Multiple RIS-aided DF relaying for vehicular communication systems: a performance analysis
TL;DR
Simulation results demonstrate that the proposed multi-RIS-assisted DF relaying cooperative scheme significantly outperforms both the DF-only and multi-RIS-only schemes, and system performance improves as the number of RIS reflecting elements increases, in line with the law of diminishing marginal returns.
Abstract
This paper addresses the issue of outdated channel state information (CSI) caused by the coupling between Doppler frequency shift and CSI feedback delay in high-mobility internet of vehicles (IoV) scenarios. It establishes a multi-reconfigurable intelligent surface (RIS)-assisted decode-and-forward (DF) relaying communication system model for IoV and introduces a first-order auto-regressive (AR1) channel model to characterise the correlation between the estimated CSI and the actual channel. It also proposes a dynamic RIS selection mechanism. Under generalised-k fading channels, approximate closed-form expressions are derived for the system outage probability, bit error rate (BER) and ergodic capacity based on the statistical properties of the end-to-end signal-to-noise ratio. Furthermore, the problem of maximising system energy efficiency is formulated subject to constraints on total transmit power, minimum transmission rate and BER. Block coordinate descent and a phase matching technique are then employed to obtain a closed-form solution for the RIS phase shifts. The original problem is subsequently decoupled into a one-dimensional power allocation problem. Based on this, analytical solutions are derived for the piecewise stationary points and the feasible region pruning criterion via the Lambert W function. Simulation results demonstrate that, under outdated CSI conditions, the proposed multi-RIS-assisted DF relaying cooperative scheme significantly outperforms both the DF-only and multi-RIS-only schemes. Additionally, system performance improves as the number of RIS reflecting elements increases, in line with the law of diminishing marginal returns.