1 citations · 1 across the 3 of their papers we have counts for
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Channel Fingerprint Based Beam Tracking for Millimeter Wave Communications
Ruichen Deng, Sheng Chen, Sheng Zhou +2
Beamforming structures with fixed beam codebooks provide economical solutions for millimeter wave (mmWave) communications due to the low hardware cost. However, the training overhe…
Inferring Remote Channel State Information: Cramér-Rao Lower Bound and Deep Learning Implementation
Zhiyuan Jiang, Ziyan He, Sheng Chen +3
Channel state information (CSI) is of vital importance in wireless communication systems. Existing CSI acquisition methods usually rely on pilot transmissions, and geographically s…
Time-Sequence Channel Inference for Beam Alignment in Vehicular Networks
Sheng Chen, Zhiyuan Jiang, Sheng Zhou +1
In this paper, we propose a learning-based low-overhead beam alignment method for vehicle-to-infrastructure communication in vehicular networks. The main idea is to remotely infer…
Exploiting Wireless Channel State Information Structures Beyond Linear Correlations: A Deep Learning Approach
Zhiyuan Jiang, Sheng Chen, Andreas F. Molisch +3
Knowledge of information about the propagation channel in which a wireless system operates enables better, more efficient approaches for signal transmissions. Therefore, channel st…
Joint User Scheduling and Beam Selection Optimization for Beam-Based Massive MIMO Downlinks
Zhiyuan Jiang, Sheng Chen, Sheng Zhou +1
In beam-based massive multiple-input multiple-output systems, signals are processed spatially in the radio-frequency (RF) front-end and thereby the number of RF chains can be reduc…
Remote Channel Inference for Beamforming in Ultra-Dense Hyper-Cellular Network
Sheng Chen, Zhiyuan Jiang, Jingchu Liu +4
In this paper, we propose a learning-based low-overhead channel estimation method for coordinated beamforming in ultra-dense networks. We first show through simulation that the cha…