8 citations · 14 across the 2 of their papers we have counts for
Showing eess.SPShow all
3 papers · 1 filter
eess.SP2020★ 8 cited
Multi-Agent Deep Reinforcement Learning Based Trajectory Planning for Multi-UAV Assisted Mobile Edge Computing
Liang Wang, Kezhi Wang, Cunhua Pan +3
An unmanned aerial vehicle (UAV)-aided mobile edge computing (MEC) framework is proposed, where several UAVs having different trajectories fly over the target area and support the…
eess.SP2019
Deep Reinforcement Learning Based Dynamic Trajectory Control for UAV-assisted Mobile Edge Computing
Liang Wang, Kezhi Wang, Cunhua Pan +3
In this paper, we consider a platform of flying mobile edge computing (F-MEC), where unmanned aerial vehicles (UAVs) serve as equipment providing computation resource, and they ena…
eess.SP2019
Learn to Compress CSI and Allocate Resources in Vehicular Networks
Liang Wang, Hao Ye, Le Liang +1
Resource allocation has a direct and profound impact on the performance of vehicle-to-everything (V2X) networks. In this paper, we develop a hybrid architecture consisting of centr…