On the Feasibility of Wireless Energy Transfer Using Massive Antenna Arrays

Abstract

Abstract-We illustrate potential benefits of using massive antenna arrays for wireless energy transfer (WET). Specifically, we analyze probability of outage in WET over fading channels when a base station (BS) with multiple antennas beamforms energy to a wireless sensor node (WSN). Our analytical results show that by using massive antenna arrays, the range of WET can be increased for a given target outage probability. We prove that by using multiple-antenna arrays at the BS, a lower downlink energy is required to get the same outage performance, resulting into savings of radiated energy. We show that for energy levels used in WET, the outage performance with least-squares or minimum mean-square error channel estimates is same as that obtained based on perfect channel estimates. We observe that a strong line-of-sight component between the BS and WSN lowers outage probability. Furthermore, by deploying more antennas at the BS, a larger energy can be transferred reliably to the WSN at a given target outage performance for the sensor to be able to perform its main tasks. In our numerical examples, the RF power received at the input of the sensor is assumed to be on the order of a mW, such that the rectenna operates at an efficiency in the order of 50%.Index Terms-Wireless energy transfer, massive MIMO, beamforming, outage probability, array gain I. INTRODUCTION Wireless energy transfer (WET) is a promising energy harvesting technology where the destination node harvests energy from electromagnetic radiations instead of traditional wired energy sources [3]. The use of WET can help increase the battery-lifetime of energy-constrained wireless sensor nodes (WSNs) that are used for applications such as intelligent transportation, intrusion detection, and aircraft structural monitoring [4]. Furthermore, WET can be used to charge low power devices such as temperature and humidity meters and liquid crystal displays [5]. Even low-end computation, sensing, and communication can be performed by harvesting energy from ambient radio frequency (RF) signals including TV, cellular networks, and Wi-Fi transmissions [6].However, there are several challenges that must be addressed in order to implement WET. Firstly, only a small fraction of the energy radiated by an energy transmitter can be harvested by the WSN which severely limits the range of WET [4], [7]. Secondly, the received power levels that are suitable for wireless information transfer are not suitable for energy transfer, where the absolute received power is of interest and not the signal-to-noise ratio (SNR).

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