10 citations · 37 across the 8 of their papers we have counts for
9 papers
Coded Stochastic ADMM for Decentralized Consensus Optimization with Edge Computing
Hao Chen, Yu Ye, Ming Xiao +2
Big data, including applications with high security requirements, are often collected and stored on multiple heterogeneous devices, such as mobile devices, drones and vehicles. Due…
Fully Decentralized Federated Learning Based Beamforming Design for UAV Communications
Yue Xiao, Yu Ye, Shaocheng Huang +4
To handle the data explosion in the era of internet of things (IoT), it is of interest to investigate the decentralized network, with the aim at relaxing the burden to central serv…
Decentralized Beamforming Design for Intelligent Reflecting Surface-enhanced Cell-free Networks
Shaocheng Huang, Yu Ye, Ming Xiao +2
Cell-free networks are considered as a promising distributed network architecture to satisfy the increasing number of users and high rate expectations in beyond-5G systems. However…
Deep Reinforcement Learning Based Spectrum Allocation in Integrated Access and Backhaul Networks
Wanlu Lei, Yu Ye, Ming Xiao
We develop a framework based on deep reinforce-ment learning (DRL) to solve the spectrum allocation problem inthe emerging integrated access and backhaul (IAB) architecturewith lar…
Learning Based Hybrid Beamforming for Millimeter Wave Multi-User MIMO Systems
Shaocheng Huang, Yu Ye, Ming Xiao
Hybrid beamforming (HBF) design is a crucial stage in millimeter wave (mmWave) multi-user multi-input multi-output (MU-MIMO) systems. However, conventional HBF methods are still wi…
Learning Based Hybrid Beamforming Design for Full-Duplex Millimeter Wave Systems
Shaocheng Huang, Yu Ye, Ming Xiao
Millimeter Wave (mmWave) communications with full-duplex (FD) have the potential of increasing the spectral efficiency, relative to those with half-duplex. However, the residual se…