Mixed-Timescale Deep-Unfolding for Joint Channel Estimation and Hybrid Beamforming
Author:
Affiliation:
1. College of Information Science and Electronic Engineering, Zhejiang University, Hangzhou, China
2. NVIDIA, Sophia Antipolis, France
3. Department of Mathematics and Computer Science, Weizmann Institute of Science, Rehovot, Israel
Funder
National Natural Science Foundation of China
Zhejiang Provincial Natural Science Foundation for Distinguished Young Scholars
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Computer Networks and Communications
Link
http://xplorestaging.ieee.org/ielx7/49/9863724/09830727.pdf?arnumber=9830727
Reference53 articles.
1. ViterbiNet: A Deep Learning Based Viterbi Algorithm for Symbol Detection
2. A Model-Driven Deep Learning Method for Massive MIMO Detection
3. Algorithm Unrolling: Interpretable, Efficient Deep Learning for Signal and Image Processing
4. Two-Timescale End-to-End Learning for Channel Acquisition and Hybrid Precoding
5. Hybrid Precoding for Multiuser Millimeter Wave Massive MIMO Systems: A Deep Learning Approach
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