Abstract-Wireless energy transfer (WET) has attracted significant attention recently for delivering energy to electrical devices without the need of wires or power cables. In particular, the radio frequency (RF) signal enabled far-field WET is appealing to power energy-constrained wireless networks in a broadcast manner. To overcome the significant path loss over wireless channels, multi-antenna or multiple-input multiple-output (MIMO) techniques have been proposed to enhance both the transmission efficiency and range for RF-based WET. However, in order to reap the large energy beamforming gain in MIMO WET, acquiring the channel state information (CSI) at the energy transmitter (ET) is an essential task. This task is particularly challenging for WET systems, since existing channel training and feedback methods used for communication receivers may not be implementable at the energy receiver (ER) due to its hardware limitation. To tackle this problem, we consider in this paper a multiuser MIMO WET system, and propose a new channel learning method that requires only one feedback bit from each ER to the ET per feedback interval. Specifically, each feedback bit indicates the increase or decrease of the harvested energy by each ER in the present as compared to the previous intervals, which can be measured without changing the existing structure of the ER. Based on such feedback information, the ET adjusts transmit beamforming in subsequent training intervals and at the same time obtains improved estimates of the MIMO channels to different ERs by applying an optimization technique called analytic center cutting plane method (ACCPM). For the proposed ACCPM based channel learning algorithm, we analyze its worst-case convergence, from which it is revealed that the algorithm is able to estimate multiuser MIMO channels at the same time without reducing the analytic convergence speed. Furthermore, through extensive simulations, we show that the proposed algorithm outperforms existing one-bit feedback based channel learning schemes in terms of both convergence speed and energy transfer efficiency, especially when the number of ERs becomes large. Index Terms-Wireless energy transfer (WET), multiple-input multiple-output (MIMO), energy beamforming, channel learning, one-bit feedback, analytic center cutting plane method (ACCPM).
In REF , the authors investigate energy harvesting (EH) with an one-bit feedback, where every receiver only reports whether the harvested energy in the current time interval is larger than that of the previous interval, and the transmitter estimates the channel using analytic center cutting plane method.
Energy Beamforming with One-Bit Feedback
ArXiv
ArXiv
Mathematics Computer Science