• DocumentCode
    2621065
  • Title

    Subspace-based delay estimation for CDMA communication systems

  • Author

    Bensley, Stephen E. ; Aazhang, Behnaam

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Rice Univ., Houston, TX, USA
  • fYear
    1994
  • fDate
    27 Jun-1 Jul 1994
  • Firstpage
    138
  • Abstract
    We consider a subspace-based approach to delay estimation for code division multiple access communication systems. By exploiting the eigenstructure of the received signal´s sample correlation matrix, the observation space is partitioned into a signal subspace and a noise subspace without prior knowledge of the users´ delays. The delay estimate is formed by maximizing the likelihood of the projection of a given user´s spreading waveform into the estimated noise subspace, thus decomposing the multiuser delay estimation problem into a series of single user problems. This subspace-based approach requires no preamble for acquisition, is near-far resistant, and is robust to changing channel conditions
  • Keywords
    Gaussian channels; code division multiple access; correlation methods; delays; eigenvalues and eigenfunctions; matrix algebra; pseudonoise codes; spread spectrum communication; state-space methods; AWGN channel; CDMA communication systems; channel conditions; code division multiple access; eigenstructure; multiuser delay estimation; near-far resistant method; noise subspace; observation space; sample correlation matrix; signal subspace; spreading code; spreading waveform; subspace-based delay estimation; AWGN channels; Additive white noise; Delay estimation; Eigenvalues and eigenfunctions; Gaussian noise; Matrix decomposition; Multiaccess communication; Noise robustness; Propagation delay; Sampling methods;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Theory, 1994. Proceedings., 1994 IEEE International Symposium on
  • Conference_Location
    Trondheim
  • Print_ISBN
    0-7803-2015-8
  • Type

    conf

  • DOI
    10.1109/ISIT.1994.394837
  • Filename
    394837