The DOI matches its Crossref record; 20 of the 20 references it cites were found in a registry or an index.
Channel Estimation for Extremely Large-Scale MIMO: Far-Field or Near-Field?
Open accessAbstract
Extremely large-scale multiple-input-multiple-output (XL-MIMO) is promising to meet the high rate requirements for future 6G. To realize efficient precoding, accurate channel state information is essential. Existing channel estimation algorithms with low pilot overhead heavily rely on the channel sparsity in the angular domain, which is achieved by the classical far-field planar-wavefront assumption. However, due to the non-negligible near-field spherical-wavefront property in XL-MIMO, this channel sparsity in the angular domain is not achievable. Therefore, existing far-field channel estimation schemes will suffer from severe performance loss. To address this problem, in this paper, we study the near-field channel estimation by exploiting the polar-domain sparsity. Specifically, unlike the classical angular-domain representation that only considers the angular information, we propose a polar-domain representation, which simultaneously accounts for both the angular and distance information. In this way, the near-field channel also exhibits sparsity in the polar domain, based on which, we propose on-grid and off-grid near-field XL-MIMO channel estimation schemes. Firstly, an on-grid polar-domain simultaneous orthogonal matching pursuit (P-SOMP) algorithm is proposed to efficiently estimate the near-field channel. Furthermore, an off-grid polar-domain simultaneous iterative gridless weighted (P-SIGW) algorithm is proposed to improve the estimation accuracy. Finally, simulations are provided to verify the effectiveness of our schemes.
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5G-Advanced Toward 6G: Past, Present, and Future
Chen, W., Lin, X., Lee, J., Toskala, A., Sun, S., Chiasserini, C. F., & Liu, L. (2023) · IEEE Journal on Selected Areas in Communications · doi:10.1109/jsac.2023.3274037 · Cited by 408
A Tutorial on Near-Field XL-MIMO Communications Toward 6G
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Gong, T., Gavriilidis, P., Ji, R., Huang, C., Alexandropoulos, G. C., Wei, L., Zhang, Z., Debbah, M., Poor, H. V., & Yuen, C. (2024) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2023.3309529 · Cited by 328
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Shi, E., Zhang, J., Du, H., Ai, B., Yuen, C., Niyato, D., Letaief, K. B., & Shen, X. (2024) · Proceedings of the IEEE · doi:10.1109/jproc.2024.3404491 · Cited by 224
Stacked Intelligent Metasurfaces for Holographic MIMO-Aided Cell-Free Networks
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Metadata
- Authors
- Cui, M., & Dai, L.
- Venue
- IEEE Transactions on Communications
- Published
- 2022-04
- Volume
- 70
- Issue
- 4
- Pages
- 2663-2677
- ISSN
- 0090-6778 (ISSN-L)
- 1558-0857
- OpenAlex
- W4226370247
- Cited by
- 871
- References
- 20
- FWCI
- 45.44
- Type
- journal article
- Language
- en
- Open access
- green
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