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A soft-in soft-out detection approach using partial gaussian approximation

Conference Paper


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Abstract


  • This paper concerns the implementation of the softin

    soft-out detector in an iterative detection system. A detection

    approach is proposed based on the properties of Gaussian

    functions. In this approach, for the computation of the APP (a

    posteriori probability) of a concerned symbol, the other symbols

    are distinguished based on their contributions to the APP of

    the concerned symbol, and the symbols with less contributions

    are treated as Gaussian variables to reduce the computational

    complexity. The exact APP detector and the well-known LMMSE

    (linear minimum mean square error) detector are two special

    cases of the proposed detector. Simulation results show that

    the proposed detector can significantly outperform the LMMSE

    detector, and achieve a good trade-off between complexity and

    performance.

UOW Authors


  •   Guo, Qinghua
  •   Fang, Licai (external author)
  •   Huang, Defeng (David) (external author)
  •   Nordholm, Sven (external author)

Publication Date


  • 2012

Citation


  • Q. Guo, L. Fang, D. Huang & S. Nordholm, "A soft-in soft-out detection approach using partial gaussian approximation," in International Conference on Wireless Communications and Signal Processing, 2012, pp. 1-6.

Scopus Eid


  • 2-s2.0-84881036232

Ro Full-text Url


  • http://ro.uow.edu.au/cgi/viewcontent.cgi?article=1747&context=eispapers

Ro Metadata Url


  • http://ro.uow.edu.au/eispapers/741

Has Global Citation Frequency


Start Page


  • 1

End Page


  • 6

Place Of Publication


  • Australia

Abstract


  • This paper concerns the implementation of the softin

    soft-out detector in an iterative detection system. A detection

    approach is proposed based on the properties of Gaussian

    functions. In this approach, for the computation of the APP (a

    posteriori probability) of a concerned symbol, the other symbols

    are distinguished based on their contributions to the APP of

    the concerned symbol, and the symbols with less contributions

    are treated as Gaussian variables to reduce the computational

    complexity. The exact APP detector and the well-known LMMSE

    (linear minimum mean square error) detector are two special

    cases of the proposed detector. Simulation results show that

    the proposed detector can significantly outperform the LMMSE

    detector, and achieve a good trade-off between complexity and

    performance.

UOW Authors


  •   Guo, Qinghua
  •   Fang, Licai (external author)
  •   Huang, Defeng (David) (external author)
  •   Nordholm, Sven (external author)

Publication Date


  • 2012

Citation


  • Q. Guo, L. Fang, D. Huang & S. Nordholm, "A soft-in soft-out detection approach using partial gaussian approximation," in International Conference on Wireless Communications and Signal Processing, 2012, pp. 1-6.

Scopus Eid


  • 2-s2.0-84881036232

Ro Full-text Url


  • http://ro.uow.edu.au/cgi/viewcontent.cgi?article=1747&context=eispapers

Ro Metadata Url


  • http://ro.uow.edu.au/eispapers/741

Has Global Citation Frequency


Start Page


  • 1

End Page


  • 6

Place Of Publication


  • Australia