1.7k citations · 6.2k across the 106 of their papers we have counts for
74 papers · 1 filter
Message Passing Meets Graph Neural Networks: A New Paradigm for Massive MIMO Systems
Hengtao He, Xianghao Yu, Jun Zhang +2
As one of the core technologies for 5G systems, massive multiple-input multiple-output (MIMO) introduces dramatic capacity improvements along with very high beamforming and spatial…
Lightweight and Flexible Deep Equilibrium Learning for CSI Feedback in FDD Massive MIMO
Yifan Ma, Wentao Yu, Xianghao Yu +3
In frequency-division duplexing (FDD) massive multiple-input multiple-output (MIMO) systems, downlink channel state information (CSI) needs to be sent back to the base station (BS)…
Error Rate Analysis for Grant-free Massive Random Access with Short-Packet Transmission
Xinyu Bian, Yuyi Mao, Jun Zhang
Grant-free massive random access (RA) is a promising protocol to support the massive machine-type communications (mMTC) scenario in 5G and beyond networks. In this paper, we focus…
Graph Neural Networks for Wireless Communications: From Theory to Practice
Yifei Shen, Jun Zhang, S. H. Song +1
Deep learning-based approaches have been developed to solve challenging problems in wireless communications, leading to promising results. Early attempts adopted neural network arc…
Cell-Free Massive MIMO for 6G Wireless Communication Networks
Hengtao He, Xianghao Yu, Jun Zhang +2
The recently commercialized fifth-generation (5G) wireless communication networks achieved many improvements, including air interface enhancement, spectrum expansion, and network i…
Cell-Free Massive MIMO Detection: A Distributed Expectation Propagation Approach
Hengtao He, Xianghao Yu, Jun Zhang +2
Cell-free massive MIMO is one of the core technologies for future wireless networks. It is expected to bring enormous benefits, including ultra-high reliability, data throughput, e…