Wireless Power Transfer for Future Networks: Signal Processing, Machine Learning, Computing, and Sensing

Abstract

Wireless power transfer (WPT) is an emerging paradigm that will enable using wireless to its full potential in future networks, not only to convey information but also to deliver energy. Such networks will enable trillions of future low-power devices to sense, compute, connect, and energize anywhere, anytime, and on the move. The design of such future networks brings new challenges and opportunities for signal processing, machine learning, sensing, and computing so as to make the best use of the RF radiations, spectrum, and network infrastructure in providing cost-effective and realtime power supplies to wireless devices and enable wirelesspowered applications. In this paper, we first review recent signal processing techniques to make WPT and wireless information and power transfer (WIPT) as efficient as possible. Topics include high-power amplifier and energy harvester nonlinearities, active and passive beamforming, intelligent reflecting surfaces, receive combining with multi-antenna harvester, modulation, coding, waveform, large-scale (massive) multiple-input multipleoutput (MIMO), channel acquisition, transmit diversity, multiuser power region characterization, coordinated multipoint, and distributed antenna systems. Then, we overview two different design methodologies: the model and optimize approach relying on analytical system models, modern convex optimization, and communication/information theory, and the learning approach based on data-driven end-to-end learning and physics-based learning. We discuss the pros and cons of each approach, especially when accounting for various nonlinearities in wireless-powered networks, and identify interesting emerging opportunities for the approaches to complement each other. Finally, we identify new emerging wireless technologies where WPT may play a key role-wireless-powered mobile edge computing and wirelesspowered sensing-arguing WPT, communication, computation, and sensing must be jointly designed.

Massive MIMO With Radio Stripes for Indoor Wireless Energy Transfer

“…Radio frequency (RF) wireless energy transfer (WET) constitutes an appealing technology to be further researched, developed and exploited for powering IoT deployments [1]- [4]. Different from near-field WET solutions as those exploiting induction, magnetic resonance coupling and piezoelectricity phenomena, and energy harvesting (EH) from other energy sources, RF-WET allows: i) small-form factor, ii) native multiuser support, and iii) relatively long range energy coverage.…”

“…Recent works on WET have mainly targeted extremely lowpower/cost IoT applications, e.g., wireless sensor networks and RFIDs, due to the ultra-low PTE (see [1] and references therein). However, several promising technologies such as i) energy beamforming and waveform optimization [4]- [7], ii) distributed [8], [9] and massive antenna [9]- [15] systems, iii) smart reflect arrays and reconfigurable metasurfaces [16], iv) motor-equipped power beacons (PBs) [17], flying PBs [18], PBs with rotary antennas [7]), and v) mobile computation offloading and crowd sensing [4], may broaden WET applicability, and turn it plausible for powering more energyhungry IoT devices, e.g., smartphones, game console controllers, electronic toys. In this work, we leverage some of above enablers to investigate WET's feasibility for powerhungry indoor charging.…”

Closed-Loop Wireless Power Transfer with Adaptive Waveform and Beamforming: Design, Prototype, and Experiment

“…Another and complementary research area to increase the output dc power is to design efficient WPT signals [26], [27]. One promising signal strategy is the waveform.…”

Residual Energy Estimation-Based MAC Protocol for Wireless Powered Sensor Networks

“…Recent advances in radio frequency (RF)-based wireless energy transfer (WET) techniques enable battery-powered sensor devices to receive energy remotely without time and space constraints on ambient resources such as solar, thermal, wind, and vibration, enabling perpetual operations. Thus, wireless sensor networks (WSNs) with RF-based WETwireless powered sensor networks (WPSNs)-are considered one of the most promising technologies for a sustainable Internet of Things [1][2][3][4][5][6][7][8][9]. In the WPSN, a power station wirelessly transfers energy to sensor devices that use the harvested energy to transmit their collected information to a fusion center [10][11][12].…”