• DocumentCode
    1754666
  • Title

    Comparisons of Two Real-Valued MIMO Signal Models and Their Associated ZF-SIC Detectors over the Rayleigh Fading Channel

  • Author

    Tsung-Hsien Liu

  • Author_Institution
    Dept. of Commun. Eng., Nat. Chung Cheng Univ., Chiayi, Taiwan
  • Volume
    12
  • Issue
    12
  • fYear
    2013
  • fDate
    41609
  • Firstpage
    6054
  • Lastpage
    6066
  • Abstract
    Two real MIMO models, the new lattice representation and the conventional real model, have been proposed in literature as equivalent models to the same complex MIMO model. To learn which one shares more information with the complex model, we show in this paper that the matrices produced by singular value decomposition and QR-decomposition of the complex and new real channel matrices for the complex and new real models, respectively, are fully related. Also, the new real zero-forcing successive interference cancellation (ZF-SIC) detector is shown to find the same solution as the complex ZF-SIC detector. Comparisons of the two real ZF-SIC detectors based on the two real models are therefore equivalent to the comparisons of the complex and conventional real ZF-SIC detectors. Plenty comparisons of the two real ZF-SIC detectors over the Rayleigh fading channel are reported, including the average joint error probability at finite signal-to-noise ratio (SNR), outage probability at different layers, average error probability at high SNR, and the scenario with optimal transmit power allocation. These comparisons provide much understanding about the complex and two real models as well as their associated detectors.
  • Keywords
    MIMO communication; Rayleigh channels; error statistics; interference suppression; signal detection; signal representation; singular value decomposition; QR-decomposition; Rayleigh fading channel; SNR; ZF-SIC detectors; average joint error probability; channel matrices; finite signal-to-noise ratio; lattice representation; optimal transmit power allocation; outage probability; real-valued MIMO signal models; singular value decomposition; zero-forcing successive interference cancellation detector; Computational modeling; Detectors; Fading; Lattices; MIMO; Signal to noise ratio; Vectors; Multiple input multiple output (MIMO) system; spatially multiplexed MIMO system; zero-forcing successive interference cancellation (ZF-SIC) detection;
  • fLanguage
    English
  • Journal_Title
    Wireless Communications, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1536-1276
  • Type

    jour

  • DOI
    10.1109/TW.2013.103113.121600
  • Filename
    6661317