Abstract
Radio frequency wireless energy transfer (WET) is a promising solution for powering autonomous Internet of Things (IoT) deployments. In this work, we leverage energy beamforming for powering multiple user equipments (UEs) with stringent energy harvesting (EH) demands in an indoor distributed massive multiple-input multiple-output system. Based on semi-definite programming, successive convex approximation (SCA), and maximum ratio transmission (MRT) techniques, we derive optimal and sub-optimal precoders aimed at minimizing the radio stripes' transmit power while exploiting information of the power transfer efficiency of the EH circuits at the UEs. Moreover, we propose an analytical framework to assess and control the electromagnetic field (EMF) radiation exposure in the considered indoor scenario. Numerical results show that i) the EMF radiation exposure can be more easily controlled at higher frequencies at the cost of a higher transmit power consumption, ii) training is not a very critical factor for the considered indoor system, iii) MRT/SCA-based precoders are particularly appealing when serving a small number of UEs, thus, especially suitable for implementation in a time domain multiple access (TDMA) scheduling framework, and iv) TDMA is more efficient than spatial domain multiple access (SDMA) when serving a relatively small number of UEs. Results suggest that additional boosting performance strategies are needed to increase the overall system efficiency, thus making the technology viable in practice.
Highlights
The expected massive number of “Internet of Things” (IoT) devices coming online over the decade is conditioned on first solving critical challenges, especially in terms of efficient massive access, lightweight communication protocols, and sustainable powering mechanisms
A) Scenario Geometry: We consider a room with dimensions 6 × 6 × 3 m3, where the radio stripes system is assumed at the ceiling level, i.e., zap = G = 3 m
We derived optimal and sub-optimal precoders based on SDP, SCA and MRT that aim to minimize the radio stripes’ transmit power subject to stringent EH requirements per UE, while exploiting channel state information (CSI) and information of the power transfer efficiency (PTE) of the EH circuits
Summary
Radio frequency (RF) wireless energy transfer (WET) constitutes an appealing technology to be further researched, developed and exploited for powering IoT deployments [1]–[4]. The ultra-low end-to-end power transfer efficiency (PTE) of WET systems, together with strict regulations on the electromagnetic field (EMF) radiation, are critical factors that may limit WET feasibility in practice. By addressing these challenges, while exploiting further advancements on ultra-low-power integrated circuits, WET may emerge as a revolutionary technology that will cut the “last wires” (i.e., cables for energy recharging [3]) for a truly wireless and autonomous connectivity.
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