University of Oulu

T. Takahashi, A. Tolli, S. Ibi and S. Sampei, "Low-Complexity Beam-Domain Channel Estimation with Long-Term Statistics for Large MIMO Detection," 2019 IEEE Global Communications Conference (GLOBECOM), Waikoloa, HI, USA, 2019, pp. 1-6, doi: 10.1109/GLOBECOM38437.2019.9014066

Low-complexity beam-domain channel estimation with long-term statistics for large MIMO detection

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Author: Takahashi, Takumi1; Tölli, Antti2; Ibi, Shinsuke3;
Organizations: 1Department of Information and Communications Technology, Osaka University, Yamada-oka 2-1, Suita 565-0871, Japan
2Centre for Wireless Communications (CWC), FI-90014 University of Oulu, Finland
3Faculty of Science and Engineering, Doshisha University, 1-3 Tataramiyakodani, Kyotanabe-shi, 610-0394, Japan
Format: article
Version: accepted version
Access: open
Online Access: PDF Full Text (PDF, 0.2 MB)
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Language: English
Published: Institute of Electrical and Electronics Engineers, 2019
Publish Date: 2020-06-22


This paper proposes low-complexity beam-domain channel estimation using long-term channel statistics in belief propagation (BP) based large multi-input multi-output (MIMO) detection. When the channel correlation matrix between the base station (BS) and each user equipment (UE) is available and used as prior information, maximum a-posteriori probability (MAP) estimation provides the optimal estimation performance. However, it requires undesirably complex large-scale matrix operations at any time the channel statistics is changed. By appropriately selecting beam-domain angular bins for each UE, the proposed method allows us to significantly reduce the computational cost while maintaining the near-optimal performance in terms of the mean square error (MSE) of estimated channel. The selection threshold is adaptively determined based on the prior information such as the channel correlation matrix, statistical beam, and receive SNR. For the subsequent BP-based signal detection, an appropriate covariance matrix is designed while considering the detrimental impact of channel estimation errors. Numerical results show that the proposed method can reduce the computational cost to less than 4% as compared to the MAP estimation, while providing similar MSE performance.

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Series: IEEE Global Communications Conference
ISSN: 2334-0983
ISSN-E: 2576-6813
ISSN-L: 2334-0983
ISBN: 978-1-7281-0962-6
ISBN Print: 978-1-7281-0963-3
Pages: 1 - 6
Article number: 9014066
DOI: 10.1109/GLOBECOM38437.2019.9014066
Host publication: 2019 IEEE Global Communications Conference (GLOBECOM), December 9-14, Waikoloa, HI, USA
Conference: IEEE Global Communications Conference
Type of Publication: A4 Article in conference proceedings
Field of Science: 213 Electronic, automation and communications engineering, electronics
Funding: This work was financially supported by JSPS KAKENHI Grant Number JP18H03765, Japan.
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