PSO-Based UAV Deployment and Dynamic Power Allocation for UAV-Enabled Uplink NOMA Network

• Published in: Wireless communications and mobile computing Vol. 2021; no. 1
• Main Authors: Abdel-Razeq, Sharief, Shakhatreh, Hazim, Alenezi, Ali, Sawalmeh, Ahmad, Anan, Muhammad, Almutiry, Muhannad
• Format: Journal Article
• Language: English
• Published: Oxford Hindawi 2021; John Wiley & Sons, Inc
• Subjects: Algorithms; Cellular communication; Communication; Data collection; Efficiency; Ergodic processes; Genetic algorithms; Heuristic methods; Line of sight; Nonorthogonal multiple access; Optimization; Particle swarm optimization; Radio equipment; Unmanned aerial vehicles; Wireless networks
• ISSN: 1530-8669; 1530-8677; 1530-8677
• DOI: 10.1155/2021/2722887

Recently, unmanned aerial vehicles (UAVs) have been used as flying base stations (BSs) to take advantage of line-of-sight (LOS) connectivity and efficiently enable fifth-generation (5G) and cellular network coverage and data rates. On the other hand, nonorthogonal multiple access (NOMA) is a promising technique to help achieve unprecedented requirements by simultaneously allowing multiple users to send data over the same resource block. In this paper, we study a UAV-enabled uplink NOMA network, where the UAV collects data from ground users while flying at a certain altitude. Unlike all existing work on this topic, this study consists of two stages. In the first stage, we use the well-known Particle Swarm Optimization (PSO) algorithm, which is a metaheuristic algorithm, to deploy the UAV in 3D space, so that the users’ sum pathlosses are minimized. In the second stage, we investigate the user pairing problem and propose a dynamic power allocation technique for determining the user’s power allocation coefficients, as well as a closed-form equation for the ergodic sum-rate. Results show our PSO-based algorithm prevailing over the Genetic Algorithm (GA) and random deployment methods. The proposed dynamic power allocation strategy maximizes the network’s ergodic sum-rate and outperforms the fixed power allocation strategy. Additionally, the results reveal that the best pairing scheme is the one that keeps uniform channel gain difference in the same pair.