Multi-UAV deployment for NOMA-enabled wireless networks based on IMOGWO algorithm

In this article, we address the multi-unmanned aerial vehicle (UAV) deployment problem in the presence of co-channel interference (CCI) for non-orthogonal multiple access (NOMA) enabled wireless networks. Considering UAV as aerial base station for downlink communication, we aim to maximize the energy efficiency and coverage rate by jointly optimizing the power allocation of users and the locations of UAVs. Initially, the ground users are divided into clusters by K-means clustering, where each UAV serves a cluster. Then, the clusters are further divided into multiple sub-clusters, each having a pair of near and far users. Orthogonal multiple access (OMA) is applied among sub-clusters, and NOMA is applied to intra sub-cluster users. Lastly, to tackle the formulated multi-objective non-convex problem, we propose an improved multi-objective grey wolf optimizer (IMOGWO) to maintain an optimal trade-off between energy efficiency and coverage rate. Simulation results demonstrate that the proposed algorithm outperforms the benchmarks. © 2022 Elsevier GmbH