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Beam Structured Signal Detection for HF Skywave Massive MIMO Communications
Southeast University, National Mobile Communications Research Laboratory, Nanjing, China; Purple Mountain Laboratories, Nanjing, China.
Southeast University, National Mobile Communications Research Laboratory, Nanjing, China; Purple Mountain Laboratories, Nanjing, China.
Southeast University, National Mobile Communications Research Laboratory, Nanjing, China; Purple Mountain Laboratories, Nanjing, China.
Southeast University, National Mobile Communications Research Laboratory, Nanjing, China; Purple Mountain Laboratories, Nanjing, China.
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2023 (English)In: 2023 IEEE 98th Vehicular Technology Conference, VTC 2023-Fall - Proceedings, Institute of Electrical and Electronics Engineers Inc. , 2023Conference paper, Published paper (Refereed)
Abstract [en]

In this paper, we investigate signal detection for HF skywave massive multiple-input multiple-output (MIMO) communications with orthogonal frequency division multiplexing (OFDM) modulation. We first introduce beam based channel model (BBCM) in the space domain and reveal the sparsity of the channel in the space-beam domain. Based on the BBCM in the space domain, we propose a beam structured detector (BSD) for each subcarrier. Specifically, we prove that the space domain detector design can be transformed to that of a beam domain detector without sacrificing optimality, and the asymptotically optimal space domain detector is beam structured with a low-dimensional beam domain detector, thus significantly reducing the design and implementation complexities. Furthermore, we provide a beam selection criterion to choose the beams that are used for the BSD. Simulation results demonstrate the low complexity and satisfactory performance of the proposed detector.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers Inc. , 2023.
National Category
Signal Processing
Identifiers
URN: urn:nbn:se:kth:diva-342081DOI: 10.1109/VTC2023-Fall60731.2023.10333845ISI: 001133762500427Scopus ID: 2-s2.0-85181173504OAI: oai:DiVA.org:kth-342081DiVA, id: diva2:1826891
Conference
98th IEEE Vehicular Technology Conference, VTC 2023-Fall, Hong Kong, China, Oct 10 2023 - Oct 13 2023
Note

QC 20240110

Part of ISBN 9798350329285

Available from: 2024-01-12 Created: 2024-01-12 Last updated: 2024-02-29Bibliographically approved

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Bengtsson, Mats

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CiteExportLink to record
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Citation style
  • apa
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  • de-DE
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