Efficient Beamforming Training and Channel Estimation for mmWave MIMO-OFDM Systems
ID：144 Submission ID：106 View Protection：ATTENDEE Updated Time：2020-08-05 10:17:28 Hits：387 Oral Presentation

Start Time：2020-06-08 14:00 （Asia/Shanghai）

Duration：20min

Session：[S] Special Session » [SS02] Sparse And Low-Rank Signal Processing For Array Processing And Wireless Communications

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Abstract
We consider the problem of channel estimation for millimeter wave (mmWave) MIMO-OFDM systems. To efficiently probe the channel, the transmitter forms multiple beams simultaneously and steer them towards different directions. The objective of this paper is to devise the beam-training patterns and develop an efficient algorithm to estimate the channel. By exploiting the common sparsity inherent in MIMO-OFDM mmWave channels, we develop a sparse bipartite graph coding-based method for joint beamforming training and channel estimation. Simulation results are provided to show the effectiveness of the proposed method.
Keywords
MmWave communications; beamforming training; channel estimation
Speaker
Hanyu Wang
University of Electronic Science and Technology of China, China

Submission Author
Hanyu Wang University of Electronic Science and Technology of China, China
Jun Fang University of Electronic Science and Technology of China, China
Huiping Duan University of Electronic Science and Technology of China, China
Hongbin Li Stevens Institute of Technology, USA
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