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Joint Semi-blind Channel Estimation and Finite Alphabet Signal Recovery Detection for large-scale MIMO systems

Hajji Zahran 1, 2 Abdeldjalil Aissa El Bey 1, 2 Karine Amis 1, 2
2 Lab-STICC_COSYDE - Equipe Communication System Design
Lab-STICC - Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance : UMR6285
Abstract : In this paper, we consider large-scale MIMO systems and we address the channel estimation problem. We propose an iterative receiver consisting of the cascade of a semi-blind leastsquares channel estimation algorithm with a simplicity-based detection algorithm for finite-alphabet signals (FAS and FAS-SAC). A minimum number of pilot sequences is used to get an initial channel estimation. The detection algorithm outputs are then used to refine it gradually. Two feeding methods are studied. The first one uses raw detection outputs. The second one is based on hard decisions and enables better performance. Theoretical MSEs are calculated in both cases. Simulations assess the efficiency of the proposed iterative procedure compared to the state-of-the-art methods and show that it performs very close to the ideal scenario where all the communication frame sequences are known.
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Submitted on : Wednesday, July 14, 2021 - 11:14:01 AM
Last modification on : Monday, October 11, 2021 - 2:24:03 PM
Long-term archiving on: : Friday, October 15, 2021 - 4:11:23 PM

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Hajji Zahran, Abdeldjalil Aissa El Bey, Karine Amis. Joint Semi-blind Channel Estimation and Finite Alphabet Signal Recovery Detection for large-scale MIMO systems. IEEE Open Journal of Signal Processing, IEEE, 2021, 2, pp.370-382. ⟨10.1109/OJSP.2021.3097968⟩. ⟨hal-03286312⟩

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