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- Publisher Website: 10.1109/TVT.2023.3311868
- Scopus: eid_2-s2.0-85171548688
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Article: Two-Stage Hierarchical Beam Training for Near-Field Communications
Title | Two-Stage Hierarchical Beam Training for Near-Field Communications |
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Authors | |
Keywords | Beam training extremely large-scale array (XL-array) hierarchical codebook near-field communications |
Issue Date | 2024 |
Citation | IEEE Transactions on Vehicular Technology, 2024, v. 73, n. 2, p. 2032-2044 How to Cite? |
Abstract | Extremely large-scale array (XL-array) has emerged as a promising technology to improve the spectrum efficiency and spatial resolution of future wireless systems. However, the huge number of antennas renders the users more likely to locate in the near-field (instead of the far-field) region of the XL-array with spherical wavefront propagation. This inevitably incurs prohibitively high beam training overhead since it requires a two-dimensional (2D) beam search over both the angular and distance domains. To address this issue, we propose in this article an efficient two-stage hierarchical beam training method for near-field communications. Specifically, in the first stage, we employ the central sub-array of the XL-array to search for a coarse user direction in the angular domain with conventional far-field hierarchical codebook. Then, in the second stage, given the coarse user direction, we progressively search for the fine-grained user direction-and-distance in the polar domain with a dedicatedly designed codebook. Numerical results show that our proposed two-stage hierarchical beam training method can achieve over 99% training overhead reduction as compared to the 2D exhaustive search, yet achieving comparable rate performance. |
Persistent Identifier | http://hdl.handle.net/10722/349964 |
ISSN | 2023 Impact Factor: 6.1 2023 SCImago Journal Rankings: 2.714 |
DC Field | Value | Language |
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dc.contributor.author | Wu, Chenyu | - |
dc.contributor.author | You, Changsheng | - |
dc.contributor.author | Liu, Yuanwei | - |
dc.contributor.author | Chen, Li | - |
dc.contributor.author | Shi, Shuo | - |
dc.date.accessioned | 2024-10-17T07:02:10Z | - |
dc.date.available | 2024-10-17T07:02:10Z | - |
dc.date.issued | 2024 | - |
dc.identifier.citation | IEEE Transactions on Vehicular Technology, 2024, v. 73, n. 2, p. 2032-2044 | - |
dc.identifier.issn | 0018-9545 | - |
dc.identifier.uri | http://hdl.handle.net/10722/349964 | - |
dc.description.abstract | Extremely large-scale array (XL-array) has emerged as a promising technology to improve the spectrum efficiency and spatial resolution of future wireless systems. However, the huge number of antennas renders the users more likely to locate in the near-field (instead of the far-field) region of the XL-array with spherical wavefront propagation. This inevitably incurs prohibitively high beam training overhead since it requires a two-dimensional (2D) beam search over both the angular and distance domains. To address this issue, we propose in this article an efficient two-stage hierarchical beam training method for near-field communications. Specifically, in the first stage, we employ the central sub-array of the XL-array to search for a coarse user direction in the angular domain with conventional far-field hierarchical codebook. Then, in the second stage, given the coarse user direction, we progressively search for the fine-grained user direction-and-distance in the polar domain with a dedicatedly designed codebook. Numerical results show that our proposed two-stage hierarchical beam training method can achieve over 99% training overhead reduction as compared to the 2D exhaustive search, yet achieving comparable rate performance. | - |
dc.language | eng | - |
dc.relation.ispartof | IEEE Transactions on Vehicular Technology | - |
dc.subject | Beam training | - |
dc.subject | extremely large-scale array (XL-array) | - |
dc.subject | hierarchical codebook | - |
dc.subject | near-field communications | - |
dc.title | Two-Stage Hierarchical Beam Training for Near-Field Communications | - |
dc.type | Article | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1109/TVT.2023.3311868 | - |
dc.identifier.scopus | eid_2-s2.0-85171548688 | - |
dc.identifier.volume | 73 | - |
dc.identifier.issue | 2 | - |
dc.identifier.spage | 2032 | - |
dc.identifier.epage | 2044 | - |
dc.identifier.eissn | 1939-9359 | - |