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Enhanced Channel Estimation for MIMO OFDM Systems

Authors
Song,Hoon-GeunPark, Kwang HyunJeon, Sang Woon
Issue Date
Oct-2022
Publisher
 IEEE
Keywords
Channel estimation; Linear minimum mean square error estimation; OFDM system
Citation
2022 13th International Conference on Information and Communication Technology Convergence (ICTC), v.2022-October, pp 691 - 694
Pages
4
Indexed
OTHER
Journal Title
2022 13th International Conference on Information and Communication Technology Convergence (ICTC)
Volume
2022-October
Start Page
691
End Page
694
URI
https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/114733
DOI
10.1109/ICTC55196.2022.9952550
ISSN
2162-1233
Abstract
In this paper, the enhanced approximate linear minimum mean square error channel estimation (EALMMSE) method is proposed. It outperforms the conventional approximate linear minimum mean square error channel estimation (ALMMSE) method, known for its poor performance for the low signal-to-noise ratio (SNR) regime. The proposed EALMMSE method uses the channel autocorrelation matrix in the frequency domain, which estimates channel coefficients more accurately by the Pilot-Only Autocorrelation Matrix. The EALMMSE achieves improved performance for a broad range of SNR, offsetting the shortcoming of the conventional ALMMSE method so that it can be applied to various practical network environments. In addition, the EALMMSE method is well suited for a multiple-input-multiple-output (MIMO) OFDM system. It is demonstrated by simulation that EALMMSE outperforms ALMMSE under the standard channel model developed by the Third-Generation Partnership Project (3GPP).
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COLLEGE OF ENGINEERING SCIENCES > DEPARTMENT OF MILITARY INFORMATION ENGINEERING > 1. Journal Articles

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Jeon, Sang Woon
ERICA 공학대학 (SCHOOL OF ELECTRICAL ENGINEERING)
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