POWER CONTROL AND RESOURCE ALLOCATION FOR DELAY

168 Pages·2009·2 MB·English

POWER CONTROL AND RESOURCE ALLOCATION FOR DELAY-CONSTRAINED
COMMUNICATIONS
By
XIAOCHEN LI
A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL
OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT
OF THE REQUIREMENTS FOR THE DEGREE OF
DOCTOR OF PHILOSOPHY
UNIVERSITY OF FLORIDA
2009
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(cid:176)c 2009 Xiaochen Li
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To my beloved parents and dear husband
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ACKNOWLEDGMENTS
First of all, my special gratitude goes to my advisor, Professor Dapeng Oliver Wu, for
his great inspiration and excellent guidance throughout this dissertation and my Ph.D.
education at UFL. His enthusiasm and deep thoughts spark my interest in academic
research. I am grateful to him for his insightful guidance and strict training on creative
thinking, rigorous analyzing, and effective writing skills.
My deeply appreciation goes to my committee members: Professor Liuqing Yang,
Janise McNair and Shigang Chen, for their interest in my work and the valuable feedbacks
on my research. I would like to thank Professor Jianbo Gao. I have learnt a lot from his
signal processing classes and elaborately designed course projects. I would like to thank
Professor P. Oscar Boykin for many useful discussions about the queueing theory. I would
like to thank my Master advisor Professor Bingli Jiao, he guided me into the world of
wireless communications.
I would like to thank my lab-mates in the Multimedia Communications and
Networking Laboratory (MCN) here in UF. I am fortunate to be a member of this friendly
and family-like group. I would like to thank Xihua Dong, for the helpful discussions on
the research and cooperation of many papers; Bing Han, Wenxing Ye, Jun Xu, Zhifeng
Chen, Taoran Lu, Yiran Li, Yunzhao Li, and my senior lab-mate Dr. Jieyan Fan, for
their constant supports and sincere friendship, and I cherish every minute we have spent
together; Shanshan Ren, Ziyi Wang and Lin Zhang, for hosting the parties and adding the
element of fun to my Ph.D. life. I have spent wonderful four years in Gainesville. Without
them, it is not even possible. I would also like to thank Zongrui Ding, Lei Yang, Qian
Chen, Jiangping Wang, Yakun Hu, Qin Chen, Qing Wang, Youngho Jo and Chris Paulson.
Wish you all have success in your Ph.D. studies.
I would like to thank my parents for the endless love and constant support they’ve
provided during my whole life. Thanks for the encouragement for every tiny progress
that I have ever made. Without them, I would have never been able to accomplish what
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I had today. Last but not the least I would like to thank my husband, Dr. Hongbing
Cheng, for his deep love, understanding and support, both academically and morally. His
encouragement is my best stimulus.
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TABLE OF CONTENTS
page
ACKNOWLEDGMENTS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
LIST OF TABLES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
LIST OF FIGURES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
ABSTRACT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
CHAPTER
1 INTRODUCTION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
1.1 Wireless Fading Channels . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
1.2 Related Works on Delay-Constrained Communications . . . . . . . . . . . 19
1.2.1 Physical Layer Model . . . . . . . . . . . . . . . . . . . . . . . . . . 21
1.2.2 Link-PHY layer Model . . . . . . . . . . . . . . . . . . . . . . . . . 25
1.3 Outline of the Dissertation . . . . . . . . . . . . . . . . . . . . . . . . . . . 32
2 HIERARCHICAL QUEUE-LENGTH-AWARE POWER CONTROL . . . . . . 35
2.1 System Description . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 36
2.1.1 Structure of Data Source and Transmitter . . . . . . . . . . . . . . 36
2.1.2 Markov Chain Model . . . . . . . . . . . . . . . . . . . . . . . . . . 37
2.2 Hierarchical Queue-Length-Aware Power Control Scheme . . . . . . . . . . 39
2.2.1 Hierarchical Queue-Length-Aware Power Control Scheme . . . . . . 41
2.2.2 Steady State Queue Length Distribution . . . . . . . . . . . . . . . 42
2.2.3 Average Power . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45
2.2.4 Effective Capacity with Power Control . . . . . . . . . . . . . . . . 47
2.2.5 Peak Power Constraint . . . . . . . . . . . . . . . . . . . . . . . . . 47
2.3 Simulation Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49
2.3.1 Steady State Queue Length Distribution . . . . . . . . . . . . . . . 49
2.3.2 Effective Capacity . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50
2.3.3 Power Gain in 3G Environment . . . . . . . . . . . . . . . . . . . . 52
2.3.4 HQLA with Adaptive Modulation . . . . . . . . . . . . . . . . . . . 55
2.3.5 Peak Power Constraint . . . . . . . . . . . . . . . . . . . . . . . . . 57
2.4 Steady State Analysis for Variable-Rate Arrival Process and Correlated
Channel . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57
2.4.1 Correlated channel . . . . . . . . . . . . . . . . . . . . . . . . . . . 57
2.4.2 Variable-Rate Arrival Process . . . . . . . . . . . . . . . . . . . . . 61
2.5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64
3 QOS-DRIVEN POWER ALLOCATION FOR MULTI-CHANNEL COMMUNICATIONS
UNDER OUTDATED CHANNEL SIDE INFORMATION . . . . . . . . . . . . 65
3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65
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3.2 System Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67
3.3 Optimal Power Allocation Scheme . . . . . . . . . . . . . . . . . . . . . . . 68
3.4 Suboptimal Power Allocation Scheme . . . . . . . . . . . . . . . . . . . . . 71
3.5 Simulation Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75
3.6 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76
4 JOINT POWER AND CHANNEL ALLOCATION IN WIRELESS NETWORKS 79
4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79
4.2 Reference Channel Approach . . . . . . . . . . . . . . . . . . . . . . . . . . 80
4.3 System Description . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81
4.4 Simulation Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87
4.4.1 Simulation Setting . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87
4.4.2 Performance Evaluation . . . . . . . . . . . . . . . . . . . . . . . . . 89
4.5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92
5 JOINT QUEUE-LENGTH-AWARE POWER CONTROL . . . . . . . . . . . . 93
5.1 System Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96
5.2 Separate QLA Power Control . . . . . . . . . . . . . . . . . . . . . . . . . 102
5.3 Joint QLA Power Control . . . . . . . . . . . . . . . . . . . . . . . . . . . 106
5.4 Structure Of The Optimal Power Control Scheme . . . . . . . . . . . . . . 113
5.4.1 Convexity of the Objective Function . . . . . . . . . . . . . . . . . . 114
5.4.2 Solution for the Constraint-Relaxed Optimization Problem . . . . . 116
5.4.3 Only One Negative Column in pˆ . . . . . . . . . . . . . . . . . . . 118
i,j
5.4.4 Arbitrary Number of Negative Columns in pˆ . . . . . . . . . . . . 123
i,j
5.4.5 Structure of the Optimal Power Control Scheme . . . . . . . . . . . 124
5.5 Simulation Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125
5.5.1 SQLA Power Control . . . . . . . . . . . . . . . . . . . . . . . . . . 125
5.5.2 JQLA Power Control . . . . . . . . . . . . . . . . . . . . . . . . . . 127
5.6 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 129
6 POWER CONTROL WITH ADAPTIVE MODULATION . . . . . . . . . . . . 134
6.1 Adaptive Modulation Overview . . . . . . . . . . . . . . . . . . . . . . . . 135
6.2 Adaptive Modulation in Cross Layer Design . . . . . . . . . . . . . . . . . 137
6.3 JQLA with Adaptive Modulation . . . . . . . . . . . . . . . . . . . . . . . 138
6.4 Simulation Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 141
6.5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 143
7 CONCLUSIONS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 147
APPENDIX . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 150
A PROOFS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 150
A.1 Proof of Lemma 3.1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 150
A.2 Proof of Lemma 3.2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 151
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A.3 Proof of Lemma 5.1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 152
A.4 Proof of Lemma 5.2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 153
A.5 Proof of Lemma 5.3 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 154
A.6 Proof of Lemma 5.4 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 155
A.7 Proof of Lemma 5.5 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 157
A.8 Proof of Lemma 5.6 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 157
A.9 Proof of Lemma 5.7 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 158
A.10 Proof of Lemma 5.8 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 159
REFERENCES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 160
BIOGRAPHICAL SKETCH . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 168
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LIST OF TABLES
Table page
2-1 Parameters for 3G environment simulation. . . . . . . . . . . . . . . . . . . . . . 53
2-2 Parameters for 3G environment simulation with adaptive modulation. . . . . . . 56
3-1 Comparison of computational complexity. . . . . . . . . . . . . . . . . . . . . . 75
5-1 Configuration of f(g). . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103
5-2 Constructing p∗ from pˆ . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 124
i,j i,j
5-3 Constructing y∗ from yˆ . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 126
j j
5-4 Simulation parameters for SQLA. . . . . . . . . . . . . . . . . . . . . . . . . . . 127
5-5 Simulation results. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 127
5-6 Simulation parameters for JQLA. . . . . . . . . . . . . . . . . . . . . . . . . . . 128
5-7 Simulation results for JQLA. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 129
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LIST OF FIGURES
Figure page
1-1 Type of fading channels. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
1-2 Physical layer and link-PHY layer system models . . . . . . . . . . . . . . . . . 20
2-1 Structure of data source and transmitter. . . . . . . . . . . . . . . . . . . . . . . 37
2-2 Update of the queue length. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39
2-3 Markov property of the queue length. . . . . . . . . . . . . . . . . . . . . . . . . 39
2-4 Hierarchical queue-length-aware power control scheme. . . . . . . . . . . . . . . 41
2-5 Hierarchical queue-length-aware power control scheme with peak power constraint. 41
2-6 Probability mass function of HQLA/CONST. . . . . . . . . . . . . . . . . . . . 50
2-7 Probability mass function of HQLA/TDWF. . . . . . . . . . . . . . . . . . . . . 51
2-8 Delay bound violation probability of HQLA/TDWF. . . . . . . . . . . . . . . . 51
2-9 Effective capacity of HQLA/CONST. . . . . . . . . . . . . . . . . . . . . . . . . 52
2-10 Effective capacity of HQLA/TDWF. . . . . . . . . . . . . . . . . . . . . . . . . 52
2-11 Effective capacity of HQLA/OPT. . . . . . . . . . . . . . . . . . . . . . . . . . . 53
2-12 Power gain of HQLA/CONST over CONST PC. . . . . . . . . . . . . . . . . . . 54
2-13 Power gain of HQLA/TDWF over TDWF PC. . . . . . . . . . . . . . . . . . . . 54
2-14 Power gain of HQLA/TCI over TCI PC. . . . . . . . . . . . . . . . . . . . . . . 55
2-15 Power gain of HQLA/TCI over TCI PC with adaptive modulation, voice data. . 56
2-16 D vs. average power with fixed µ and (cid:178). . . . . . . . . . . . . . . . . . . . . 57
max
2-17 Delay bound violation probability at 20mph. . . . . . . . . . . . . . . . . . . . . 60
2-18 Delay bound violation probability at 80mph. . . . . . . . . . . . . . . . . . . . . 60
2-19 An example of variable-rate arrival process. . . . . . . . . . . . . . . . . . . . . 62
2-20 Queue length distribution of TCI PC with variable-rate arrival process. . . . . . 63
2-21 Queue length violation probability of TCI PC with variable-rate arrival process. 63
3-1 System diagram. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68
3-2 Effect of CSI delay on the effective capacity. . . . . . . . . . . . . . . . . . . . . 77
10