Active elements for Hybrid Relay-Reflecting Intelligent Surface-assisted secrecy wireless communications: A Jaya-based optimization approach

Abstract

This work addresses optimizing active elements in Hybrid Relay-Reflecting Intelligent Surface (HR-RIS) systems to enhance both the sum and secrecy rates in communication networks facing eavesdropping threats. We present a new strategy that overcomes the drawbacks of traditional approaches by utilizing the HR-RIS framework’s Jaya optimization process. Using a population-based search strategy that maintains a balance between exploration and exploitation, the Jaya method effectively tackles complex solution spaces to find global solutions while avoiding obvious local optima, in contrast to traditional strategies. Additionally, we present a dynamic optimization method that adapts to shifting power levels, eavesdropper locations, and user positions. This improves the sum rate while strengthening security by maximizing the Signal-to-Interference-plus-Noise Ratio (SINR) and minimizing signal leakage. We further derive a closed-form expression for Strictly Positive Secrecy Capacity (SPSC) to assess secrecy performance compared to state-of-the-art techniques. Simulation results validate the proposed method’s effectiveness in optimizing HR-RIS active elements across diverse scenarios, examining the effects of different RIS element counts, edge node (EN) antenna configurations, and the spatial positioning of users and eavesdroppers. This investigation demonstrates a noticeable enhancement in the security and sum rate performance, demonstrating the HR-RIS strategy based on Jaya as a powerful tool for efficient and secure wireless communications systems.