Performance Analysis of Clustering Algorithms for Content-Sharing Based D2D Enabled 5G Networks

Abstract

5G networks are expected to be content-centric which present various research challenges. Content-Sharing via Device-to-Device (D2D) clustered networks has emerged as a popular approach of alleviating the burden on the 5G network. A novel channel-based clustering algorithm, for grouping the D2D User Equipment (DUEs) sharing a common interest, is proposed in this paper. Performance parameters such as energy consumption of devices and area spectral efficiencies (ASE) are considered for evaluating the performance of the D2D clustered network in a simulation study. The proposed algorithm exhibits better node energy consumptions as compared to several existing clustering algorithms. It also yields better ASE compared to the existing algorithms for various node densities. Effect of the number of clusters on the performance parameters is also discussed.