Wireless RF Energy Transfer in the Massive IoT Era

Onel L. A. López is a Researcher at the University of Oulu, Finland. His research focuses on wireless communications, including energy harvesting setups, and efficient access techniques for massive, machine-type communications.Hirley Alves, D.Sc., is Assistant Professor on Machine-type Wireless Communications at the University of Oulu, Finland. His research focuses on massive connectivity and ultra-reliable low latency communications for future wireless networks.

• Preface ixAcknowledgments xiAcronyms xiiMathematical Notation xviAbout the Companion Website xviii1 Massive IoT 11.1 Selected Use-cases and Scenarios 41.2 Key Technologies 61.3 Requirements and KPIs 101.4 Key Enablers 121.4.1 Holistic and Globally Scalable Massive IoT 121.4.2 Sustainable Connectivity 131.5 Final Remarks and Discussions 172 Wireless RF Energy Transfer: An Overview 202.1 Energy Harvesting 202.1.1 EH Sources 202.1.2 RF Energy Transfer 222.2 RF–EH Performance 242.2.1 Analytical Models 242.2.2 State-of-the-art on RF EH 262.3 RF–EH IoT 302.3.1 Architectures of IoT RF EH Networks 302.3.2 Green WET 312.3.3 WIT-WET Layouts 322.3.4 RF EH in IoT Use Cases 322.4 Enabling Efficient RF-WET 352.4.1 Energy Beamforming 352.4.2 CSI-limited Schemes 352.4.3 Distributed Antenna System 372.4.4 Enhancements in Hardware and Medium 372.4.5 New Spectrum Opportunities 392.4.6 Resource Scheduling and Optimization 402.4.7 Distributed Ledger Technology 412.5 Final Remarks 413 Ambient RF EH 433.1 Motivation and Overview 433.1.1 Hybrid of RF–EH and Power Grid 453.1.2 Energy Usage Protocols 463.1.3 On Efficient Ambient RF–RH Designs 483.2 Measurement Campaigns 513.2.1 Greater London (2012) 523.2.2 Diyarbakir (2014) 523.2.3 Flanders (2017-2019) 533.2.4 Other Measurements 543.3 Energy Arrival Modeling 553.3.1 Based on Arbitrary Distributions 563.3.2 Based on Stochastic Geometry 563.4 A Stochastic Geometry-based Study 573.4.1 System Model and Assumptions 573.4.2 Energy Coverage Probability 593.4.3 Average Harvested Energy 623.4.4 Meta-distribution of Harvested Energy 633.4.5 Numerical Results 643.5 Final Considerations 674 Efficient Schemes for WET 684.1 EH from Dedicated WET 684.2 Energy Beamforming 684.2.1 Low-complexity EB Design 714.2.2 CSI-limited Energy Beamforming 744.2.3 Performance Analysis 764.3 CSI-free Multi-antenna Techniques 804.3.1 System Model and Assumptions 814.3.2 Positioning-agnostic CSI-free WET 824.3.3 Positioning-aware CSI-free WET 944.4 On the Massive WET Performance 964.5 Final Considerations 985 Multi-PB Massive WET 995.1 On the PBs Deployment 995.1.1 Positioning-aware Deployments 995.1.2 Positioning-agnostic Deployments 1045.2 Multi-antenna Energy Beamforming 1095.2.1 Centralized Energy Beamforming 1105.2.2 Distributed Energy Beamforming 1115.2.3 Available RF Energy 1115.3 Distributed CSI-free WET 1135.3.1 SA, AA–IS and RPS–EMW 1135.3.2 AA–SS 1145.3.3 RAB 1175.3.4 Positioning-aware CSI-free Schemes 1185.3.5 Numerical Examples 1185.4 On the Deployment Costs 1205.5 Final Remarks 1236 Wireless-powered Communication Networks 1256.1 WPCN Models 1256.2 Reliable Single-user WPCN 1276.2.1 Harvest-then-transmit (HTT) 1276.2.2 Allowing Energy Accumulation 1306.2.3 HTT versus FEIPC 1356.3 Multi-user Resource Allocation 1396.3.1 Signal Model 1406.3.2 Problem Formulation 1416.3.3 Optimization Framework 1426.3.4 TDMA versus SDMA 1436.4 Cognitive MAC 1456.4.1 Time Sharing and Scheduling 1486.4.2 MAC Protocol at the Device Side 1506.4.3 MAC Protocol at the HAP Side 1516.5 Final Remarks 1527 Simultaneous Wireless Information and Power Transfer 1557.1 SWIPT Schemes 1557.2 Separate EH and ID Receivers 1567.2.1 Problem Formulation 1577.2.2 Optimal Solution 1587.2.3 Performance Results 1597.3 Co-located EH and ID Receivers 1607.3.1 Time Switching 1627.3.2 Power splitting 1657.3.3 TS versus PS 1677.4 Enablers for Efficient SWIPT 1717.4.1 Waveform Optimization 1717.4.2 Multicarrier SWIPT 1747.4.3 Cooperative Relaying 1757.4.4 Interference Exploitation 1767.4.5 Artificial Intelligence 1777.5 Final Considerations 1778 Final Notes 1798.1 Summary 1798.2 Future Research Directions 182A A Brief Overview on Finite Block Length Coding 187A.1 Finite Block Length Model 187B Distribution of Transferred RF Energy Under CSI-free WET 191B.1 Proof of Theorem 4.2 191B.2 Proof of Theorem 4.4 192C Clustering Algorithms 198C.1 Partitioning Methods 198C.1.1 K-Means 199C.1.2 K-Medoids 199C.1.3 K-Modes 199C.2 Hierarchical Methods 200C.3 Other Methods 200C.4 Pre-processing 201D Required SNR for a Target Decoding Error Probability (Proof of Theorem 6.1) 202D.1 On the Convergence of Algorithm 3 203Bibliography 205Index 226