Interference-Aware Path Planning Optimization for Multiple UAVs in Beyond 5G Networks

Abstract

Integrating unmanned aerial vehicles (UAVs) as flying base stations (FBSs) is expected to be an important architectural element in the beyond 5G/6G mobile wireless networks. A key operational aspect in UAV-aided 5G/6G networks is the UAV path optimization (or trajectory planning as it is also commonly referred to). In this paper, we address this problem using a mixed integer linear programming (MILP) formulation for FBS path optimization in terms of traveling time considering co-channel interference and time windows in serving ground users (GUs) at cluster points (CPs) for constructing the multiple UAV paths in both a single-cell and a multi-cell wireless network. In the proposed technique, we assume that all FBSs depart and return to a single depot, which is considered to be a terrestrial 5G/6G base station (BS). The novelty of the proposed solution compared to previous techniques is that we take explicitly into account the interference under the unit disk graph (UDG) model to create interference-aware UAV’s trajectory. Numerical investigations reveal that the proposed interference-aware path optimization approaches improve the overall performance of the network up to approximately 21% in terms of throughput for the FBSs. Notably, these gains come with an unnoticeable increase in the total completion time, which is comparable to well-known previously proposed solutions. Additionally, the proposed heuristic algorithms provide competitive decision making with low underlying computational complexity rendering them amenable for real-time implementation.