Cache-enabling UAV Communications: Network Deployment and Resource Allocation

TL;DR

This paper presents a joint optimization framework for UAV deployment, caching, and user association in cache-enabled UAV-assisted networks to enhance user experience and reduce content access delay.

Contribution

It introduces a low complexity iterative algorithm that effectively optimizes UAV deployment, caching, and user association, outperforming benchmark algorithms.

Findings

The proposed algorithm approaches exhaustive search performance.

It converges within several iterations.

It improves MOS, reduces delay, and offloads backhaul traffic.

Abstract

In this article, we investigate the content distribution in the hotspot area, whose traffic is offloaded by the combination of the unmanned aerial vehicle (UAV) communication and edge caching. In cache-enabling UAV-assisted cellular networks, the network deployment and resource allocation are vital for quality of experience (QoE) of users with content distribution applications. We formulate a joint optimization problem of UAV deployment, caching placement and user association for maximizing QoE of users, which is evaluated by mean opinion score (MOS). To solve this challenging problem, we decompose the optimization problem into three sub-problems. Specifically, we propose a swap matching based UAV deployment algorithm, then obtain the near-optimal caching placement and user association by greedy algorithm and Lagrange dual, respectively. Finally, we propose a low complexity iterative algorithm for the joint UAV deployment, caching placement and user association optimization, which achieves good computational complexity-optimality tradeoff. Simulation results reveal that: i) the MOS of the proposed algorithm approaches that of the exhaustive search method and converges within several iterations; and ii) compared with the benchmark algorithms, the proposed algorithm achieves better performance in terms of MOS, content access delay and backhaul traffic offloading.