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Energy Harvesting Wireless Communications

IEEE Press 1. Aufl.

von: Chuang Huang, Sheng Zhou, Jie Xu, Zhisheng Niu, Rui Zhang, Shuguang Cui
117,99 €
Verlag:	Wiley
Format:	PDF
Veröffentl.:	07.12.2018
ISBN/EAN:	9781119295976
Sprache:	englisch
Anzahl Seiten:	336

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Titelbeschreibung

Energy Harvesting Wireless Communications offers a review of the most current research as well as the basic concepts, key ideas and powerful tools of energy harvesting wireless communications. Energy harvesting is both renewable and cheap and has the potential for many applications in future wireless communication systems to power transceivers by utilizing environmental energy such as solar, thermal, wind, and kinetic energy. The authors—noted experts in the field—explore the power allocation for point-to-point energy harvesting channels, power allocation for multi-node energy harvesting channels, and cross-layer design for energy harvesting links. In addition, they offer an in-depth examination of energy harvesting network optimization and cover topics such as energy harvesting ad hoc networks, cost aware design for energy harvesting assisted cellular networks, and energy harvesting in next generation cellular networks.

Inhaltsverzeichnis

1 Introduction 1 1.1 Energy Harvesting Models and Constraints 1 1.2 Structure of the Book 3 Part I Energy Harvesting Wireless Transmission 5 2 Power Allocation for Point-to-Point Energy Harvesting Channels 7 2.1 A General Utility Optimization Framework for Point-to-Point EH Channels 8 2.2 Throughput Maximization for Gaussian Channel with EH Transmitter 9 2.2.1 The Case with Noncausal ESIT 10 2.2.1.1 Staircase Power Allocation to Problem (2.7) 10 2.2.1.2 Efficient Algorithm to Solve Problem (12.7) 11 2.2.2 The Case with Causal ESIT 15 2.2.2.1 Dynamic Programming 15 2.3 Throughput Maximization for Fading Channel with EH Transmitter 17 2.3.1 The Case with Noncausal CSIT and ESIT 18 2.3.1.1 Water-Filling Power Allocation 18 2.3.1.2 Staircase Water-Filling Power Allocation 19 2.3.1.3 Efficient Implementation of Staircase Water-Filling Algorithm 22 2.3.2 The Case with Causal CSIT and ESIT 23 2.3.2.1 Dynamic Programming 24 2.3.2.2 Heuristic Online Solutions 27 2.3.3 Other ESIT and CSIT Cases 27 2.4 Outage Probability Minimization with EH Transmitter 29 2.4.1 The Case with No CSIT and Noncausal ESIT 29 2.4.1.1 Properties of Outage Probability Function 30 2.4.1.2 Optimal Offline Power Allocation with M = 1 33 2.4.1.3 Suboptimal Power Allocation with M = 1 35 2.4.1.4 Optimal Power Allocation for the General Case of M > 1 36 2.4.1.5 Suboptimal Offline Power Allocation with M > 1 40 2.4.2 The Case with No CSIT and Causal ESIT 41 2.4.2.1 Optimal Online Power Allocation 42 2.4.2.2 Suboptimal Online Power Allocation 43 2.4.3 Numerical Results 44 2.4.3.1 The Case of M = 1 44 2.4.3.2 The Case of M > 1 44 2.4.4 Other CSIT and ESIT Cases 47 2.5 Limited Battery Storage 48 2.5.1 Throughput Maximization over Gaussian Channel with Noncausal ESIT 48 2.5.2 Throughput Maximization over Fading Channels with Noncausal CSIT and ESIT 52 2.5.3 Other Cases 55 2.6 Imperfect Circuits 56 2.6.1 Practical Power Consumption for Wireless Transmitters 56 2.6.2 The Case with Noncausal ESIT 58 2.6.2.1 Problem Reformulation 59 2.6.2.2 Single-Block Case with M = 1 60 2.6.2.3 General Multi-Block Case with M ≥ 1 61 2.6.3 The Case with Causal ESIT 64 2.7 Power Allocation with EH Receiver 66 2.7.1 Power Consumption Model for a Wireless Receiver 66 2.7.2 The Case with Only EH Receiver 68 2.7.3 The Case with Both EH Transmitter and EH Receiver 70 2.8 Summary 70 3 Power Allocation for Multi-node Energy Harvesting Channels 75 3.1 Multiple-Access Channels 75 3.1.1 System Model 75 3.1.2 Problem Formulation 76 3.1.3 The Optimal Offline Scheme 78 3.1.4 Optimal Sum Power Allocation 78 3.1.4.1 Optimal Rate Scheduling 80 3.1.5 The Online Scheme 84 3.1.5.1 Competitive Analysis 84 3.1.5.2 The Greedy Scheme 85 3.1.6 Numerical Results 87 3.2 Relay Channels 91 3.2.1 System Model 92 3.2.2 Problem Formulation 94 3.2.2.1 Delay-Constrained Case 94 3.2.2.2 No-Delay-Constrained Case 95 3.2.3 Optimal Solution for the Delay-Constrained Case 97 3.2.3.1 Monotonic Power Allocation 97 3.2.3.2 The Case with Direct Link 99 3.2.3.3 The Case Without Direct Link 104 3.2.4 Optimal Solution for the No-Delay-Constrained Case 106 3.2.4.1 Optimal Source Power Allocation 106 3.2.4.2 Optimal Relay Power Allocation 109 3.2.4.3 Optimal Rate Scheduling 111 3.2.4.4 Throughput Comparison: DC versus NDC 112 3.2.5 Numerical Results 113 3.3 Large Relay Networks 115 3.3.1 System Model and Assumptions 115 3.3.2 Average Throughput for Threshold-Based Transmissions 117 3.3.2.1 Threshold-Based Transmission 117 3.3.2.2 Markov Property of the Transmission Scheme 118 3.3.3 Transmission Threshold Optimization 120 3.3.3.1 Convexification via Randomization 120 3.3.3.2 State-DependentThreshold Optimization 122 3.3.3.3 State-Oblivious Transmission Threshold 123 3.3.4 Numerical Results 124 3.4 Summary 125 4 Cross-Layer Design for Energy Harvesting Links 127 4.1 Introduction 127 4.2 Completion Time and Delay Minimization 128 4.2.1 Completion Time Minimization 128 4.2.1.1 Offline Optimum 129 4.2.1.2 Online Settings 130 4.2.1.3 Preliminaries on Competitive Analysis 131 4.2.2 A 2-Competitive Online Algorithm 131 4.2.3 Game-Theoretic Analysis on the Completion Time Minimization 134 4.2.3.1 The Action Set of the Nature 134 4.2.3.2 The Action Set of the Transmitter 136 4.2.3.3 Two-Person Zero-Sum Game 137 4.2.3.4 Discussions 140 4.2.4 Delay-Optimal Energy Management 142 4.2.4.1 Formulation 142 4.2.4.2 Offline Analysis 142 4.2.4.3 Online Analysis 143 4.3 Traffic-Aware Base Station Sleeping in Renewable Energy-Powered Cellular Networks 144 4.3.1 System Model of a Renewable Energy-Powered Cellular Network 144 4.3.1.1 Power Consumption Model 144 4.3.1.2 Traffic Model 145 4.3.1.3 Channel Model 146 4.3.2 Blocking Probability Analysis 147 4.3.2.1 Service Blocking Probability 147 4.3.2.2 Relation Between P(b)G and ;;(b) 149 4.3.2.3 Overall Blocking Probability 149 4.3.3 Power Grid Energy Minimization 150 4.3.3.1 Problem Formulation 150 4.3.3.2 Optimal DP Algorithm 151 4.3.3.3 Two-Stage DP Algorithm 153 4.3.3.4 Heuristic Algorithms 155 4.3.4 Numerical Simulations 156 4.3.4.1 Single-Cell Case 157 4.3.4.2 3-Sector Case 158 4.4 Summary 163 Part II Energy Harvesting Network Optimization 167 5 Energy Harvesting Ad Hoc Networks 169 5.1 Distributed Opportunistic Scheduling 169 5.1.1 System Model 169 5.1.2 Transmission Scheduling 171 5.1.2.1 Problem Formulation 171 5.1.2.2 Optimal Stopping Rule for Constant EH Model 175 5.1.2.3 Optimal Stopping Rule for i.i.d. EH Model 179 5.1.3 Battery Dynamics 180 5.1.3.1 Battery with Constant EH Model 180 5.1.3.2 Battery with i.i.d. EH Model 183 5.1.4 Computation of the Optimal Throughput 184 5.1.5 Numerical Results 184 5.2 Multiuser Gain Analysis 187 5.2.1 System Model 187 5.2.2 Centralized Access 188 5.2.2.1 Fixed TDMA 189 5.2.2.2 Energy-Greedy Access 191 5.2.3 Distributed Access 196 5.2.4 Numerical Analysis and Discussions 199 5.3 Summary 200 6 Cost-Aware Design for Energy Harvesting Powered Cellular Networks 203 6.1 Introduction 203 6.2 Energy Supply and Demand of Cellular Systems 205 6.3 Energy Cooperation 207 6.3.1 Aggregator-Assisted Energy Trading 207 6.3.2 Aggregator-Assisted Energy Sharing 208 6.4 Communication Cooperation 209 6.4.1 Cost-Aware Traffic Offloading 210 6.4.2 Cost-Aware Spectrum Sharing 210 6.4.3 Cost-Aware Coordinated Multipoint (CoMP) 211 6.5 Joint Energy and Communication Cooperation 211 6.5.1 A Case Study 212 6.6 Joint Aggregator-Assisted Energy Trading and CoMP 214 6.7 Joint Aggregator-Assisted Energy Sharing and CoMP 226 6.7.1 System Model 226 6.7.2 Optimal Solution 230 6.7.3 Numerical Results 232 6.8 Extensions and Future Directions 235 6.9 Summary 236 7 Energy Harvesting in Next-Generation Cellular Networks 239 7.1 Introduction 239 7.2 Energy Harvesting Hyper-cellular Networks 240 7.2.1 System Model 240 7.2.1.1 HCNs with Hybrid Energy Supply 240 7.2.1.2 Traffic and Channel Model 241 7.2.1.3 Power Consumption Model 242 7.2.1.4 Green Energy Supply Model 243 7.2.2 Analysis of Power Supply and Demand 244 7.2.2.1 Energy Queue Analysis 244 7.2.2.2 Outage Probability Analysis 245 7.2.3 Optimization in the Single-SBS Case 248 7.2.3.1 Single HSBS 248 7.2.3.2 Single-RSBS Case 250 7.2.4 Optimization in the Multi-SBS Case 253 7.2.4.1 Problem Formulation 253 7.2.4.2 SBS Reactivation and TEATO Scheme 254 7.2.5 Simulation Results 255 7.2.5.1 Power Saving Gain of the Single-SBS Case 255 7.2.5.2 Network Power Saving Gain 257 7.3 Proactive Content Caching and Push with Energy Harvesting-Based Small Cells 259 7.3.1 Network Architecture and Proactive Service Provisioning 260 7.3.1.1 Exploiting the Content and Energy Timeliness 261 7.3.1.2 Energy Harvesting-Based Caching and Push: A Simple Policy Design Example 263 7.3.2 Policy Optimization for Content Push 265 7.3.2.1 Model for Content Push at the Energy Harvesting-Based SBS 266 7.3.2.2 Optimal Policy with Finite Battery Capacity 268 7.3.2.3 MDP Problem Formulation and Optimization 269 7.3.2.4 Threshold-Based Policies 272 7.3.2.5 Numerical Results 279 7.4 Summary 283 Part III Appendices 287 A Convex Optimization 289 B Markov Decision Process 297 C Optimal Stopping Theory 307 Index 315

Autorenportrait

CHUAN HUANG, PHD, is a professor in the National Key Laboratory of Science and Technology on Communications at University of Electronic Science and Technology of China, Chengdu, China. SHENG ZHOU, PHD, is an associate professor in the Department of Electronic Engineering at Tsinghua University, Beijing, China. JIE XU, PHD, is a professor at Guangdong University of Technology, Guangzhou, China. ZHISHENG NIU, PHD, is a professor in the Department of Electronic Engineering at Tsinghua University, Beijing, China. RUI ZHANG, PHD, is an associate professor in the Department of Electrical and Computer Engineering at National University of Singapore, Singapore. SHUGUANG CUI, PHD, is a professor in the Department of Electrical and Computer Engineering at University of California, Davis, USA.

Back cover copy

A COMPREHENSIVE REVIEW OF THE RESEARCH IN THE EMERGENT FIELD OF ENERGY HARVESTING WIRELESS COMMUNICATIONS Energy Harvesting Wireless Communications offers a review of the most current research as well as the basic concepts, key ideas and powerful tools of energy harvesting wireless communications. Energy harvesting is both renewable and cheap and has the potential for many applications in future wireless communication systems to power transceivers by utilizing environmental energy such as solar, thermal, wind, and kinetic energy. The authors—noted experts in the field—explore the power allocation for point-to-point energy harvesting channels, power allocation for multi-node energy harvesting channels, and cross-layer design for energy harvesting links. In addition, they offer an in-depth examination of energy harvesting network optimization and cover topics such as energy harvesting ad hoc networks, cost aware design for energy harvesting assisted cellular networks, and energy harvesting in next generation cellular networks. This important resource: <ul> <li>Brings together in one concise volume the most current research, key concepts, challenges and applications in energy harvesting for wireless transmission and network optimization</li> <li>Offers a variety of energy harvesting models and explores the constraints of them in the optimization of EH wireless communication systems</li> <li>Contains a comprehensive review from leading researchers whose specializations include circuit design, signal processing, communication and information theory, network protocol, traffic engineering, and optimization</li> <li>Provides information into managing randomness in energy supplies, channel fading and traffic load variation</li> </ul> Written for academics, researchers, graduate students, and industry research engineers in electrical, electronic, and computer engineering fields, Energy Harvesting Wireless Communications offers a comprehensive resource to the innovations and technology of energy harvesting wireless communications.