Analysis and Optimization of Caching in Fog Radio Access Networks

Abstract

Caching is a promising approach to address the backhaul traffic congestion problem and boost throughput in fog radio access networks. In this correspondence paper, we investigate a proactive probabilistic caching optimization in wireless fog radio access network where multiple users request different files from multiple base stations (BSs). To assess the performance, we first derive the analytical results of successful transmission probability (STP) using tools of stochastic geometry. With the derived closed-form STP expressions, our objective is to optimize the proactive probabilistic caching distribution to maximize the STP. To reduce the computational complexity, we specially discuss the optimization in high signal-to-noise ratio (SNR). We propose a projection gradient method to get a local optimal solution. Simulation results show that the caching placement optimized by our proposed algorithm increases the STP by about $18\%$ over the best existing caching distribution when ${\rm SNR}=10$ dB with user density $\lambda _u=0.09$ , BS density $\lambda _b=0.1$ and file number $N=100$ .