Many-to-many matching for social-aware minimized redundancy caching in D2D-enabled cellular networks

To relieve the heavy data transmission pressure caused by duplicate requests from user equipments (UEs) on base stations (BSs), edge caching is envisioned as an effective method to help BSs for traffic offloading. In D2D networks, pre-cache the various files for mobile users is a crucial issue to improve the network performance. Therefore, an effective cache placement scheme is necessary to reduce cache redundancy and capacity waste. In this paper, the cache placement problem is investigated for cache redundancy reduction. Considering that users' mobility has a non-negligible impact on the system performance, we model the users' mobility as a continuous-time Markov chain (CTMC) in which the user's encounter probability is estimated using the historical contact time and inter-contact time among users. Then, the contact intensity and the interest similarity are modeled to represent social relationship intensity among users. Integrating the users' mobility with the social relationship, a social relationship graph is constructed. Subsequently, we formulate the file placement problem as a many-to-many matching problem and we propose a novel file placement algorithm to make decisions on cache placement based on the social relationship graph with low computational complexity and low caching redundancy. Simulation results show that the proposed algorithm can achieve better performance compared with the existing caching placement schemes under the limited storage capacity.