1 citations · 2 across the 8 of their papers we have counts for
6 papers · 1 filter
Networked Tracking of Multiple Moving Targets in 6G Network
Yanmo Hu, Weifeng Zhu, Chenshu Wu +3
This paper considers a networked tracking architecture in 6G integrated sensing and communication (ISAC) systems, where multiple base stations (BSs) cooperatively transmit radio si…
Deep Learning for Joint Design of Pilot, Channel Feedback, and Hybrid Beamforming in FDD Massive MIMO-OFDM Systems
Junyi Yang, Weifeng Zhu, Shu Sun +3
This letter considers the transceiver design in frequency division duplex (FDD) massive multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) syst…
Hierarchical Beam Alignment for Millimeter-Wave Communication Systems: A Deep Learning Approach
Junyi Yang, Weifeng Zhu, Meixia Tao +1
Fast and precise beam alignment is crucial for high-quality data transmission in millimeter-wave (mmWave) communication systems, where large-scale antenna arrays are utilized to ov…
Cooperative Multi-Cell Massive Access with Temporally Correlated Activity
Weifeng Zhu, Meixia Tao, Xiaojun Yuan +2
This paper investigates the problem of activity detection and channel estimation in cooperative multi-cell massive access systems with temporally correlated activity, where all acc…
Deep Learning for Hierarchical Beam Alignment in mmWave Communication Systems
Junyi Yang, Weifeng Zhu, Meixia Tao
Fast and precise beam alignment is crucial to support high-quality data transmission in millimeter wave (mmWave) communication systems. In this work, we propose a novel deep learni…
Double-Sided Information Aided Temporal-Correlated Massive Access
Weifeng Zhu, Meixia Tao, Yunfeng Guan
This letter considers temporal-correlated massive access, where each device, once activated, is likely to transmit continuously over several consecutive frames. Motivated by that t…