Work

Maximizing energy efficiency through joint resource optimization in NOMA-assisted UAV-enabled next-generation wireless networks

Year: 2025

Type: article

Abstract: Conventional base stations (BS) often face limitations in providing consistent communication services, particularly in remote or congested areas. Unmanned Aerial Vehicles (UAVs) have emerged as a promising solution to assist BS in expanding coverage and improving service quality. However, the primary challenge with UAVs lies in their limited battery life, which restricts flight time and overall efficiency. To address this, non-orthogonal multiple access (NOMA) is a promising technique that can significantly improve the energy efficiency (EE) of the network. In this paper, we first formulate a joint resource optimization problem to maximize EE while ensuring quality of service (QoS) constraints. Then, a low-complexity heuristic solution is presented to address a nonlinear, nonconvex, and NP-hard problem by optimizing the key parameters, including user pairing (UP), UAV altitude (UA), and power allocation (PA). The simulation results show that our proposed solution outperforms benchmark schemes, achieving 23.07% higher EE than random pairing and 28.67% higher EE than the worst-case pairing scenario.

Source: Cluster Computing

DOI: 10.1007/s10586-025-05244-w

Authors: Rahat Ullah, Mubashar Sarfraz, Muhammad Farhan Sohail, Sheraz Alam, Sajjad A. Ghauri, Nauman Anwar Baig

Institutions: National University of Modern Languages, Isra University, Robert Gordon University

Language: English

Topic: UAV Applications and Optimization

Subfield: Aerospace Engineering

Field: Engineering

Domain: Physical Sciences

SDGs: Industry, innovation and infrastructure, Affordable and clean energy

Open Access status: hybrid

Estimated APC paid: $3,190