Work

Energy‐Efficient Sparse UAV‐Assisted Networks: Co‐Optimizing Hybrid Transmission Modes and Interference‐Aware Power Allocation

Year: 2025

Type: article

Abstract: ABSTRACT In the context of wide‐area data collection using sensor nodes, unmanned aerial vehicles (UAVs) are frequently employed to assist ground nodes in achieving data backhaul. This paper proposes a joint optimization framework, with the aim of addressing the dynamic selection of transmission schemes, the mutual interference of line‐of‐sight links, and energy constraints in sparse networks comprising UAVs and ground nodes. Firstly, a hybrid transmission mode decision maker is designed using Lyapunov optimization, enabling multi‐hop routing/ferry‐transmission/carry‐forwarding modes to be dynamically assigned according to node locations and data transmission requirements, thereby achieving an online trade‐off between delay and energy consumption. Secondly, the joint interference‐aware power‐distance control algorithm is proposed to enhance the transmission link signal‐to‐noise ratio by 23.6%. Finally, the normalized energy efficiency index is constructed and a decoupled gradient optimization method is designed to achieve Pareto equilibrium between throughput and energy consumption. The simulation results demonstrate that the proposed method can effectively reduce the end‐to‐end delay and improve the system energy efficiency in sparse networks, providing an effective and feasible solution for energy‐constrained UAV‐assisted sparse networks.

Source: Electronics Letters

DOI: 10.1049/ell2.70296

Authors: Qin Zichao, Wang Hai, Qin Zhen

Institutions: PLA Army Engineering University, PAP Non-commissioned Officer School

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: gold

Estimated APC paid: $2,590