Downlink Channel Covariance Matrix Reconstruction for FDD Massive MIMO Systems With Limited Feedback-Reference-Cited by-同舟云学术

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Downlink Channel Covariance Matrix Reconstruction for FDD Massive MIMO Systems With Limited Feedback

Published:2024 Issue: Volume:72 Page:1032-1048
ISSN:1053-587X
Container-title:IEEE Transactions on Signal Processing
language:
Short-container-title:IEEE Trans. Signal Process.

Author:

Li Kai¹^ORCID,Li Ying²^ORCID,Cheng Lei³^ORCID,Shi Qingjiang⁴^ORCID,Luo Zhi-Quan¹^ORCID

Affiliation:

1. The Chinese University of Hong Kong, Shenzhen, China

2. Department of Statistics and Actuarial Science, University of Hong Kong, Hong Kong, SAR, China

3. College of Information Science and Electronic Engineering, Zhejiang University, Hangzhou, China

4. School of Software Engineering, Tongji University, Shanghai, China

Funder

National Key Research and Development Project

Guangdong Provincial Key Laboratory of Big Data Computing

National Natural Science Foundation of China

Fundamental Research Funds for the Central Universities

Zhejiang University Education Foundation Qizhen Scholar Foundation

Science and Technology on Sonar Laboratory

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/78/10347386/10400462.pdf?arnumber=10400462

Reference45 articles.

1. Towards 6G wireless communication networks: vision, enabling technologies, and new paradigm shifts

2. An Overview of Massive MIMO: Benefits and Challenges

3. Massive MIMO for Maximal Spectral Efficiency: How Many Users and Pilots Should Be Allocated?

4. Smart Pilot Assignment for Massive MIMO

5. Joint spatial division and multiplexing: Realizing massive MIMO gains with limited channel state information

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1. Bayesian Hierarchical Sparse Autoencoder for Massive MIMO CSI Feedback;IEEE Transactions on Signal Processing;2024

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