Content Caching for Heterogeneous Small-Cell Networks with Intelligent Content Access

Abstract

To realize content caching at base stations (BSs), a caching system fetches contents to the appropriate base stations in advance then it uses the fetched contents to serve end users in the serving phase. This paper studies a caching problem for heterogeneous small-cell networks with QoS-aware and adaptive BS association where end users can be associated with either small-cell or macro-cell BSs. Toward this end, we derive the cache miss ratio for general caching strategy based on which we formulate a caching problem which aims at minimizing the cache miss ratio. To solve this problem, we propose two algorithms, namely Sparse Network Caching (SNC) and Two-Stage Caching (TSC) algorithms. We prove that the SNC algorithm can obtain the optimal caching solution as the request rate to each BS is much smaller than its serving capability. Numerical results demonstrate that the SNC algorithm performs well in the sparse network scenario while the TSC algorithm operates efficiently in all studied scenarios. Moreover, the proposed algorithms significantly outperform the random caching (RDC) and most popular caching (MPC) algorithms.