• DocumentCode
    422915
  • Title

    A new method of channel feedback quantization for high data rate MIMO systems

  • Author

    Sadrabadi, Mehdi Ansari ; Khandani, Amir K. ; Lahouti, Farshad

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Waterloo Univ., Ont., Canada
  • Volume
    1
  • fYear
    2004
  • fDate
    29 Nov.-3 Dec. 2004
  • Firstpage
    91
  • Abstract
    In this work, we study a multiple-input multiple-output wireless system, where the channel state information is partially available at the transmitter through a feedback link. Based on singular value decomposition, the MIMO channel is split into independent subchannels, which allows separate, and therefore, efficient decoding of the transmitted data signal. Effective feedback of the required spatial channel information entails efficient quantization/encoding of a Haar unitary matrix. The parameter reduction of an n × n unitary matrix to its n2 - n basic parameters is performed through Givens decomposition. We prove that Givens matrices of a Haar unitary matrix are statistically independent. Subsequently, we derive the probability distribution function (PDF) of the corresponding matrix elements. Based on these analyses, an efficient quantization scheme is proposed. The performance evaluation is provided for a scenario where the rates allocated to each independent channel are selected according to its corresponding gain. The results indicate a significant performance improvement compared to the performance of MIMO systems without feedback at the cost of a very low-rate feedback link.
  • Keywords
    MIMO systems; channel coding; channel estimation; feedback; matrix algebra; mobile radio; singular value decomposition; statistical distributions; Givens decomposition; Haar unitary matrix; PDF; channel feedback quantization; channel state information; decoding; encoding; high data rate MIMO systems; independent subchannels; multiple-input multiple-output wireless system; performance evaluation; probability distribution function; singular value decomposition; statistically independent Givens matrices; Channel state information; Decoding; MIMO; Matrix decomposition; Performance gain; Probability distribution; Quantization; Singular value decomposition; State feedback; Transmitters;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Global Telecommunications Conference, 2004. GLOBECOM '04. IEEE
  • Print_ISBN
    0-7803-8794-5
  • Type

    conf

  • DOI
    10.1109/GLOCOM.2004.1377919
  • Filename
    1377919