Resource Allocation in Uplink OFDMA Wireless Systems: Optimal Solutions and Practical Implementations

Tackling problems from the least complicated to the most, Resource Allocation in Uplink OFDMA Wireless Systems provides readers with a comprehensive look at resource allocation and scheduling techniques (for both single and multi-cell deployments) in uplink OFDMA wireless networks?relying on convex optimization and game theory to thoroughly analyze performance. Inside, readers will find topics and discussions on: Formulating and solving the uplink ergodic sum-rate maximization problem Proposing suboptimal algorithms that achieve a close performance to the optimal case at a considerably reduced complexity and lead to fairness when the appropriate utility is used Investigating the performance and extensions of the proposed suboptimal algorithms in a distributed base station scenario Studying distributed resource allocation where users take part in the scheduling process, and considering scenarios with and without user collaboration Formulating the sum-rate maximization problem in a multi-cell scenario, and proposing efficient centralized and distributed algorithms for intercell interference mitigation Discussing the applicability of the proposed techniques to state-of-the-art wireless technologies, LTE and WiMAX, and proposing relevant extensions Along with schematics and figures featuring simulation results, Resource Allocation in Uplink OFDMA Wireless Systems is a valuable book for?wireless communications and cellular systems professionals and students.

Table of Contents:
PREFACE xiii ACKNOWLEDGMENTS xv ACRONYMS xvii CHAPTER 1 INTRODUCTION 1 1.1 Evolution of Wireless Communication Systems 1 1.2 Orthogonal Frequency Division Multiple Access 2 1.3 Organization of this Book 5 CHAPTER 2 BACKGROUND ON DOWNLINK RESOURCE ALLOCATION IN OFDMA WIRELESS NETWORKS 9 2.1 Centralized Single Cell Scheduling 9 2.2 Distributed Scheduling 13 2.3 Scheduling in Multicell Scenarios 14 2.3.1 Multicell Scheduling in LTE 16 2.4 Summary 18 CHAPTER 3 ERGODIC SUM-RATE MAXIMIZATION WITH CONTINUOUS RATES 19 3.1 Background 19 3.2 Problem Formulation 21 3.3 Problem Solution 23 3.4 Achievable Rate Region 28 3.5 Results and Discussion 35 3.6 Summary 41 CHAPTER 4 ERGODIC SUM-RATE MAXIMIZATION WITH DISCRETE RATES 43 4.1 Background 43 4.2 Problem Formulation 44 4.3 Problem Solution 46 4.4 Results and Discussion 52 4.5 Summary 57 CHAPTER 5 GENERALIZATION TO UTILITY MAXIMIZATION 59 5.1 Background 59 5.2 Ergodic Utility Maximization with Continuous Rates 60 5.3 Ergodic Utility Maximization with Discrete Rates 64 5.4 Summary 68 CHAPTER 6 SUBOPTIMAL IMPLEMENTATION OF ERGODIC SUM-RATE MAXIMIZATION 69 6.1 Background 69 6.2 Suboptimal Approximation of the Continuous Rates Solution 71 6.3 Suboptimal Approximation of the Discrete Rates Solution 73 6.4 Complexity Analysis of the Suboptimal Algorithms 76 6.5 Results and Discussion 78 6.6 Summary 88 CHAPTER 7 SUBOPTIMAL IMPLEMENTATION WITH PROPORTIONAL FAIRNESS 89 7.1 Background 89 7.2 Proportional Fair Scheduling 91 7.3 Low Complexity Utility Maximization Algorithms 94 7.4 Proportional Fair Utilities 100 7.5 Results and Discussion 101 7.6 Summary 112 CHAPTER 8 SCHEDULING WITH DISTRIBUTED BASE STATIONS 113 8.1 Background 113 8.2 System Model 115 8.3 Scheduling with Distributed Base Stations 118 8.4 Results and Discussion 120 8.5 Distributed Base Stations Versus Relays 128 8.6 Distributed Base Stations Versus Femtocells 131 8.7 Summary 133 CHAPTER 9 DISTRIBUTED SCHEDULING WITH USER COOPERATION 135 9.1 Background 135 9.2 Cooperative Distributed Scheduling Scheme 136 9.3 Distributed Scheduling Algorithm 140 9.4 Results and Discussion 142 9.5 Summary 149 CHAPTER 10 DISTRIBUTED SCHEDULING WITHOUT USER COOPERATION 151 10.1 Background 151 10.2 Noncooperative Distributed Scheduling Scheme 153 10.3 Comparison to Existing Schemes 155 10.4 Analysis of Measurement Inaccuracies 156 10.5 Results and Discussion 160 10.6 Optimization of Transmission Probabilities 165 10.7 Practical Considerations 169 10.8 Summary 171 CHAPTER 11 CENTRALIZED MULTICELL SCHEDULING WITH INTERFERENCE MITIGATION 173 11.1 Background 173 11.2 Problem Formulation 175 11.3 Iterative Pricing-Based Power Control Solution 178 11.4 Pricing Game with Centralized Control 184 11.5 Suboptimal Scheduling Scheme Using Pricing-Based Power Control 186 11.6 Suboptimal Scheduling Scheme Using Probabilistic Transmission 190 11.7 Results and Discussion 191 11.8 Summary 201 CHAPTER 12 DISTRIBUTED MULTICELL SCHEDULING WITH INTERFERENCE MITIGATION 203 12.1 Background 203 12.2 System Model 204 12.3 Intracell Cooperation: Distributed Scheduling 205 12.4 Intercell Interference Mitigation/Avoidance 206 12.5 Results and Discussion 209 12.6 Practical Aspects 217 12.6.3 Application in a CR Network 219 12.6.4 Application in a Network with Femtocell Deployment 219 12.6.5 Distributed Multicell Scheduling without User Cooperation 220 12.7 Summary 221 CHAPTER 13 SCHEDULING IN STATE-OF-THE-ART OFDMA-BASED WIRELESS SYSTEMS 223 13.1 WiMAX Scheduling Overview 223 13.2 LTE Scheduling Overview 228 13.3 SCFDMA Versus OFDMA Scheduling 235 13.4 Comparison to the LTE Power Control Scheme 240 13.5 Summary 245 CHAPTER 14 FUTURE RESEARCH DIRECTIONS 247 14.1 Resource Allocation with Multiple Service Classes 247 14.2 Network MIMO 247 14.3 Coalitional Game Theory 248 14.4 Resource Allocation with Femtocells 249 14.5 Green Networks and Self-Organizing Networks 249 14.6 Joint Uplink/Downlink Resource Allocation 250 14.7 Joint Resource Allocation in Heterogeneous Networks 251 14.8 Resource Allocation in Cognitive Radio Networks 252 BIBLIOGRAPHY 255 INDEX 269