Clustering technique for dense D2D communication in RIS-aided multicell cellular network

Abstract

Device-to-device (D2D) communication and reconfigurable intelligent surface (RIS) are well-known as two promising technologies for nextgeneration cellular communication networks. D2D users operate on the same spectrum as traditional cellular users, potentially leading to increased interference and reduced efficiency in frequency resource usage. RIS provides a remedy for clearing blocked signals from obstructions by reflecting the desired signals to the intended receiver. However, RIS elements reflect not only the desired signals but also the interference signals. This paper proposes a distance-based clustering method aimed at creating a grouping algorithm for neighboring D2D users using different channels, thereby reducing co-channel interference. The simulation indicates that the proposed clustering method for D2D users' equipment (DUEs) leads to a 0.72 dB increase in signal-to-interference-plus-noise ratio (SINR), enhances throughput to 11.25 Mbps, and reduces the bit error rate by up to 24×10⁻² compared to the baseline system. The study findings also indicate that cellular users' equipment (CUEs) experience satisfactory signal quality, even with the presence of DUEs on the cellular network. Our clustering algorithm is feasible to deploying D2D densely in RIS-aided cellular network without significantly affecting CUE performance.