Probabilistic caching placement in UAV-assisted heterogeneous wireless networks

Abstract

In this paper, we investigate the probabilistic caching placement in a heterogeneous wireless network, where there are several types of Unmanned Aerial Vehicle Base Station (UAV-BS) placed following the independent homogeneous Poisson Point Process (PPP), and each type of UAV-BS has a different cache capacity. We measure the network transmission performance by introducing the average service success probability, which is the probability that each user’s request can be successfully serviced by the nearest UAV-BS among several types. Taking into account stochastic geometry and Zipf distribution as well as the Signal-to-Noise Ratio (SNR) coverage model, we provide the cache hit probability and the successful transmission probability to obtain the average service success probability. The system performance is optimized by maximizing the average service success probability, through optimizing the probability caching placement. As this problem is non-convex in general, and we turn to use Genetic Algorithm (GA) to solve the placement strategy. Numerical and simulation results are provided to demonstrate that the proposed caching placement strategy is superior to the conventional Most Popular Content (MPC) strategy, especially in the high SNR regime. Moreover, we note that when the small-capacity UAV-BS uses the MPC strategy and the large-capacity UAV-BS uses the proposed caching strategy, the sub-optimal result can be obtained with reduced implementation complexity.