Work

Joint Optimization of Multi-UAV Deployment and 3D Positioning in Traffic-Aware Aerial Networks

Year: 2025

Type: conference-paper

Abstract: Unmanned Aerial Vehicles (UAVs) are a promising solution for next-generation wireless networks due to their mobility, rapid deployment, and ability to provide Line-of-Sight (LoS) connectivity. However, deploying multiple UAVs in realtime to meet dynamic, non-uniform traffic demands remains a significant challenge, especially when aiming to optimize network throughput and resource utilization. In this paper, we propose the Efficient Multi-UAV Traffic-Aware Deployment (EMTAD) algorithm, a scalable algorithm that jointly minimizes UAV count and optimizes 3D positioning based on real-time user distribution and traffic demand. In contrast to prior works that assume static user patterns or fixed UAV counts, EMTAD dynamically adapts UAV deployment to maximize spectral efficiency and satisfy userspecific Quality of Service (QoS) requirements. Simulation results demonstrate that EMTAD reduces the number of UAVs required and achieves superior aggregate throughput compared to baseline approaches.

Source: IEEE Virtual Conference on Communications (VCC)

DOI: 10.1109/vcc67261.2025.11351234

Authors: Kamran Shafafi, Alaa Awad Abdellatif, Manuel Ricardo, Rui Campos

Institutions: Universidade do Porto, INESC TEC

Language: English

Topic: UAV Applications and Optimization

Subfield: Aerospace Engineering

Field: Engineering

Domain: Physical Sciences

SDGs: Industry, innovation and infrastructure, Sustainable cities and communities

Open Access status: green

Funders: HORIZON EUROPE Framework Programme, Fundação para a Ciência e a Tecnologia