Energy Harvesting Wireless Communications

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.

• 1 Introduction 11.1 Energy Harvesting Models and Constraints 11.2 Structure of the Book 3Part I Energy Harvesting Wireless Transmission 52 Power Allocation for Point-to-Point Energy Harvesting Channels 72.1 A General Utility Optimization Framework for Point-to-Point EH Channels 82.2 Throughput Maximization for Gaussian Channel with EH Transmitter 92.2.1 The Case with Noncausal ESIT 102.2.1.1 Staircase Power Allocation to Problem (2.7) 102.2.1.2 Efficient Algorithm to Solve Problem (12.7) 112.2.2 The Case with Causal ESIT 152.2.2.1 Dynamic Programming 152.3 Throughput Maximization for Fading Channel with EH Transmitter 172.3.1 The Case with Noncausal CSIT and ESIT 182.3.1.1 Water-Filling Power Allocation 182.3.1.2 Staircase Water-Filling Power Allocation 192.3.1.3 Efficient Implementation of Staircase Water-Filling Algorithm 222.3.2 The Case with Causal CSIT and ESIT 232.3.2.1 Dynamic Programming 242.3.2.2 Heuristic Online Solutions 272.3.3 Other ESIT and CSIT Cases 272.4 Outage Probability Minimization with EH Transmitter 292.4.1 The Case with No CSIT and Noncausal ESIT 292.4.1.1 Properties of Outage Probability Function 302.4.1.2 Optimal Offline Power Allocation with M = 1 332.4.1.3 Suboptimal Power Allocation with M = 1 352.4.1.4 Optimal Power Allocation for the General Case of M > 1 362.4.1.5 Suboptimal Offline Power Allocation with M > 1 402.4.2 The Case with No CSIT and Causal ESIT 412.4.2.1 Optimal Online Power Allocation 422.4.2.2 Suboptimal Online Power Allocation 432.4.3 Numerical Results 442.4.3.1 The Case of M = 1 442.4.3.2 The Case of M > 1 442.4.4 Other CSIT and ESIT Cases 472.5 Limited Battery Storage 482.5.1 Throughput Maximization over Gaussian Channel with Noncausal ESIT 482.5.2 Throughput Maximization over Fading Channels with Noncausal CSIT and ESIT 522.5.3 Other Cases 552.6 Imperfect Circuits 562.6.1 Practical Power Consumption for Wireless Transmitters 562.6.2 The Case with Noncausal ESIT 582.6.2.1 Problem Reformulation 592.6.2.2 Single-Block Case with M = 1 602.6.2.3 General Multi-Block Case with M ≥ 1 612.6.3 The Case with Causal ESIT 642.7 Power Allocation with EH Receiver 662.7.1 Power Consumption Model for a Wireless Receiver 662.7.2 The Case with Only EH Receiver 682.7.3 The Case with Both EH Transmitter and EH Receiver 702.8 Summary 703 Power Allocation for Multi-node Energy Harvesting Channels 753.1 Multiple-Access Channels 753.1.1 System Model 753.1.2 Problem Formulation 763.1.3 The Optimal Offline Scheme 783.1.4 Optimal Sum Power Allocation 783.1.4.1 Optimal Rate Scheduling 803.1.5 The Online Scheme 843.1.5.1 Competitive Analysis 843.1.5.2 The Greedy Scheme 853.1.6 Numerical Results 873.2 Relay Channels 913.2.1 System Model 923.2.2 Problem Formulation 943.2.2.1 Delay-Constrained Case 943.2.2.2 No-Delay-Constrained Case 953.2.3 Optimal Solution for the Delay-Constrained Case 973.2.3.1 Monotonic Power Allocation 973.2.3.2 The Case with Direct Link 993.2.3.3 The Case Without Direct Link 1043.2.4 Optimal Solution for the No-Delay-Constrained Case 1063.2.4.1 Optimal Source Power Allocation 1063.2.4.2 Optimal Relay Power Allocation 1093.2.4.3 Optimal Rate Scheduling 1113.2.4.4 Throughput Comparison: DC versus NDC 1123.2.5 Numerical Results 1133.3 Large Relay Networks 1153.3.1 System Model and Assumptions 1153.3.2 Average Throughput for Threshold-Based Transmissions 1173.3.2.1 Threshold-Based Transmission 1173.3.2.2 Markov Property of the Transmission Scheme 1183.3.3 Transmission Threshold Optimization 1203.3.3.1 Convexification via Randomization 1203.3.3.2 State-DependentThreshold Optimization 1223.3.3.3 State-Oblivious Transmission Threshold 1233.3.4 Numerical Results 1243.4 Summary 1254 Cross-Layer Design for Energy Harvesting Links 1274.1 Introduction 1274.2 Completion Time and Delay Minimization 1284.2.1 Completion Time Minimization 1284.2.1.1 Offline Optimum 1294.2.1.2 Online Settings 1304.2.1.3 Preliminaries on Competitive Analysis 1314.2.2 A 2-Competitive Online Algorithm 1314.2.3 Game-Theoretic Analysis on the Completion Time Minimization 1344.2.3.1 The Action Set of the Nature 1344.2.3.2 The Action Set of the Transmitter 1364.2.3.3 Two-Person Zero-Sum Game 1374.2.3.4 Discussions 1404.2.4 Delay-Optimal Energy Management 1424.2.4.1 Formulation 1424.2.4.2 Offline Analysis 1424.2.4.3 Online Analysis 1434.3 Traffic-Aware Base Station Sleeping in Renewable Energy-Powered Cellular Networks 1444.3.1 System Model of a Renewable Energy-Powered Cellular Network 1444.3.1.1 Power Consumption Model 1444.3.1.2 Traffic Model 1454.3.1.3 Channel Model 1464.3.2 Blocking Probability Analysis 1474.3.2.1 Service Blocking Probability 1474.3.2.2 Relation Between P(b)G and ;;(b) 1494.3.2.3 Overall Blocking Probability 1494.3.3 Power Grid Energy Minimization 1504.3.3.1 Problem Formulation 1504.3.3.2 Optimal DP Algorithm 1514.3.3.3 Two-Stage DP Algorithm 1534.3.3.4 Heuristic Algorithms 1554.3.4 Numerical Simulations 1564.3.4.1 Single-Cell Case 1574.3.4.2 3-Sector Case 1584.4 Summary 163Part II Energy Harvesting Network Optimization 1675 Energy Harvesting Ad Hoc Networks 1695.1 Distributed Opportunistic Scheduling 1695.1.1 System Model 1695.1.2 Transmission Scheduling 1715.1.2.1 Problem Formulation 1715.1.2.2 Optimal Stopping Rule for Constant EH Model 1755.1.2.3 Optimal Stopping Rule for i.i.d. EH Model 1795.1.3 Battery Dynamics 1805.1.3.1 Battery with Constant EH Model 1805.1.3.2 Battery with i.i.d. EH Model 1835.1.4 Computation of the Optimal Throughput 1845.1.5 Numerical Results 1845.2 Multiuser Gain Analysis 1875.2.1 System Model 1875.2.2 Centralized Access 1885.2.2.1 Fixed TDMA 1895.2.2.2 Energy-Greedy Access 1915.2.3 Distributed Access 1965.2.4 Numerical Analysis and Discussions 1995.3 Summary 2006 Cost-Aware Design for Energy Harvesting Powered Cellular Networks 2036.1 Introduction 2036.2 Energy Supply and Demand of Cellular Systems 2056.3 Energy Cooperation 2076.3.1 Aggregator-Assisted Energy Trading 2076.3.2 Aggregator-Assisted Energy Sharing 2086.4 Communication Cooperation 2096.4.1 Cost-Aware Traffic Offloading 2106.4.2 Cost-Aware Spectrum Sharing 2106.4.3 Cost-Aware Coordinated Multipoint (CoMP) 2116.5 Joint Energy and Communication Cooperation 2116.5.1 A Case Study 2126.6 Joint Aggregator-Assisted Energy Trading and CoMP 2146.7 Joint Aggregator-Assisted Energy Sharing and CoMP 2266.7.1 System Model 2266.7.2 Optimal Solution 2306.7.3 Numerical Results 2326.8 Extensions and Future Directions 2356.9 Summary 2367 Energy Harvesting in Next-Generation Cellular Networks 2397.1 Introduction 2397.2 Energy Harvesting Hyper-cellular Networks 2407.2.1 System Model 2407.2.1.1 HCNs with Hybrid Energy Supply 2407.2.1.2 Traffic and Channel Model 2417.2.1.3 Power Consumption Model 2427.2.1.4 Green Energy Supply Model 2437.2.2 Analysis of Power Supply and Demand 2447.2.2.1 Energy Queue Analysis 2447.2.2.2 Outage Probability Analysis 2457.2.3 Optimization in the Single-SBS Case 2487.2.3.1 Single HSBS 2487.2.3.2 Single-RSBS Case 2507.2.4 Optimization in the Multi-SBS Case 2537.2.4.1 Problem Formulation 2537.2.4.2 SBS Reactivation and TEATO Scheme 2547.2.5 Simulation Results 2557.2.5.1 Power Saving Gain of the Single-SBS Case 2557.2.5.2 Network Power Saving Gain 2577.3 Proactive Content Caching and Push with Energy Harvesting-Based Small Cells 2597.3.1 Network Architecture and Proactive Service Provisioning 2607.3.1.1 Exploiting the Content and Energy Timeliness 2617.3.1.2 Energy Harvesting-Based Caching and Push: A Simple Policy Design Example 2637.3.2 Policy Optimization for Content Push 2657.3.2.1 Model for Content Push at the Energy Harvesting-Based SBS 2667.3.2.2 Optimal Policy with Finite Battery Capacity 2687.3.2.3 MDP Problem Formulation and Optimization 2697.3.2.4 Threshold-Based Policies 2727.3.2.5 Numerical Results 2797.4 Summary 283Part III Appendices 287A Convex Optimization 289B Markov Decision Process 297C Optimal Stopping Theory 307Index 315