Resource allocation in uplink OFDMA wireless systems : optimal solutions and practicalimplementations

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.

Author Notes

Zaher Dawy, PhD. is an associate professor at the American University of Beirut (AUB). His research interests include cooperative and distributed communications, resource allocation, cellular technologies, and computational biology. He received the IEEE Communications Society Outstanding Young Researcher Award for Europe, Middle East, and Africa Region in 2011 and the AUB 2008 Teaching Excellence Award Dr. Dawy is a senior member of the IEEE and Chair of the IEEE Communications Society, Lebanon Chapter.

Preface	p. xiii
Acknowledgments	p. xv
Acronyms	p. xvii
Chapter 1 Introduction	p. 1
1.1 Evolution of Wireless Communication Systems	p. 1
1.2 Orthogonal Frequency Division Multiple Access	p. 2
1.3 Organization of this Book	p. 5
Chapter 2 Background on Downlink Resource Allocation in OFDMA Wireless Networks	p. 9
2.1 Centralized Single Cell Scheduling	p. 9
2.1.1 Continuous Versus Discrete Rates	p. 11
2.1.2 Optimal Versus Suboptimal Scheduling	p. 12
2.2 Distributed Scheduling	p. 13
2.3 Scheduling in Multicell Scenarios	p. 14
2.3.1 Multicell Scheduling in LTE	p. 16
2.4 Summary	p. 18
Chapter 3 Ergodic Sum-Rate Maximization with Continuous Rates	p. 19
3.1 Background	p. 19
3.2 Problem Formulation	p. 21
3.3 Problem Solution	p. 23
3.3.1 Solution of the Dual Problem	p. 24
3.3.2 Duality Gap Analysis	p. 26
3.3.3 Complexity Analysis	p. 28
3.3.4 Solution Approach in a MIMO Scenario	p. 28
3.4 Achievable Rate Region	p. 28
3.4.1 K-user Achievable Rate Region without Rate Constraints	p. 29
3.4.2 K-user Achievable Rate Region with Rate Constraints	p. 30
3.4.3 Application to the Two-Users Rate Region	p. 32
3.5 Results and Discussion	p. 35
3.5.1 Simulation Parameters	p. 35
3.5.2 Multiplier Calculation and Convergence	p. 35
3.5.3 Duality Gap Results	p. 38
3.5.4 Sum-Rate Results	p. 38
3.6 Summary	p. 41
Chapter 4 Ergodic Sum-Rate Maximization with Discrete Rates	p. 43
4.1 Background	p. 43
4.2 Problem Formulation	p. 44
4.3 Problem Solution	p. 46
4.3.1 Duality Gap Analysis	p. 50
4.3.2 Complexity Analysis	p. 52
4.4 Results and Discussion	p. 52
4.4.1 Simulation Model	p. 52
4.4.2 Continuous Versus Discrete Rates	p. 53
4.4.3 Impact of Modulation and Coding Schemes	p. 54
4.4.4 Impact of Varying the User Weights	p. 56
4.5 Summary	p. 57
Chapter 5 Generalization to Utility Maximization	p. 59
5.1 Background	p. 59
5.2 Ergodic Utility Maximization with Continuous Rates	p. 60
5.2.1 Duality Gap	p. 62
5.3 Ergodic Utility Maximization with Discrete Rates	p. 64
5.3.1 Duality Gap	p. 67
5.4 Summary	p. 68
Chapter 6 Suboptimal Implementation of Ergodic Sum-Rate Maximization	p. 69
6.1 Background	p. 69
6.2 Suboptimal Approximation of the Continuous Rates Solution	p. 71
6.3 Suboptimal Approximation of the Discrete Rates Solution	p. 73
6.4 Complexity Analysis of the Suboptimal Algorithms	p. 76
6.4.1 Complexity Analysis in the Continuous Rates Case	p. 76
6.4.2 Complexity Analysis in the Discrete Rates Case	p. 77
6.5 Results and Discussion	p. 78
6.5.1 Simulation Parameters	p. 78
6.5.2 Results of the Continuous Rates Approximation	p. 78
6.5.3 Results of the Discrete Rates Approximation	p. 80
6.5.4 Results in the Case of Imperfect CSI	p. 81
6.5.5 Comparison to Existing Algorithms	p. 84
6.6 Summary	p. 88
Chapter 7 Suboptimal Implementation with Proportional Fairness	p. 89
7.1 Background	p. 89
7.2 Proportional Fair Scheduling	p. 91
7.2.1 PF Scheduling Methods	p. 91
7.2.2 Equivalence of PF and NBS	p. 92
7.3 Low Complexity Utility Maximization Algorithms	p. 94
7.3.1 Complexity Analysis of the Utility Maximization Algorithms	p. 97
7.3.2 Comparison to Existing Algorithms	p. 98
7.3.3 Rate Calculations	p. 99
7.4 Proportional Fair Utilities	p. 100
7.5 Results and Discussion	p. 101
7.5.1 Simulation Model	p. 101
7.5.2 PFF and PFTF Utility Comparison	p. 101
7.5.3 RB-based Scheduling: Greedy and PFF Utilities	p. 103
7.5.4 Comparison to Existing Algorithms	p. 107
7.5.5 Independent versus Equal Fading over the Subcarriers of an RB	p. 111
7.6 Summary	p. 112
Chapter 8 Scheduling with Distributed Base Stations	p. 113
8.1 Background	p. 113
8.2 System Model	p. 115
8.3 Scheduling with Distributed Base Stations	p. 118
8.3.1 Scheduling Algorithm for DBS Scenarios	p. 118
8.3.2 Complexity Analysis of the DBS Scheduling Algorithm	p. 120
8.4 Results and Discussion	p. 120
8.4.1 Simulation Model	p. 120
8.4.2 Sum-Rate Results	p. 121
8.4.3 Fairness Analysis	p. 123
8.4.4 Location Optimization	p. 126
8.4.5 Mobility Considerations	p. 127
8.5 Distributed Base Stations Versus Relays	p. 128
8.6 Distributed Base Stations Versus Femtocells	p. 131
8.7 Summary	p. 133
Chapter 9 Distributed Scheduung with User Cooperation	p. 135
9.1 Background	p. 135
9.2 Cooperative Distributed Scheduling Scheme	p. 136
9.2.1 System Model	p. 136
9.2.2 CSI Quantization Scheme	p. 138
9.2.3 Price of Anarchy	p. 139
9.3 Distributed Scheduling Algorithm	p. 140
9.3.1 Rate Calculations with Quantized CSI	p. 142
9.4 Results and Discussion	p. 142
9.4.1 Simulation Model	p. 142
9.4.2 Greedy Scheduling Results	p. 143
9.4.3 PF Scheduling Results	p. 145
9.5 Summary	p. 149
Chapter 10 Distributed Scheduling without User Cooperation	p. 151
10.1 Background	p. 151
10.2 Noncooperative Distributed Scheduling Scheme	p. 153
10.2.1 System Model	p. 153
10.2.2 Distributed Scheduling Scheme	p. 153
10.3 Comparison to Existing Schemes	p. 155
10.4 Analysis of Measurement Inaccuracies	p. 156
10.5 Results and Discussion	p. 160
10.5.1 Simulation Model	p. 160
10.5.2 Simulation Results	p. 161
10.6 Optimization of Transmission Probabilities	p. 165
10.6.1 Optimization Methods	p. 165
10.6.2 Optimization Results	p. 166
10.7 Practical Considerations	p. 169
10.7.1 Collisions	p. 169
10.7.2 Collaboration Between Mobile Users	p. 169
10.7.3 Role of the Central Controlling Devices	p. 170
10.7.4 Extension to a Single Cell Scenario	p. 170
10.7.5 Extension to a Multiple Cell Scenario	p. 171
10.7.6 Cognitive Radio and 4G	p. 171
10.8 Summary	p. 171
Chapter 11 Centralized Multicell Scheduling with Interference Mitigation	p. 173
11.1 Background	p. 173
11.2 Problem Formulation	p. 175
11.3 Iterative Pricing-Based Power Control Solution	p. 178
11.3.1 Single Cell Problem Formulation	p. 178
11.3.2 Single Cell Scheduling Solution	p. 179
11.3.3 Iterative Pricing Game	p. 182
11.4 Pricing Game with Centralized Control	p. 184
11.4.1 Online versus Offline Implementation	p. 186
11.5 Suboptimal Scheduling Scheme Using Pricing-Based Power Control	p. 186
11.5.1 Utility Functions	p. 186
11.5.2 Setting the Prices in the Power Control Scheme	p. 189
11.5.3 Scheduling Algorithm	p. 189
11.6 Suboptimal Scheduling Scheme Using Probabilistic Transmission	p. 190
11.7 Results and Discussion	p. 191
11.7.1 Simulation Model	p. 191
11.7.2 Comparison of the Pricing-Based Power Control Schemes	p. 191
11.7.3 Results of the Suboptimal Pricing-Based Power Control Schemes	p. 196
11.7.4 Results of the Suboptimal Probabilistic Scheduling Scheme	p. 198
11.8 Summary	p. 201
Chapter 12 Distributed Multicell Scheduling with Interference Mitigation	p. 203
12.1 Background	p. 203
12.2 System Model	p. 204
12.3 Intracell Cooperation: Distributed Scheduling	p. 205
12.4 Intercell Interference Mitigation/Avoidance	p. 206
12.4.1 Intercell Cooperation: Transparent Pricing Scheme	p. 207
12.4.2 Intercell Cooperation: Pricing-Based Power Control Scheme	p. 208
12.4.3 Interference Avoidance in the Absence of Intercell Cooperation: Probabilistic Transmission Scheme	p. 209
12.5 Results and Discussion	p. 209
12.5.1 Simulation Model	p. 209
12.5.2 Greedy Allocation Results	p. 210
12.5.3 Proportional Fair Allocation Results	p. 213
12.5.4 Additional Comments	p. 216
12.6 Practical Aspects	p. 217
12.6.1 Application in a Local Area Network	p. 217
12.6.2 Application in a Distributed Base Station Scenario	p. 217
12.6.3 Application in a CR Network	p. 219
12.6.4 Application in a Network with Femtocell Deployment	p. 219
12.6.5 Distributed Multicell Scheduling without User Cooperation	p. 220
12.7 Summary	p. 221
Chapter 13 Scheduling in State-Of-The-Art OFDMA-Based Wireless Systems	p. 223
13.1 WiMAX Scheduling Overview	p. 223
13.1.1 Enhancements in the Next Generation of WiMAX	p. 226
13.1.2 Intercell Interference Issues in WiMAX	p. 227
13.1.3 Relation of the Work in this Book to WiMAX Scheduling	p. 227
13.2 LTE Scheduling Overview	p. 228
13.2.1 Enhancements in the Next Generation of LTE	p. 233
13.2.2 Intercell Interference Issues in LTE	p. 233
13.2.3 Relation of the Work in this Book to LTE Scheduling	p. 234
13.3 SCFDMA Versus OFDMA Scheduling	p. 235
13.3.1 SCFDMA Rate Calculations	p. 236
13.3.2 Scheduling Algorithm with Contiguous RBs	p. 236
13.3.3 Results and Discussion	p. 237
13.4 Comparison to the LTE Power Control Scheme	p. 240
13.4.1 LTE Multicell Interference Mitigation Schemes	p. 241
13.4.2 Results and Discussion	p. 242
13.5 Summary	p. 245
Chapter 14 Future Research Directions	p. 247
14.1 Resource Allocation with Multiple Service Classes	p. 247
14.2 Network MIMO	p. 247
14.3 Coalitional Game Theory	p. 248
14.4 Resource Allocation with Femtocells	p. 249
14.5 Green Networks and Self-Organizing Networks	p. 249
14.6 Joint Uplink/Downlink Resource Allocation	p. 250
14.7 Joint Resource Allocation in Heterogeneous Networks	p. 251
14.8 Resource Allocation in Cognitive Radio Networks	p. 252
Bibliography	p. 255
Index	p. 269

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