Simultaneous Lightwave Information and Power Transfer With Optical IRS Under Time-Varying Traffic: A Lyapunov Optimization Perspective

Abstract

The evolution of 6G networks is expected to support data-intensive applications, which impose energy demands on communication systems. In this paper, to address the challenge of sustainable power supply under dynamic traffic conditions, the integration of simultaneous lightwave information and power transfer (SLIPT) with optical intelligent reflecting surfaces (OIRS) is explored. Leveraging the large unlicensed spectrum of visible light communication (VLC), SLIPT offers a promising solution for combined high-speed data transmission and wireless power transfer. Specifically, we investigate adaptive resource allocation for the OIRS-aided SLIPT system, where the objective is to minimize the average total energy consumption under time-varying traffic. Therefore, a Lyapunov drift-plus-penalty method is utilized to transform the original problem and ensure system stability under stochastic traffic. To address the non-convex problem, a block coordinate descent framework is applied to decouple it into four sub-problems. First, the service association sub-problem is tackled by the Kuhn-Munkres algorithm; second, the power allocation is optimized via sequential convex programming; third, the power splitting factor is similarly derived; and finally, the OIRS configuration is updated via a minorization-maximization algorithm. Simulation results verify the convergence and effectiveness of the proposed algorithm, showing that the integration of OIRS significantly reduces the energy consumption while maintaining stable data transmission and energy supply. These findings highlight the potential of OIRS-aided SLIPT to provide sustainable and adaptive co-design of energy and information for future optical communication systems.