Matching With Peer Effects for Context-Aware Resource Allocation in D2D Communications

Abstract

In this letter, we investigate the context-aware resource allocation for device-to-device communications accounting for the quality-of-service requirements and priorities of different applications based on users’ requests. We formulate a context-aware optimization problem and implement the matching theory to solve the problem. We propose a novel algorithm where the device-to-device user equipments and resource blocks act as two opposite sets of players and interact with each other to obtain the optimal matching. We analytically prove that the algorithm converges to a two-sided exchange stability within limited number of swap operations. We also demonstrate that the proposed algorithm significantly outperforms the context-unaware resource allocation algorithm by around 62.2%.