Secrecy Energy Efficiency Maximization in RIS-Aided Wireless Networks with Statistical CSI

TL;DR

This paper proposes an optimization algorithm to maximize secrecy energy efficiency in RIS-assisted wireless networks, considering statistical CSI and addressing eavesdropping threats, with demonstrated convergence and performance improvements.

Contribution

It introduces a novel, convergent optimization method for joint power, reflection, and filtering design in RIS-aided networks with statistical CSI.

Findings

The algorithm converges reliably in simulations.

Significant secrecy energy efficiency gains are achieved.

The method effectively mitigates eavesdropping risks.

Abstract

This work studies the problem of secrecy energy efficiency maximization in multi-user wireless networks aided by reconfigurable intelligent surfaces, in which an eavesdropper overhears the uplink communication. A provably convergent optimization algorithm is proposed which optimizes the user's transmit power, metasurface reflection coefficients, and base station receive filters. The complexity of the proposed method is analyzed and numerical results are provided to show the performance of the proposed optimization method.