Beamforming of simultaneous wireless Energy and Information Transmission System Based on Reinforcement Learning

Abstract

In the simultaneous wireless information and energy power transmission system, the system uses the same radio frequency signal to transmit information and energy simultaneously, which can be effectively used for self-sustaining operation of wireless devices. In practical applications, the power splitting method can realize simultaneous wireless information and energy transmission between base station and multi-user. Different user systems have different energy consumption, so users with insufficient power need more energy transmission for power supplement. At present, the beamforming strategy of simultaneous wireless information and energy transmission does not consider the problem of insufficient power at the user end. This paper presents a simultaneous wireless energy and information transmission system based on Reinforcement learning (RL) beamforming mechanism for power splitting. The reinforcement learning (Q-learning) algorithm adopts the e-greedy strategy. The beamforming design is optimized by feedback of power information at the user end to increase energy transmission for users with insufficient power. The transmission power is optimized by minimizing the signal-to-interference-noise ratio (SINR) and energy harvesting constraints using channel state information and node power information of each node, and the simulation analysis is carried out.