Work

Energy Consumption Minimization for UAV-Assisted Network in Hotspot Area

Year: 2025

Type: article

Abstract: Unmanned aerial vehicles (UAVs) play a crucial role in enhancing network coverage and capacity, especially in areas with high user density or limited infrastructure. This paper proposes an effective UAV-assisted offloading framework to minimize the energy consumption of both users and UAVs in an air-to-ground (A2G) network. First, UAVs are deployed by jointly considering the user distribution and guaranteeing the quality of service (QoS) of users. Further, user association, power control, and bandwidth allocation are jointly optimized, aiming to minimize the power consumption of users. Considering user mobility, the positions of UAVs are continuously refined using the double deep Q-network (DDQN) algorithm to reduce the weighted energy consumption of users and UAVs. Simulation results show that the proposed algorithm has better performance in reducing the total energy consumption compared with benchmark schemes.

Source: Drones

DOI: 10.3390/drones9030178

Authors: Jinxi Zhang, Saidiwaerdi Maimaiti, Weidong Gao, Kaisa Zhang

Institutions: Capital University of Physical Education and Sports, Xinjiang Institute of Engineering, Kashi University, Beijing University of Posts and Telecommunications

Language: English

Topic: UAV Applications and Optimization

Subfield: Aerospace Engineering

Field: Engineering

Domain: Physical Sciences

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

Open Access status: gold

Estimated APC paid: $3,137