Preference-Aware Utility Optimization for Cache-Aided Ultra-Dense Relay Networks: A Matching Perspective

Abstract

In order to deal with the surge of data traffic, the caches of the nodes in a wireless network can be utilized in efficient ways. This paper investigates the utility optimization for cache-aided ultra-dense relay networks (CUDRNs) by a preference-aware caching and stable matching scheme. First, we divide the nodes, which may act as a user or a relay, into multiple clusters, and perform optimization strategy within the clusters. Second, the file caching scheme is designed by taking user preference and file popularity into account. Third, according to the performances of the file caching scheme, the optimal power bought from the relay to maximize the utility of the user is derived by an iterative algorithm, and the mutual preference matrices between the users and relays by the maximum utility criterion is established. Then, we propose a user-relay stable matching (SM) strategy by exploring the Gale- Shapley (GS) algorithm. Simulation results demonstrate that the proposed algorithm can bring significant performance improvements compared with the conventional algorithms.