• DocumentCode
    2365449
  • Title

    An effective link error prediction technique for MIMO-OFDM systems with ML receiver

  • Author

    Moon, Sung-Hyun ; Lee, Kyoung-Jae ; Kim, Jihoon ; Lee, Inkyu

  • Author_Institution
    Sch. of Electr. Eng., Korea Univ., Seoul, South Korea
  • fYear
    2012
  • fDate
    10-15 June 2012
  • Firstpage
    4262
  • Lastpage
    4266
  • Abstract
    In this paper, we propose an accurate link performance abstraction technique for multiple-input multiple-output (MIMO) orthogonal frequency-division multiplexing systems with maximum likelihood (ML) receiver. The performance of ML detection (MLD) is estimated by using capacity bounds of two simple linear receivers. To this end, we give a simple parametrization to compute the desired per-stream signal-to-noise ratio (SNR) values, which can be applied for both vertically and horizontally coded MIMO systems. Based on the per-stream SNR estimates, the block error rate performance for each encoding block is finally obtained using the received-bit information rate metrics. From extensive simulations, we verify that the proposed method is accurate in the MIMO-MLD link evaluation with very low computational complexity.
  • Keywords
    MIMO communication; OFDM modulation; encoding; maximum likelihood detection; radio links; radio receivers; MIMO-MLD link evaluation; MIMO-OFDM system; ML Receiver; ML detection; MLD; SNR values; block error rate performance; computational complexity; encoding block; horizontally coded MIMO system; link error prediction technique; link performance abstraction technique; maximum likelihood receiver; multiple-input multiple-output system; orthogonal frequency-division multiplexing system; signal-to-noise ratio; vertically coded MIMO system; Accuracy; Encoding; MIMO; Modulation; OFDM; Receivers; Signal to noise ratio;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Communications (ICC), 2012 IEEE International Conference on
  • Conference_Location
    Ottawa, ON
  • ISSN
    1550-3607
  • Print_ISBN
    978-1-4577-2052-9
  • Electronic_ISBN
    1550-3607
  • Type

    conf

  • DOI
    10.1109/ICC.2012.6363809
  • Filename
    6363809