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Ordered MMSE–SIC via sorted QR decomposition in ill conditioned large-scale MIMO channels

Author

Listed:
  • Ricardo Tadashi Kobayashi

    (State University of Londrina (UEL))

  • Taufik Abrão

    (State University of Londrina (UEL))

Abstract

In this work, some aspects of the sorted QR decomposition are addressed for ordered successive–interference–cancellation detection in large-scale antenna systems. An analysis on the sorted QR decomposition behavior, including its impact on the performance of symbol detection in large ill conditioned MIMO channel matrices, has been presented. As the correlation on the channel matrix grows, the sorted QR decomposition may not ensure its requirements, causing misleading symbol estimation. In this context, it is shown that orthogonality condition may be broken, depending on the matrix condition, which comes from propagation errors on the norm updating of the modified Gram–Schimidt method. Numerical results have corroborated our claims, demonstrating the sensitivity of the Gram–Schimidt algorithm, as well as the deterioration of the large-scale MIMO detection performance under highly correlated channels scenarios.

Suggested Citation

  • Ricardo Tadashi Kobayashi & Taufik Abrão, 2016. "Ordered MMSE–SIC via sorted QR decomposition in ill conditioned large-scale MIMO channels," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 63(2), pages 335-346, October.
    • Handle: RePEc:spr:telsys:v:63:y:2016:i:2:d:10.1007_s11235-015-0123-5
    DOI: 10.1007/s11235-015-0123-5
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    Cited by:

    1. Ehab Ali & Mahamod Ismail & Rosdiadee Nordin & Nor Fadzilah Abdulah, 2019. "Beamforming with 2D-AOA estimation for pilot contamination reduction in massive MIMO," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 71(4), pages 541-552, August.

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