Secrecy Energy Efficiency in RIS-Assisted Networks

Abstract

This paper investigates the secrecy energy efficiency (SEE) performance in the reconfigurable intelligent surface (RIS)-assisted multi-user multiple-input-single-output (MISO) networks. An SEE maximization problem is formulated by optimizing the beamforming vectors and the phase shift coefficients. The considered problem is separated into two subproblems and solved by an alternating optimization based algorithm, where each subproblem is handled by the successive convex approximation (SCA) method. A second order cone programming is designed to initiated the proposed algorithm. Numerical results validate the proposed algorithm, which is shown to be more computational efficient than the benchmark algorithm. Besides, the employment of the RIS is shown to greatly enhance the SEE.