2021 IEEE International Conference on Acoustics, Speech and Signal Processing

6-11 June 2021 • Toronto, Ontario, Canada

Extracting Knowledge from Information

2021 IEEE International Conference on Acoustics, Speech and Signal Processing

6-11 June 2021 • Toronto, Ontario, Canada

Extracting Knowledge from Information
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Paper Detail

Paper IDSAM-4.6
Paper Title JOINT CHANNEL, DATA, AND PHASE-NOISE ESTIMATION IN MIMO-OFDM SYSTEMS USING A TENSOR MODELING APPROACH
Authors Bruno Sokal, Federal University of Ceará, Brazil; Paulo Gomes, Federal Institute of Education, Science and Technology of Ceara, Brazil; André de Almeida, Federal University of Ceará, Brazil; Martin Haardt, Ilmenau University of Technology, Germany
SessionSAM-4: MIMO and Massive MIMO Array Processing
LocationGather.Town
Session Time:Wednesday, 09 June, 16:30 - 17:15
Presentation Time:Wednesday, 09 June, 16:30 - 17:15
Presentation Poster
Topic Sensor Array and Multichannel Signal Processing: [SAM-TNSR] Tensor-based signal processing for multi-sensor systems
IEEE Xplore Open Preview  Click here to view in IEEE Xplore
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.