay networks; the cognitive transmitter may now facilitate the transmission of non-cognitive user also. Thus, smallest overlay cognitive radio network is a two user (cognitive and non-cognitive) interference channel where the cognitive transmitter has non causal knowledge of the noncognitive user s messages. Knowledge of the non-cognitive user s message allows the cognitive transmitter to apply several encoding schemes that will improve both its own rates as well as the rate of non-cognitive users. Various forms of coordination are possible [2]. 3.2 Interference Channel: An Overview The interference channel model captures scenarios in which multiple terminal pairs wish to communicate simultaneously in the presence of mutual interference. The users are not assumed to be cognitive - they do not monitor the activity or decode messages of other users. However, it is commonly assumed that all terminals know the channel gains and the codebooks of all the encoders. The communication problem is to determine the highest rates that can simultaneously be achieved with arbitrarily small error probability at the desired receivers, i.e., to determine the capacity region. This performance can serve as a benchmark to evaluate the gains of cognition. Even 12

23 for the smallest interference network consisting of two transmitter-receiver pairs, this problem has remained unsolved for more than thirty years, emphasizing that one of the fundamental problems in networks coping with and exploiting interference - is not yet entirely understood. Still, there has been a lot of progress in understanding communication in interference channels [2]. Message W1 T1 Code word X(W1) R1 Estimate of W1 Message W2 Estimate of W2 T2 Code Word X(W1) R2 Figure 3.1: Conceptual illustration to show interference channel 3.3 Dynamic Spectrum Co- Access In DSCA, when PU is not transmitting, SU freely access the spectrum as in opportunistic spectrum access. But, while PU is active, SU provide incentives to Primary for having co-access to the spectrum. Region of interest is of latter case, i.e. how the SU incentivized the Primary user to enable spectrum co-access. The two main points are co-access incentives and region of co-access. Incentives will be in the form of increased performance of primary user. This is done by secondary user by using part of its power to relay the message of the primary user and rest to transmit its own message. The co-access incentives ensure that both PU and SU benefit from coaccess. The region of co-access defines where the SU can co-access with PU. 13

24 Message W1 T1 Code word X (W1) R1 Estimate of W1 Message W2 T2 R2 Estimate of W2 Code X (W1, W2) Figure 3.2: An incentivized co-access architecture 3.4 Co-Access Encoding Techniques Co-access encoding techniques have mostly been investigated for the interference channel with one cognitive encoder, which is also known as basic overlay network. The special case of this co-access model is the basic interference channel i.e. when both user is non-cognitive. An elegant idea of superposition coding [13] allows sending information simultaneously to all users at higher data rates than what can be achieved with time sharing. The DSCA architecture utilizes the DPC technique to achieve transparent incentivizing of PUs. DPC was first introduced by costa as a proof for maintaining SINR at the receiver given that transmitter had prior knowledge of the interference state [8]. DPC allows encoder to pre-code its message at a rate associated with interference-free communication. It is called dirty paper because it is similar to writing in a paper with dirt already (coding in the channel with existing interference). 14

25 CHAPTER FOUR RESEARCH METHODOLOGY 15

26 Dynamic spectrum co-access architecture is developed to enable simultaneous transmission of primary and secondary user. Matlab is used for the simulation purpose. In this section, DSCA architecture is described. With DSCA when PU is not transmitting, SU freely access the spectrum, similarly to the opportunistic spectrum access architecture. On the other hand, when PU is active, SU provide incentives to PU so that simultaneous transmission by SU is allowed. In the following, operation of DSCA in the latter case is focused, i.e., how the SU incentivizes the PU to enable spectrum co-access. The SU allocates the portion of its power to PU and remaining for transmitting its own code word. So PU receiver receives the code word from both PU transmitter as well as SU Transmitter. The power allocation should be done in such a way that PU s SINR should be increased which is termed to be incentivized. At first a simple network with one PU node pair and one SU node pair is considered. Three key components of DSCA is used, Portion of SU power used to relay the PU message, co-access incentives and region of co-access. The co-access incentives ensure that both PUs and SUs are benefit from the spectrum co-access. The region of PU tx 1 b PU tx SU tx a 2 SU tx Figure 4.1: Basic Incentivized Architecture with a PU and a SU node pair co-access is the region where SU can be located to co-access spectrum with PU. Figure 4.1 show the basic architecture of an incentivized network with one SU node 16

27 and one PU node with normalized (1, a, b, 1) channel. The legend on a link indicates the path loss. 4.1 One PU Node Pair And One SU Node Pair In above given basic architecture of incentivized network, let Xp and Xs be the codeword transmitted by PU and SU respectively. (1, a, b, 1) is assumed as a normalized path loss between the links. Assume that SU knows the PU packet priori through a side information path. To provide incentives to the PU, so that the PU allows simultaneous spectrum access for SU, the SU transmitter uses a portion of its power to boost the SINR at the PU receiver. Let γ [0, 1] denote the portion of the SU power used to transmit the PU code word and (1 γ) the portion of power used to transmit its own code word. Let Pp and Ps denote the transmit power of the PU and SU transmitters, respectively. In addition, let Xp and Xs be a single transmitted code word for the PU and SU, respectively. The major notations are listed in Table 4.1. Over a large set of code words, the PU transmit power at the PU transmitter is PP = Xp 2. As it is already mentioned that SU have priori knowledge of PU, the DPC technique is used to form the final codeword That emerge from the SU transmitter which consist codeword of both SU and PU. The SU code word is generated using DPC such that: X s = X s + X p γp s, (4.1) P p where X s is the code word to carry the SU packet and X p γp s P p is the code word to carry the PU packet. For the large set of code word, these code words are chosen in such a way that they are statically independent, if they are not statistically independent then they SU receiver will fail to cancel the interference of the PU. A random bining technique is used for the choosing of these codeword. Table 4.1 shows major notations summary used in this chapter. 17

28 a,b Normalized path losses as shown in figure 4.1 γ Portion of the SU power used to relay the PU code word Pp,Ps Transmit Power of the PU and SU transmitter respectively S P, S S Q p,q s X p, X s X s R p, R s Np, Ns Received codeword by PU and SU receiver respectively Received signal power (excluding interference) at the PU and SU receivers, respectively Transmitted code word of PU and SU transmitters Code word of SU transmitter to carry SU packet Achievable rate of PU and SU respectively Noise plus interference Power at PU and SU Table 4.1: Major notations used to formulate the mathematical model At PU transmitter As stated earlier, this DSCA architecture transparently incentivized the PU i.e. PU don t need to be aware of the existence of SU, so no difference will be seen in the nature of PU transmitter then it was without the SU. So the transmit power of the Primary User can simply be given as: PP = Xp 2 (4.2) At SU transmitter The codeword transmitted by the SU transmitter consist the two code word separately. One its own code word and another to relay the codeword of Primary User for the incentive. This is given by the equation 4.1. So total power transmitted by the SU transmitter is: 18

29 2 Ps = (X s + X p γp s ) P p, (4.3) Ps = X 2 s + 2X X s p γp s + X 2 P p. γp s, (4.4) p P p Ps = X 2 s + γp s, (4.5) [X X s p = 0, they are statically independent] X 2 s = (1- γ) P s. (4.6) At PU receiver The received signal at PU receiver will be the sum of signal transmitted by PU and the sum of code word transmitted by SU. Received code word will be: S p = X p + a (X s + X p γp s ), (4.7) P p S p = (X p + ax p γp s P p ) + ax s. (4.8) Desired Code Noise The total desired signal power can be calculated from the Eq. (4.8) by squaring the desired code word and is given by: Q p = (X p + ax p γp s P p ) 2, (4.9) Q p = (X p + a γp s ) 2, (4.10) [X p = P p ] Q p = ( P P + a γp s ) 2, (4.11) 19

30 where Q p is the total signal power at the PU receiver. At PU receiver, total noise at the receiver will be the addition of normalized gaussian noise 1, and noise due to the secondary transmission. So total noise at PU receiver is given by: Np = (1 + (ax s) 2 (4.12) Where Np is the total noise at the PU receiver. a is path loss, X s is the codeword that carries SU packet. Achievable rate for Primary User can be calculated using the formula R p = log(1 + SINR) (4.13) Using Eq (4.11) and Eq (4.12) we can have above equation as R p = log(1 + ( P P+a γp s ) 2 (1 + (ax s) 2 ) (4.14) This equation can be finally used to determine the achievable rate of the primary user while co-access with secondary user. However the value of γ should be chosen in such a way that SINR of the primary user increases as well as rate of secondary user is satisfactory to them At SU receiver The received signal at SU receiver will be the sum of signal transmitted by SU and the code word transmitted by PU. Received code word will be: S s = X s + X p γp s P p + bx p (4.15) 20

31 The desired codeword is X s and SU receiver non causaully knows that interference to the SU receiver would be X p γp s P p coding is done in such a way that γp s P p + bx p. This is cancelled by DPC i.e will be cancelled by bx p. This is already stated in the paper published in [10] which shows that DPC will be success to cancel the interference. So only the normalized noise remains in SU receiver. Achievable rate can be given as R s = log(1 + SINR), (4.16) R s = log(1 + X 2 s ), (4.17) Using Eq (4.6) in Eq (4.17) we can derive R s = log(1 + (1 γ) P s ). (4.18) This equation can be used to determine the achievable rate of secondary user when SU co-access with the PU. 4.2 Co-Access Incentive Without SU the SINR of the Primary user will be given as SINR = P p /1, (4.19) with SU, changed SINR is given as SINR = ( P P+a γp s ) 2 (1 + (ax s) 2, (4.20) For primary user to be incentivized, 21

32 ( P P +a γp s ) 2 (1 + (ax s) 2 P p + K, (4.21) where K is the PU co-access incentive in terms of increased SINR of the Primary user. After some manipulation in above Equation we can derive γ ( ((P P+K)(1 P P +a 2 P s (P P +K+1))) P s ) a P s ( P p +K+1) 2. (4.22) This Equation can be used to calculate the portion of power to be used to relay for given amount of PU co-access incentive to the PU user. 4.3 Acceptable SU SINR Let λ be the minimum SINR that is desired to be received in SU receiver. Then we can write ((1 γ) P s ) λ (4.23) 4.4 Region Of Co-Access If the PU co-access incentive K is not able to be offered by the SU, then the PU does not allow the SU to co-access the licensed spectrum with it. Therefore it is necessary to be able to find an area within the PU network that if the SU is located within it, it would be able to provide enough incentive for co-access. In contrast to that while calculating region of co-access acceptable SU SINR should also be guaranteed for given γ which is used to incentivize PU by amount K. The figure 4.2 shows the basic architecture to determine the region of co-access. Here three PU s are assumed and PU2 relays the message of PU1 to the PU3. A SU is also intended to 22

33 locate around PU2 such that it increase received SINR of PU3. For this, SU should able to receive the code word from the PU1, Thus s 2 r 2 (4.24) Thus Eq (4.22) explain and finds the value of power split to provide enough incentive to the primary user. So it guarantees that PU3 is incentivized. Eq (4.23) can be used to assure that the rate of SU for above incentivizing is satisfactory to SU or not. Thus combining these constraints in the below mentioned architecture we can find the bound for the region of co-access. PU1 r PU2 a PU3 s SU b Figure 4.2: Architecture to determine region of co-access consisting three PU node and a SU node 23

34 CHAPTER FIVE SIMULATION RESULTS AND INTERPRETATION 24

35 5.1 Simulation Parameters Simulation is done in Matlab version r2013a. It is assumed prior to the simulation that the spectrum sensing portion, obtaining side information has already been done. So this simulation focuses on the achievable rates, incentives rather than sensing of spectrum, since lots of research have been performed in case of spectrum sensing techniques and its optimization. The power level for GSM 900 that is used in this thesis is shown below. Power Level Number Power Output level dbm for 900 MHz Power level in Watt Table 5.1: Table showing values of transmit power level of base station in dbm and watt for GSM 900[14]. 25

36 5.2 Achievable Rates It is well known that achievable rate varies with the portion of SU power that is used to relay the PU packet. So using Eq (4.14) and Eq (4.18) following results is drawn. Figure 5.1 Plot of maximum achievable PU rate with increasing γ while PU transmitting 5 watt and SU transmitting 7 watt. Figure 5.1 show that the variation in Achievable PU rate with increasing γ (power split). when γ =0 (SU does not assist PU), then the rate is very low, it is because the transmission of SU totally act as an interference to the PU so this reduces the achievable rate of PU to large extent. As the value of γ goes on increasing the achievable rate goes on increasing, at certain value of γ, the rate will be more than it was without co-accessing. This scenario is called incentivized. 26

37 Figure 5. 2 Plot of maximum achievable SU rate with increasing γ while PU transmitting 5 watt and SU transmitting 7 watt. Figure 5.2 shows the Achievable SU rate with change in γ. Here when whole power of SU is used to transmit its own code word, then achievable rate of SU is very high, but as we decrease the portion of power then rate of SU decreases with increase in γ. 27

38 Figure 5.3 Figure showing the comparative change in maximum achievable rate of PU and SU with change in γ In Figure 5.3 we can see the achievable rate of both PU and SU with increasing γ. This graph is very much useful to determine that both SU and PU are satisfied with given power split or not. Here we can see at γ = 0, the rate of PU is not zero whereas when γ = 100 the rate of SU is 0, this is because even if SU does not assist PU, there exist small rate for PU due to its own transmission but when all power is given to PU, SU totally act as a repeater for PU so rate of SU goes down to zero. As the value of γ goes on increasing the rate of PU goes on increasing and rate of SU goes on decreasing. For co-access the value of γ should be chosen in such a way that there should be win win situation for both primary as well as secondary user. This power split should be chosen in proper manner for the co-access. 28

39 Figure 5.4 shows the various curves; in which each curve represent the variation in achievable SU rate with fixed PU power and varying SU power. PU transmit power is assumed as 5 watt and SU transmit power ranges from 1 to 7 watt. Each curve associated with it is plotted in the graph. The maximum achievable rate is increased with increase in SU transmit power. This is due to more power for SU codeword as SU tranmit power is increased. Figure 5.4 Effect of change in transmit power level of SU on maximum achievable rate of SU network Figure 5.5 shows the various curves; in which each curve represent the variation in achievable PU rate with fixed PU power and varying SU power. PU transmit power is assumed as 5 watt and SU transmitting with power ranging from 1 to 7 watt. Each curve associated with it is plotted in the graph. The maximum achievable rate of SU is increased with increase in SU transmit power. 29

40 Figure 5.5 Effect of change in transmit power level of SU on maximum achievable rate of PU network 5.3 Region of Co-Access Region of co-access is defined as the geographical location around the primary user where secondary can be located and incentivize the Primary user also finding some space for itself. The basic architecture and methodology of how to calculate the region of co-access is already discussed in chapter 4. Figure 4.1 shows the basic architecture for determination of region of co-access. Thus using the equations and the architecture with various simulation parameters the below result is obtained and interpreted. 30

41 Figure 5.6: Region of co-access where SU can located between any two PU node Figure 5.6 shows the region of co-access around the second primary user, where SU can be located to co-access with the primary user. It consist of two circles, the first one denotes the coverage of the PU1, and the second one denotes the coverage of PU3, PU2 is repeater, SU should be within the first circle so that it can relay the message of PU for incentivizing, but this location should be proper enough that PU3 gets the relayed message with given incentive. Thus the region between the two circles is what we called the region of co-access. 31

42 CHAPTER SIX EPILOGUE 32

43 6.1 Limitations The various limitations of this dissertation are as follows: 1. For now, fixed transmit power is considered for simulation purpose. 2. The spectrum is assumed that it is sensed and priori information of PU is already given to the SU. 6.2 Future Enhancements This possibility of future enhancement are as follows: 1. It can be used for all types of wireless bands. 2. Adaptive power control according to PU power can be implemented in SU transmitted. 3. System modeling with numbers of node pair can be done. 6.3 Schedule This thesis is aimed to complete within twenty two weeks. Collection and Study of Materials Familiarization of N/Wsimulator Algorithm Study, Design and System Design Integration and Testing Output Analysis Documentation and Report Table 6.1 Time schedule 33

44 6.4 Conclusion This dissertation presents a dynamic spectrum access architecture termed DSCA. DSCA enables SUs to co-access spectrum with PUs, i.e., simultaneously transmit with PUs. This significantly reduces the disruption to SU communication due to the Resurgence of PU traffic. Furthermore, it offers guaranteed incentives to PUs to allow the co-access of SUs, as well as guaranteed performance for SUs in spectrum co-access. Together, both PUs and SUs benefit from the DSCA architecture. We have defined the co-access incentives for both PUs and SUs, and derived a model to compute the region of co-access based on the co-access incentives. 34

45 REFERENCES 35

46 [1] S.Sun.,Y. Ju., overlay cognitive radio ofdm system for 4g cellular network, IEEE Wireless Communication, April [2] A. Goldsmith et al., Breaking spectrum gridlock with cognitive radios: an information theoretic perspective, Proc. IEEE, vol. 97, no. 5, May 2009, pp [3] C. Xin, M. Song, L. Ma, G. Hsieh, and C.-C. Shen, An incentivized cooperative architecture for dynamic spectrum access networks, IEEE Trans. Wireless Commun., vol. 12, no. 10, pp , Oct [4] J. Mitola, Cognitive radio, Licentiate proposal, KTH, Stockholm, Sweden,Dec [5] H. Bezabih et al., Digital broadcasting: increasing the available white space spectrum using tv receiver information, IEEE Vehic. Tech. Mag., vol. 7 no. 1, Mar. 2012, pp [6] K. Shin, H. Kim, A. Min, and A. Kumar, cognitive radios for dynamic spectrum access: from concept to reality, wireless communications, IEEE, vol. 17, no. 6, pp , [7] M. Song, C. Xin, Y. Zhao, and X. Cheng, Dynamic spectrum access: from cognitive radio to network radio, Wireless Communications, IEEE,vol. 19, no. 1, pp , [8] M. Costa, Writing in a dirty paper (corresp.), IEEE transaction on Information Theory, Vol 29, No.3, pp ,

47 [9] X. Guan, Y. Cai, Y. Sheng, and W. Yang, Exploiting primary retransmission to improve secondary throughput by cognitive relaying with best-relay selection, IET Communications, vol. 6, no. 12, pp , [10] M. Mohammadin, S. seltine., Joint interference cancellation and dirty paper coding for cog- nitive cellular networks, in Wireless Communications and Networking Conference (WCNC), 2011 IEEE. IEEE, 2011, pp [11] R. Zhang, Member, IEEE, and Y-C Liang, Senior Member, IEE., Investigation on Multiuser Diversity in Spectrum Sharing Based Cognitive Radio Networks. [12] Federal Communications Commission Spectrum Policy Task Force, Report of the Spectrum Efficiency Working Group, Technica Report , no. November, Download available at 1.pdf [13] T. cover, Broadcast Channels, IEEE transaction on Information Theory, Vol 18, pp. 2-14, [14] Transmit power level of GSM base station. Download available at wer.php 37