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• W3161522046 abstract "In this work, we propose a two-stage tensor-based receiver for joint channel, phase-noise (PN), and data estimation in MIMO-OFDM systems. First, we cast the received signal at the pilot subcarriers as a third-order PARAFAC model. Based on this model, we propose a closed-form algorithm based on the LS-KRF (Least Squares - Khatri-Rao Factorization) that estimates the channel gains and the phase-noise terms through multiple rank-one factorizations. From the estimated channel, the second stage of the receiver consists of data estimation based on a ZF (Zero-Forcing) receiver that capitalizes on the tensor structure of the received signal at the data subcarriers via a Selective Kronecker Product (SKP) approach. Our numerical simulations show that the proposed receiver achieves an improved performance compared to the state-of-art receivers." @default.
• W3161522046 created "2021-05-24" @default.
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• W3161522046 date "2021-06-06" @default.
• W3161522046 modified "2023-10-03" @default.
• W3161522046 title "Joint Channel, Data, and Phase-Noise Estimation in MIMO-OFDM Systems Using a Tensor Modeling Approach" @default.
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• W3161522046 doi "https://doi.org/10.1109/icassp39728.2021.9414541" @default.
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