Deep Learning-Based Channel Estimation for Beamspace mmWave Massive MIMO Systems
Open accessAbstract
Channel estimation is very challenging when the receiver is equipped with a limited number of radio-frequency (RF) chains in beamspace millimeter-wave massive multiple-input and multiple-output systems. To solve this problem, we exploit a learned denoising-based approximate message passing (LDAMP) network. This neural network can learn channel structure and estimate channel from a large number of training data. Furthermore, we provide an analytical framework on the asymptotic performance of the channel estimator. Based on our analysis and simulation results, the LDAMP neural network significantly outperforms state-of-the-art compressed sensing-based algorithms even when the receiver is equipped with a small number of RF chains.
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- Authors
- He, H., Wen, C.-K., Jin, S., & Li, G. Y.
- Affiliations
- Southeast University (CN)
- National Sun Yat-sen University (TW)
- Georgia Institute of Technology (US)
- Venue
- IEEE Wireless Communications Letters
- Published
- 2018-10
- Volume
- 7
- Issue
- 5
- Pages
- 852-855
- ISSN
- 2162-2337 (ISSN-L)
- 2162-2345
- OpenAlex
- W2963290405
- Cited by
- 823
- References
- 10
- Citations by year
- 2026: 68 · 2025: 106 · 2024: 98 · 2023: 107 · 2022: 113 · 2021: 126 · 2020: 110 · 2019: 82 · 2018: 13
- FWCI
- 31.66
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- IEEE Wireless Communications Letters (publishedVersion)
- arXiv (Cornell University) (submittedVersion)
- Rare & Special e-Zone (The Hong Kong University of Science and Technology) (submittedVersion)
- arXiv (Cornell University)
- Funders
- National Science Foundation (NSFC) for Distinguished Young Scholars of China (61625106)
- National Natural Science Foundation of China (61531011)
- Ministry of Science and Technology, Taiwan (MOST 106-2221-E-110-019)
- ITRI, Hsinchu, Taiwan
- Topics
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Millimeter-Wave Propagation and Modeling
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Advanced Wireless Communication Techniques
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Advanced Wireless Communication Technologies
- Keywords
- channel estimation, millimeter-wave communication, RF chain reduction, compressed sensing, asymptotic performance analysis
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