14 citations · 52 across the 8 of their papers we have counts for
9 papers · 1 filter
Decentralized Federated Learning with Unreliable Communications
Hao Ye, Le Liang, Geoffrey Li
Decentralized federated learning, inherited from decentralized learning, enables the edge devices to collaborate on model training in a peer-to-peer manner without the assistance o…
A Lightweight Deep Network for Efficient CSI Feedback in Massive MIMO Systems
Yuyao Sun, Wei Xu, Le Liang +3
To fully exploit the advantages of massive multiple-input multiple-output (m-MIMO), accurate channel state information (CSI) is required at the transmitter. However, excessive CSI…
Deep Learning based Wireless Resource Allocation with Application to Vehicular Networks
Le Liang, Hao Ye, Guanding Yu +1
It has been a long-held belief that judicious resource allocation is critical to mitigating interference, improving network efficiency, and ultimately optimizing wireless communica…
Spectrum Sharing in Vehicular Networks Based on Multi-Agent Reinforcement Learning
Le Liang, Hao Ye, Geoffrey Ye Li
This paper investigates the spectrum sharing problem in vehicular networks based on multi-agent reinforcement learning, where multiple vehicle-to-vehicle (V2V) links reuse the freq…
Deep Learning based End-to-End Wireless Communication Systems with Conditional GAN as Unknown Channel
Hao Ye, Le Liang, Geoffrey Ye Li +1
In this article, we develop an end-to-end wireless communication system using deep neural networks (DNNs), in which DNNs are employed to perform several key functions, including en…
Resource Allocation for Low-Latency Vehicular Communications with Packet Retransmission
Chongtao Guo, Le Liang, Geoffrey Ye Li
Vehicular communications have stringent latency requirements on safety-critical information transmission. However, lack of instantaneous channel state information due to high mobil…