Deep Reinforcement Learning based Secure Wireless Communication with
Self-powered Intelligent Reflecting Surface
Abstract
This paper addresses a multiple-input, single-output (MISO) downlink
secure wireless communication system assisted by an intelligent
reflecting surface (IRS). Instead of employing a conventional IRS model
that requires an external power supply, we consider a self-powered IRS
to achieve extra resource efficiency. Our goal is to design a
beamforming vector at the transmitter side and phase shifters for the
IRS that maximize the secrecy rate while assuring seamless IRS operation
via energy harvesting (EH). Since the considered optimization cannot be
solved analytically, we propose to utilize deep reinforcement learning
(DRL). Numerical results verify that the proposed DRL-based solution
outperforms the conventional relaxed convex optimization approach in
both secrecy and energy harvesting perspectives.