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Low-Complexity and High-Accuracy Semi-blind Joint Channel and Symbol Estimation for Massive MIMO-OFDM

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Abstract

In order to fully exploit the scarce spectrum, antenna arrays are incorporated into wireless communication devices in 4G and 5G communication networks to deploy MIMO-OFDM systems. Recently, the least squares Khatri–Rao factorization has been applied to MIMO-OFDM systems for semi-blind joint channel and symbol estimation. Its cubic computational complexity is prohibitive when the number of transmit and receive antennas is very large. Therefore, the average vector and Hadamard ratio rank one approximation has been proposed for MIMO-OFDM systems, showing a linear complexity, but being limited to channels and transmitted symbols with offsets. In this paper, we present four novel MIMO-OFDM algorithms for massive antenna array systems that outperform the state-of-the-art approaches in terms of complexity and/or accuracy. The four proposed schemes are the alternating least squares with vector selection initialization, the vector projection rank one approximation including vector selection rank one initialization, the factorization based on eigenvalue decomposition with eigenvector projection and the factorization based on sectional truncated singular value decomposition and vector projection. Our analytical complexity analysis and numerical results corroborate the trade-offs offered by the different receiver algorithms in terms of complexity, parallelism and performance.

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Notes

  1. A simple and suboptimal choice of \(\phi \) is given by \(\phi _m=2\pi (m-1)/M\). However, it can be optimized. See [24].

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Acknowledgements

The authors would like to thank the Research Support Foundation of the Brazilian Federal District (FAPDF) for their funding under the calls 03/2015 and 01/2017, the Brazilian Coordination for the Improvement of Higher Education Personnel (CAPES) for the PNPD, PVE and PDE scholarships, and CAPES/PROBAL Grant 88887.144009/2017-00. João P. C. L. da Costa and André L. F. de Almeida are partially supported by the Brazilian National Council for Scientific and Technological Development (CNPq).

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Authors and Affiliations

  1. Department of Electrical Engineering, University of Brasília, Campus Darcy Ribeiro, Asa Norte, Brasília, 70910-900, Brazil

    Ricardo Kehrle Miranda, João Paulo C. L. da Costa & Rafael T. de Sousa Jr.

  2. Institute for Information Technology, Ilmenau University of Technology, Helmholtzpl. 2, Helmholtzbau, 98684, Ilmenau, Germany

    Binghua Guo & Giovanni Del Galdo

  3. Fraunhofer Institute for Integrated Circuits IIS, Erlangen, Germany

    Giovanni Del Galdo

  4. Department of Teleinformatics Engineering, Federal University of Ceará, Av. Mister Hull, P.O. Box 6005, Fortaleza, CE, 60455-760, Brazil

    André L. F. de Almeida

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  1. Ricardo Kehrle Miranda
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  2. João Paulo C. L. da Costa
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  3. Binghua Guo
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  4. André L. F. de Almeida
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  5. Giovanni Del Galdo
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  6. Rafael T. de Sousa Jr.
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Correspondence to Ricardo Kehrle Miranda.

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Kehrle Miranda, R., C. L. da Costa, J.P., Guo, B. et al. Low-Complexity and High-Accuracy Semi-blind Joint Channel and Symbol Estimation for Massive MIMO-OFDM. Circuits Syst Signal Process 38, 1114–1136 (2019). https://doi.org/10.1007/s00034-018-0898-1

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