Resource Management in UAV-Assisted 5G/6G Networks with Mobile Edge Computing

Description :

This project aims to develop resource management approaches for UAV-assisted 5G/6G networks with integrated mobile edge computing (MEC). In temporary high-demand scenarios (e.g., concerts or championship events), a fleet of UAVs will be deployed to reinforce cellular coverage and capacity while enabling edge computation offloading for user devices. The research focuses on two core dimensions: (1) radio resource allocation and power control for UAV-base stations to maximize network throughput and coverage, and (2) computational task offloading from ground users to UAV-mounted MEC servers to reduce application latency. These dimensions will be addressed jointly, balancing the trade-offs among data throughput, end-to-end latency, and UAV energy consumption. We will design centralized and distributed approaches leveraging combinatorial optimization, game theory, swarm intelligence, reinforcement learning, and heuristics.

Titulaire :
HELOU (EL) Melhem

Contact USJ :
melhem.helou@usj.edu.lb

Chercheur(s) :
M. Melhem HELOU (EL)

Projet présenté au CR, le : 01/01/2026

Projet achevé auprès du CR : 31/12/2028