Bio-Inspired Optimization for RIS-Aided SWIPT Toward Crisis-Resilient Communications
TL;DR
Numerical results demonstrate that the proposed FFA-based approach achieves significant transmit power savings and outperforms conventional alternating optimization techniques in both solution quality and scalability.
Abstract
This paper investigates a reconfigurable-intelligent-surface (RIS)-aided simultaneous-wireless-information-and-power-transfer (SWIPT) system, which can be utilized in crisis-resilient scenarios. Specifically, a passive RIS is deployed to facilitate both data transmission for information users (IUs), e.g., the response team, and wireless power delivery for energy devices (EDs), e.g., wireless sensors and wearable devices. In the considered RIS-assisted SWIPT system, the active beamforming vectors at the base station and the passive phase-shift vectors at the RIS are jointly optimized with the objective of minimizing the total transmit power subject to three critical constraints: i) guaranteeing quality-of-service requirements of the IUs to ensure reliable communications, ii) satisfying the required power demands of EDs for uninterrupted operation, and iii) preserving the passive characteristics of the RIS. The resulting optimization problem is non-convex and multivariate, rendering it NP-hard. To address this challenge, a bio-inspired firefly algorithm (FFA) is developed to obtain near-optimal solutions. Numerical results demonstrate that the proposed FFA-based approach achieves significant transmit power savings and outperforms conventional alternating optimization techniques in both solution quality and scalability.