Throughput Performance in D2D Communication Networks: Effects of Power, Density and User Distance

Abstract

Device-to-Device (D2D) communication plays a vital role in enhancing spectral efficiency and data rates in next-generation wireless networks, but interference management and optimal power control remain key challenges. This study aims to address these gaps by developing a modified Power Control Scheme for D2D communication (mPCS-D2D) using a Hierarchical Clustering Algorithm (HCA) to improve throughput while minimizing interference. The scheme combines proximity-based clustering for general D2D users and social relationship-based clustering for mmWave D2D communication. Simulations were conducted to evaluate the throughput performance of mPCS-D2D under varying D2D transmit power levels, user densities, and inter-user distances. Results showed that the proposed scheme significantly outperformed the baseline PCS-D2D model across multiple scenarios. At 10 m and 15 m distances with a pathloss exponent of 4.5, mPCS-D2D improved throughput by 5.15% and 4.42%, respectively. Under varying user densities and pathloss exponents (3.5 and 4.5), throughput gains ranged from 4.33% to 4.77%, while across 10 m, 15 m, and 20 m distances, it achieved improvements of 4.13% to 5.53%. These findings demonstrate that the proposed mPCS-D2D scheme effectively enhances data transmission rates under diverse network conditions. The study concludes that integrating hierarchical clustering into power control mechanisms can significantly improve D2D communication efficiency. The proposed method offers practical implications for designing scalable, interference-aware D2D systems in future wireless networks.