Optimal power allocation for fading channels in cognitive radio networks

OPTIMAL POWER ALLOCATION FOR FADING CHANNELS IN COGNITIVE RADIO NETWORKS KANG XIN NATIONAL UNIVERSITY OF SINGAPORE 2010 OPTIMAL POWER ALLOCATION FOR FADING CHANNELS IN COGNITIVE RADIO NETWORKS KANG XIN (B Eng., Xi’an Jiaotong University, China) A THESIS SUBMITTED FOR THE DEGREE OF DOCTOR OF PHILOSOPHY DEPARTMENT OF ELECTRICAL AND COMPUTER ENGINEERING NATIONAL UNIVERSITY OF SINGAPORE 2010 Acknowledgement First of all, I would like to express my sincere gratitude and appreciation to my advisors Prof Hari Krishna Garg and Dr Ying-Chang Liang for their valuable guidance and helpful technical support throughout my Ph.D course Had it not been for their advices, direction, patience and encouragement, this thesis would certainly not be possible I would like to thank Dr Rui Zhang in Institute for Infocomm Research, and Dr Arumugam Nallanathan in King’s College London, with whom I have had the good fortune to collaborate My thanks also go to my research groupmates Edward Chu Yeow Peh, Yiyang Pei, Shoukang Zheng, Ebrahim Avazkonandeh Gharavol, and Yonghong Zeng in Institute for Infocomm Research for their kind discussion and good advices on my research topics Meanwhile, I would like to thank my colleagues Feifei Gao, Jinhua Jiang, Wei Cao, Qian Chen, Mingwei Wu, PeiJie Wang, Le Cao, Yang Lu, Jianwen Zhang, HonFah Chong, and Pham The Hanh in the ECE-I2 R Wireless Communications Laboratory at the Department of Electrical and Computer Engineering for their friendship and help Lastly, and most importantly, I would like to thank my parents and my wife for their love, support, and encouragement ii Contents Acknowledgement ii Contents iii Summary ix List of Figures xi List of Tables xiv List of Notations xv List of Abbreviations xvi Introduction 1.1 Motivations 1.2 Cognitive Radio Models 1.2.1 The opportunistic spectrum access model 1.2.2 The spectrum sharing model 1.3 Related Work and Challenges 1.4 Contributions and Organization of the Thesis 10 Optimal Power Allocation for Single-SU Fading CR Channels: Ergodic, iii CONTENTS Delay-limited, and Outage Capacities 13 2.1 Introduction 14 2.2 System Model and Power Constraints 16 2.2.1 System model 16 2.2.2 Power constraints 17 Ergodic Capacity 18 2.3.1 Peak transmit and peak interference power constraint 18 2.3.2 Peak transmit and average interference power constraint 19 2.3.3 Average transmit and peak interference power constraint 20 2.3.4 Average transmit and average interference power constraint 20 Delay-limited Capacity 21 2.4.1 Rayleigh fading 22 2.4.2 Nakagami fading 22 2.4.3 Log-normal shadowing 23 Outage Capacity 24 2.5.1 Peak transmit and peak interference power constraint 24 2.5.2 Peak transmit and average interference power constraint 25 2.5.3 Average transmit and peak interference power constraint 25 2.5.4 Average transmit and average interference power constraint 26 2.5.5 Analytical Results 27 Simulation Results 30 2.6.1 Ergodic capacity 30 2.6.2 Delay-limited capacity and outage capacity 33 Conclusions 37 2.3 2.4 2.5 2.6 2.7 Optimal Power Allocation for Fading Cognitive Multiple Access Channels: Outage Capacity Regions 38 iv CONTENTS 3.1 Introduction 39 3.2 System Model 41 3.2.1 System Model 41 3.2.2 Power Constraints 42 Common Outage Capacity For Fading C-MAC 43 3.3.1 Definition of Common Outage Capacity 43 3.3.2 Common Usage Probability Maximization 44 Individual Outage Capacity For Fading C-MAC 50 3.4.1 Definition of Individual Outage Capacity 50 3.4.2 Individual Usage Probability Region 51 3.4.3 M SUs scenario 55 Numerical Results 57 3.5.1 Common Outage Capacity 57 3.5.2 Individual Outage Capacity 59 Conclusions 61 3.3 3.4 3.5 3.6 Optimal Power Allocation for Fading CR Networks with PU Outage Constraint 63 4.1 Introduction 64 4.2 System Model 66 4.2.1 Channel Model 66 4.2.2 Primary User Transmission 67 4.2.3 Secondary User Transmission 68 Ergodic Capacity of SU under PU Outage Constraint 69 4.3.1 Average Power Constraint 70 4.3.2 Peak Power Constraint 74 Outage Capacity of SU under PU Outage Constraint 76 4.3 4.4 v CONTENTS 4.4.1 Peak Power Constraint 81 Simulation Results 83 4.5.1 Ergodic Capacity of SU 84 4.5.2 Outage Capacity of SU 85 4.5.3 4.6 77 4.4.2 4.5 Average Power Constraint Imperfect Channel Estimation 87 Concluding Remarks 90 Optimal Power Allocation for OFDM-based fading CR Networks with PU Rate Loss Constraint 91 5.1 Introduction 92 5.2 System Model 94 5.3 Achievable Rate of SU under the Rate Loss Constraint 97 5.4 Relationship between the Rate Loss Constraint and the Interference Power Constraint 103 5.4.1 The per user based interference power constraint 104 5.4.2 The per subcarrier based interference power constraint 105 5.5 Achievable Rate of SU with Hybrid Protection to PUs 106 5.6 Numerical Results 111 5.6.1 Example 1: Effects of rate loss constraints on SU’s transmission rate 111 5.6.2 Example 2: Comparison of the rate loss constraint and per subcarrier based interference power constraint 112 5.6.3 Example 3: Effects of imperfect CSI on PU’s rate loss 113 5.6.4 Example 4: Comparison of the hybrid protection constraint and per user based interference power constraint 116 5.7 Conclusions 117 vi CONTENTS Sensing-based Spectrum Sharing in Fading CR Networks 118 6.1 Introduction 119 6.2 System Model 120 6.2.1 System Model 120 6.2.2 Spectrum Sensing Model 120 6.2.3 Transmission Model 121 6.3 Problem Formulation 122 6.4 Sensing-based Spectrum Sharing under Perfect Sensing 124 6.5 Sensing-based Spectrum Sharing under imperfect Sensing 127 6.6 Numerical Results 129 6.6.1 6.6.2 6.7 Perfect Sensing Scenario 129 Imperfect Sensing Scenario 131 Conclusions 133 Conclusions and Future Work 134 7.1 Conclusions 134 7.2 Future Work 136 7.2.1 Distributed Resource Allocation in Fading CR Networks 137 7.2.2 Resource Allocation for Fading CR networks with Imperfect CSI137 7.2.3 Resource Allocation for MIMO CR networks 137 7.2.4 Upper Layer Issues for Fading CR Networks 138 7.2.5 Resource Allocation for Femtocell Networks 138 A Appendices to Chapter 139 A.1 Proof of Theorem 2.1 139 A.2 Proof of Theorem 2.3 142 vii CONTENTS B Appendices to Chapter 144 B.1 Proof of Proposition 3.2 144 C Appendices to Chapter 147 C.1 Proof of Theorem 5.1 147 C.2 Proof of Proposition 5.1 148 D Appendices to Chapter 149 D.1 Proof of Proposition 6.1 149 Bibliography 151 List of Publications 171 viii Summary With the rapid development of wireless services and applications, the currently deployed radio spectrum is becoming more and more crowded How to accommodate more wireless services and applications within the limited radio spectrum becomes a big challenge faced by modern society Cognitive radio (CR) is proposed as a promising technology to tackle this challenge by introducing the secondary (unlicensed) users to opportunistically or concurrently access the spectrum allocated to primary (licensed) users Currently, there are two prevalent CR models: the opportunistic spectrum access model and the spectrum sharing model In the opportunistic spectrum access model, secondary users (SUs) are allowed to access the spectrum only if the primary users (PUs) are detected to be inactive In the spectrum sharing model, the SUs are allowed to coexist with the PUs as long as the interference from SUs not degrade the quality of service (QoS) of PUs to an unacceptable level This thesis studies a number of topics in CR networks under the framework of the spectrum sharing model First, we investigate the ergodic, delay-limited, and outage capacity of a single SU point-to-point channel under various fading models The optimal power allocation strategies to achieve these capacities are derived under different combinations of peak and average transmit/interference power constraints Then, we extend the obtained results to the multi-SU scenario Specifically, the outage capacity regions for a M-SU cognitive multiple access channel (C-MAC) network is characterized The optimal resource allocation schemes to achieve the boundary points 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cognitive radio networks under transmit and interference power constraints,” in Proc IEEE International Conference on Communications 2008 (ICC ’08), Beijing, China, May 2008, pp 3568-3572 X Kang, Y.-C Liang, and A Nallanathan, ”Optimal power allocation for fading channels in cognitive radio networks: Delay-limited capacity and outage capacity,” in Proc IEEE Vehicular Technology Conference 2008 (VTC Spring ’08), Singapore, May 2008, pp 1544-1548 X Kang, Y.-C Liang, and H K Garg, ”Outage probability minimization under both the transmit and interference power constraints for fading channels in cognitive radio networks,” in Proc IEEE International Conference on Communications Workshops 2008 (ICC Workshops ’08), Beijing, China, May 2008, pp 482-486 X Kang, Y.-C Liang, H K Garg, and L Zhang, ”Sensing-based spectrumsharing in cognitive radio networks,” in Proc IEEE Global Communications Conference 2008 (GLOBECOM ’08), New Orleans, USA, Dec 2008 X Kang, R Zhang, Y.-C Liang, and H K Garg, ”Optimal power allocation for cognitive radio under primary user’s outage loss constraint,” in Proc IEEE International Conference on Communications 2009 (ICC ’09), Dresden, Germany, June 2009 R Zhang, X Kang, and Y.-C Liang, ”Protecting primary users in cognitive radio 172 networks: Peak or average interference power constraint,” in Proc IEEE International Conference on Communications 2009 (ICC ’09), Dresden, Germany, June 2009 X Kang, H K Garg, Y.-C Liang, and R Zhang, ”Power allocation for OFDMbased cognitive radio systems with hybrid protection to primary users,” in Proc IEEE Global Communications Conference 2009 (GLOBECOM ’09), Honolulu, Hawaii, USA, Dec 2009 X Kang, R Zhang, Y.-C Liang, and H K Garg, ”On outage capacity of secondary users in fading cognitive radio networks with primary user’s outage constraint,” in Proc IEEE Global Communications Conference 2009 (GLOBECOM ’09), Honolulu, Hawaii, USA, Dec 2009 X Kang, Y.-C Liang, and H K Garg, ”Optimal power allocation for fading cognitive multiple access channels: individual outage capacity region,” in Proc IEEE Wireless Communications and Networking Conference 2010 (WCNC ’10), Sydney, Australia, April 2010 10 X Kang, Y.-C Liang, and H K Garg, ”Distributed power control for spectrumsharing femtocell networks using Stackelberg Game,” in Proc IEEE International Conference on Communications 2011 (ICC ’11), Kyoto, Japan, June 2011 173 ... capacities for a single-SU fading CR channel Chapter studies outage capacity regions for fading C-MAC In Chapter 4, the optimal power allocation for fading CR networks with PU outage constraint is... for various fading CR networks, including single CR point-to-point channel, cognitive MAC, and cognitive OFDM systems For a single SU point-to-point fading channel, we investigate its ergodic,.. .OPTIMAL POWER ALLOCATION FOR FADING CHANNELS IN COGNITIVE RADIO NETWORKS KANG XIN (B Eng., Xi’an Jiaotong University, China) A THESIS SUBMITTED FOR THE DEGREE OF DOCTOR