Maximizing Network Throughput in Heterogeneous UAV Networks

In this paper we study the deployment of an Unmanned Aerial Vehicle (UAV) network that consists of multiple UAVs to provide emergent communication service for people who are trapped in a disaster area, where each UAV is equipped with a base station that has limited computing capacity and power supply, and thus can only serve a limited number of people. Unlike most existing studies that focused on homogeneous UAVs, we consider the deployment of heterogeneous UAVs where different UAVs have different computing capacities. We study a problem of deploying $K$ heterogeneous UAVs in the air to form a temporarily connected UAV network such that the network throughput– the number of users served by the UAVs, is maximized, subject to the constraint that the number of people served by each UAV is no greater than its service capacity. We then propose a novel $O\left({\sqrt {\frac {s}{K}}}\right)$ -approximation algorithm for the problem, where $s$ is a given positive integer with $1 \le s\le K$ , e.g., $s=3$ . We also devise an improved heuristic, based on the approximation algorithm. We finally evaluate the performance of the proposed algorithms. Experimental results show that the numbers of users served by UAVs in the solutions delivered by the proposed algorithms are increased by 25% than state-of-the-arts.

I. Introduction

Terrestrial LTE base stations usually are statically deployed. However, this static deployment limits their usage in key 5G and 5G Beyond applications with surging traffic demands at some hotspot locations (e.g., battlefields and concerts). In addition, the deployed base stations may have been destroyed in natural disasters, e.g., earthquakes, tsunamis, flooding, etc. Emergent communication service are definitely needed for rescue teams to rescue people trapped in disaster areas [9], [19].