• DocumentCode
    178799
  • Title

    Predictive quantization of bit loading for MIMO time-correlated channels with limited feedback

  • Author

    Yuan-Pei Lin ; Chi-Chang Wu

  • Author_Institution
    Dept. Electr. Eng., Nat. Chiao Tung Univ., Hsinchu, Taiwan
  • fYear
    2014
  • fDate
    4-9 May 2014
  • Firstpage
    3489
  • Lastpage
    3492
  • Abstract
    In this paper we consider variable-rate transmission for time-correlated MIMO (multi-input multi-output) channels with limited feedback. The number of bits loaded on each subchannel of the MIMO system is dynamically assigned according to the current channel condition and fed back to the transmitter. As the channel is time-correlated, so is bit loading. We propose to feedback bit loading using predictive coding, which is known to be a powerful technique for quantizing correlated signals. Assuming the channel is a first-order Gauss-Markov random process, we derive the optimal predictor for the bit loading to be coded. We show that the subchannels prediction errors are approximated Gaussian and thus can be quantized using quantizers designed for Gaussian random variables. Simulations demonstrate that the proposed predictive coding can achieve a very good approximation of the desired transmission rate with a very low feedback rate.
  • Keywords
    Gaussian channels; MIMO communication; Markov processes; approximation theory; channel coding; correlation methods; feedback; quantisation (signal); radio transmitters; random processes; wireless channels; approximated Gaussian random variable; correlated signal quantization; feedback bit loading; first-order Gauss-Markov random process; predictive coding; predictive quantization; subchannel prediction error; time-correlated MIMO channel; time-correlated multiinput multioutput channel; transmitter; variable-rate transmission; Approximation methods; Load modeling; Loading; MIMO; Quantization (signal); Random variables; Transmitters;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Acoustics, Speech and Signal Processing (ICASSP), 2014 IEEE International Conference on
  • Conference_Location
    Florence
  • Type

    conf

  • DOI
    10.1109/ICASSP.2014.6854249
  • Filename
    6854249