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Spectrum Management in Cognitive Radio Wireless Networks

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Spectrum Management in Cognitive Radio Wireless Networks SPECTRUM MANAGEMENT IN COGNITIVE RADIO WIRELESS NETWORKS A Thesis Presented to The Academic Faculty by Won Yeol Lee In Partial Ful¯llment of the Requirements for the Degree Doctor of Philosophy in the School of Electrical and Computer Engineering Georgia Institute of Technology August 2009 SPECTRUM MANAGEMENT IN COGNITIVE RADIO WIRELESS NETWORKS Approved by: Professor Ian F. Akyildiz, Advisor Professor Joy Laskar School of Electrical and Computer School of Electrical and Computer Engineering Engineering Georgia Institute of Technology Georgia Institute of Technology Professor Ye (Geo®rey) Li Professor Mostafa Ammar School of Electrical and Computer College of Computing Engineering Georgia Institute of Technology Georgia Institute of Technology Professor Raghupathy Sivakumar Date Approved: 4 August 2009 School of Electrical and Computer Engineering Georgia Institute of Technology To my parents for their endless love and support. iii ACKNOWLEDGEMENTS First of all, I sincerely want to thank my advisor Dr. Ian F. Akyildiz for his guidance, support and encouragement. He gave me constructive criticisms as well as rewarding praises, which motivated and trained me to improve the quality of my research. He has also been a great role model and I undoubtedly intend to use what I have learned from him as I move forward in my career. He is someone I de¯nitely hope to live up to someday. I would like to acknowledge Dr. Ye (Geo®rey) Li, Dr. Raghupathy Sivakumar, Dr. Joy Laskar, and Dr. Mostafa Ammar for being on my dissertation defense committee. Their invaluable comments and enlightening suggestions have helped improve the quality for this dissertation. I also want to acknowledge all former and current members of the Broadband Networking Laboratory for their support and friendship. The unique family-like en- vironment made me to survive the tough Ph.D. student life with comfort. Last but not least, I can never ¯nd enough words to express how grateful I am for the endless support of my family. My parents have always provided me with unconditional love, sacri¯ces, and support. Without their faith in me, I could not have made it this far. I also like to thank my younger brother and sister for their love, encouragement, and concern for me. I also want to thank my mother-in-law for her support and pride in me. Finally, and most importantly, I would like to express much gratitude and love to my wife, Yang Hee Jeon. Without her patience, sacri¯ces, and love, I would not have been able to complete this work. iv TABLE OF CONTENTS DEDICATION . iii ACKNOWLEDGEMENTS . iv LIST OF TABLES . xi LIST OF FIGURES . xii LIST OF SYMBOLS OR ABBREVIATIONS . xv SUMMARY . xvii I INTRODUCTION . 1 1.1 Background . 1 1.2 Research Objectives and Solutions . 4 1.2.1 Spectrum Management Framework in Cognitive Radio Net- works . 6 1.2.2 Optimal Spectrum Sensing Framework for Cognitive Radio Networks . 6 1.2.3 QoS-Aware Spectrum Decision Framework for Cognitive Ra- dio Networks . 7 1.2.4 Spectrum Sharing Framework for Infrastructure-Based Cog- nitive Radio Networks . 7 1.2.5 Spectrum-Aware Mobility Management in Cognitive Radio Cellular Networks . 8 1.3 Thesis Outline . 9 II SPECTRUM MANAGEMENT IN COGNITIVE RADIO NETWORKS 11 2.1 Introduction . 11 2.2 Spectrum Sensing . 13 2.2.1 Basic Functionalities . 13 2.2.2 Research Challenges . 16 2.3 Spectrum Decision . 16 2.3.1 Basic Functionalities . 16 v 2.3.2 Research Challenges . 19 2.4 Spectrum Sharing . 20 2.4.1 Basic Functionalities . 20 2.4.2 Research Challenges . 23 2.5 Spectrum Mobility . 24 2.5.1 Basic Functionalities . 24 2.5.2 Research Challenges . 27 III OPTIMAL SPECTRUM SENSING FRAMEWORK FOR COGNITIVE RA- DIO NETWORKS . 28 3.1 Introduction . 28 3.2 System Model . 31 3.2.1 System Description . 31 3.2.2 Primary User Activity Model . 33 3.2.3 Optimal Spectrum Sensing Framework . 34 3.3 Sensing Parameter Optimization in a Single Spectrum Band . 35 3.3.1 Problem De¯nition . 35 3.3.2 Maximum A Posteriori (MAP) Energy Detection for Spec- trum Sensing . 36 3.3.3 Analytical Model for Interference . 39 3.3.4 Sensing Parameter Optimization . 42 3.4 Spectrum Selection and Scheduling for Spectrum Sensing on Multi- ple Spectrum Bands . 45 3.4.1 Problem De¯nition . 46 3.4.2 Spectrum Selection for Selective Sensing . 47 3.4.3 Sensing Scheduling for Multiple Spectrum Bands . 47 3.5 Adaptive and Cooperative Spectrum Sensing in Multiuser Networks 49 3.5.1 Problem De¯nition . 49 3.5.2 Availability Decision using Cooperative Gain . 50 3.5.3 Sensing Parameter Adaptation . 52 3.6 Performance Evaluation . 52 vi 3.6.1 Sensing Parameter Optimization in a Single Band . 53 3.6.2 Resource Allocation on Multiple Spectrum Band . 54 3.6.3 Cooperative Sensing in Multi-User Networks . 56 IV QOS-AWARE SPECTRUM DECISION FRAMEWORK FOR COGNITIVE RADIO NETWORKS . 59 4.1 Introduction . 59 4.2 A Framework for Spectrum Decision in Cognitive Radio Networks . 61 4.2.1 System Model . 61 4.2.2 Framework Overview . 62 4.2.3 Spectrum Decision Functionalities . 64 4.3 Spectrum Characterization . 66 4.3.1 Primary User Activity . 66 4.3.2 Cognitive Radio Capacity Model . 66 4.4 Spectrum Decision for Real-time Applications . 69 4.4.1 Minimum Variance-based Spectrum Decision - Single Selec- tion (MVSD-SS) . 70 4.4.2 Minimum Variance based Spectrum Decision - Multiple Se- lections (MVSD-MS) . 74 4.5 Spectrum Decision for Best E®ort Applications . 74 4.5.1 Maximum Capacity-based Spectrum Decision - Single Selec- tion (MCSD-SS) . 75 4.5.2 Maximum Capacity based Spectrum Decision - Multiple Se- lections (MCSD-MS) . 76 4.6 Dynamic Resource Management for Spectrum Decision . 77 4.6.1 Spectrum States for Admission Control . 78 4.6.2 Admission Control . 79 4.6.3 Decision Control . 81 4.7 Performance Evaluation . 87 4.7.1 Simulation Setup . 88 4.7.2 Real-time Applications . 90 vii 4.7.3 Best E®ort Applications . 92 4.7.4 Hybrid Scenario . 94 V JOINT SPECTRUM AND POWER ALLOCATION FOR SPECTRUM SHARING IN INFRASTRUCTURE-BASED CR NETWORKS . 98 5.1 Introduction . 98 5.2 Motivation . 100 5.2.1 Related Work . 100 5.2.2 Considerations in Infrastructure-based CR Networks . 101 5.3 System Model . 104 5.3.1 CR Network Architecture . 104 5.3.2 Primary Network Model . 106 5.4 Inter-Cell Spectrum Sharing Framework . 106 5.4.1 Overview . 106 5.4.2 Spectrum Sharing Procedures . 108 5.4.3 Distributed Spectrum Sharing Capability . 110 5.5 Spectrum Allocation for an Exclusive Model . 112 5.5.1 Cell Characterization . 113 5.5.2 Permissible Transmission Power . 116 5.5.3 Spectrum Selection . 118 5.6 Spectrum Allocation for Common Use Model . 118 5.6.1 Angle-Based Allocation for Uplink Transmission . 119 5.6.2 Interference-Based Spectrum Allocation . 120 5.7 Power Allocation for Inter-Cell Spectrum Sharing . 124 5.7.1 Upper Limits for Transmission Power . 124 5.7.2 Constrained Water Filling Method . 124 5.8 Intra-Cell Spectrum Sharing . 126 5.8.1 User Capacity Model . 127 5.8.2 Intra-Cell Spectrum Sharing Procedures . 129 5.9 Performance Evaluation . 130 viii 5.9.1 Simulation Setup . 130 5.9.2 Total Capacity . 132 5.9.3 Fairness . 134 5.9.4 QoS and Complexity . 136 5.9.5 Interference Avoidance . 138 VI SPECTRUM-AWARE MOBILITY MANAGEMENT IN CR CELLULAR NETWORKS . 140 6.1 Introduction . 140 6.2 The Proposed System Model . 142 6.2.1 Network Architecture . 142 6.2.2 Spectrum Pool Structure . 143 6.2.3 Hando® Types . 145 6.3 Mobility Management Framework . 146 6.3.1 Overview . 146 6.3.2 Inter-Cell Resource Allocation . 147 6.4 Spectrum Hando® Modeling . 149 6.4.1 Intra-Cell/Intra-Pool Hando® . 150 6.4.2 Intra-Cell/Inter-Pool Hando® . 151 6.4.3 Inter-Cell/Inter-Pool Hando® . 151 6.4.4 Inter-Cell/Intra-Pool Hando® . 152 6.5 Spectrum Mobility Management in Cognitive Radio Networks . 153 6.5.1 Overview . ..
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