Max-Min Secrecy Rate and Secrecy Energy Efficiency Optimization for RIS-Aided VLC Systems: RSMA Versus NOMA

TL;DR

This paper investigates joint optimization of power, RIS configuration, and orientation in RIS-aided VLC systems to enhance security and energy efficiency, comparing RSMA and NOMA schemes with a genetic algorithm approach.

Contribution

It introduces two frameworks for maximizing secrecy rate and energy efficiency in VLC systems using joint optimization of multiple parameters, considering RSMA and NOMA schemes.

Findings

RSMA outperforms NOMA in secrecy rate and energy efficiency.

The proposed genetic algorithm effectively finds high-quality solutions.

Insights on the effects of system parameters on performance are provided.

Abstract

Integrating VLC with the RIS significantly enhances physical layer security by enabling precise directional signal control and dynamic adaptation to the communication environment. These capabilities strengthen the confidentiality and security of VLC systems. This paper presents a comprehensive study on the joint optimization of VLC AP power allocation, RIS association, and RIS elements orientation angles for secure VLC systems, while considering RSMA and power-domain NOMA schemes. Specifically, two frameworks are proposed to maximize both the minimum secrecy rate (SR) and the minimum secrecy energy efficiency (SEE) by jointly optimizing power allocation, RIS association, and RIS elements orientation angles for both power-domain NOMA and RSMA-based VLC systems. The proposed frameworks consider random device orientation and guarantee the minimum user-rate requirement. The proposed optimization frameworks belong to the class of mixed integer nonlinear programming, which has no known feasible solution methodology to guarantee the optimal solution. Moreover, the increased degree of freedom and flexibility from the joint consideration of power control, RIS association and element orientation results in a large set of decision variables and constraints, which further complicates the optimization problem. To that end, we utilize a genetic algorithm-based solution method, which through its exploration and exploitation capabilities can obtain a good quality solution. Additionally, comprehensive simulations show that the RSMA scheme outperforms the power-domain NOMA scheme across both the SR and SEE metrics over various network parameters. Furthermore, useful insights on the impact of minimum user rate requirement, number of RIS elements, and maximum VLC AP transmit power on the minimum SR and SEE performances are provided.