10 citations · 13 across the 14 of their papers we have counts for
6 papers · 1 filter
Multi-objective Aerial Collaborative Secure Communication Optimization via Generative Diffusion Model-enabled Deep Reinforcement Learning
Chuang Zhang, Geng Sun, Jiahui Li +4
Due to flexibility and low-cost, unmanned aerial vehicles (UAVs) are increasingly crucial for enhancing coverage and functionality of wireless networks. However, incorporating UAVs…
UAV-enabled Collaborative Beamforming via Multi-Agent Deep Reinforcement Learning
Saichao Liu, Geng Sun, Jiahui Li +4
In this paper, we investigate an unmanned aerial vehicle (UAV)-assistant air-to-ground communication system, where multiple UAVs form a UAV-enabled virtual antenna array (UVAA) to…
Collaborative Ground-Space Communications via Evolutionary Multi-objective Deep Reinforcement Learning
Jiahui Li, Geng Sun, Qingqing Wu +4
In this paper, we propose a distributed collaborative beamforming (DCB)-based uplink communication paradigm for enabling ground-space direct communications. Specifically, DCB treat…
Two-Way Aerial Secure Communications via Distributed Collaborative Beamforming under Eavesdropper Collusion
Jiahui Li, Geng Sun, Qingqing Wu +3
Unmanned aerial vehicles (UAVs)-enabled aerial communication provides a flexible, reliable, and cost-effective solution for a range of wireless applications. However, due to the hi…
Multi-objective Optimization for Multi-UAV-assisted Mobile Edge Computing
Geng Sun, Yixian Wang, Zemin Sun +4
Recent developments in unmanned aerial vehicles (UAVs) and mobile edge computing (MEC) have provided users with flexible and resilient computing services. However, meeting the comp…
TJCCT: A Two-timescale Approach for UAV-assisted Mobile Edge Computing
Zemin Sun, Geng Sun, Qingqing Wu +6
Unmanned aerial vehicle (UAV)-assisted mobile edge computing (MEC) is emerging as a promising paradigm to provide aerial-terrestrial computing services in close proximity to mobile…