Gain Without Pain: Recycling Reflected Energy From Wireless-Powered RIS-Aided Communications

In this article, we investigate and analyze energy recycling for a reconfigurable intelligent surface (RIS)-aided wireless-powered communication network. As opposed to the existing works where the energy harvested by Internet of Things (IoT) devices only comes from the power station, IoT devices are also allowed to recycle energy from other IoT devices. In particular, we propose group switching- and user switching-based protocols with time-division multiple access to evaluate the impact of energy recycling on the system performance. Two different optimization problems are, respectively, formulated for maximizing the sum throughput by jointly optimizing the energy beamforming vectors, the transmit power, the transmission time, the receive beamforming vectors, the grouping factors, and the phase-shift matrices, where the constraints of the minimum throughput, the harvested energy, the maximum transmit power, the phase shift, the grouping, and the time allocation are taken into account. In light of the intractability of the above problems, we, respectively, develop two alternating optimization-based iterative algorithms by combining the successive convex approximation method and the penalty-based method to obtain corresponding suboptimal solutions. Simulation results verify that the energy recycling-based mechanism can assist in enhancing the performance of IoT devices in terms of energy harvesting and information transmission. Besides, we also verify that the group switching-based algorithm can obtain more sum throughput of IoT devices, and the user switching-based algorithm can harvest more energy.

I. Introduction

The development and popularization of Internet of Things (IoT) technologies has greatly facilitated the information-processing capabilities of IoT devices, a variety of IoT devices, such as controllers, sensors, actuators, and communication devices, have substantially promoted the implementation of remote adaptation and configuration, digital twins, and device collaborative operation [1], [2]. However, the limited energy supply has become a major bottleneck in restricting the communication performance of IoT devices due to the increased energy consumption and the limited battery size of IoT devices. Frequent battery replacement and redeployment will greatly increase the cost and are also extremely difficult in extreme environments [3]. How to charge these energy-limited devices in a green and low-carbon way is an imminent issue.