• DocumentCode
    2647425
  • Title

    High-SNR analysis of optimum multiuser detection with an unknown number of users

  • Author

    Campo, Adrià Tauste ; Fàbregas, Albert Guillén I ; Biglieri, Ezio

  • Author_Institution
    Dept. of Eng., Univ. of Cambridge, Cambridge, UK
  • fYear
    2009
  • fDate
    11-16 Oct. 2009
  • Firstpage
    283
  • Lastpage
    287
  • Abstract
    We analyze multiuser detection under the assumption that the number of users accessing the channel is unknown by the receiver. Our main goal is to determine the performance loss caused by the need for estimating the identities of active users, which are not known a priori. To prevent a loss of optimality, we assume that identities and data are estimated jointly, rather than in two separate steps. We examine the performance of multiuser detectors when the number of potential users is large. Statistical-physics methodologies are used to determine the fixed-point equation whose solutions yield the multiuser efficiency of the optimal detector. Special attention is paid to the large signal-to-noise ratio, which yields tight closed-form bounds on the minimum mean-squared error. These bounds analytically illustrate the set of solutions of the fixed-point equation, and their relationship with the maximum system load. By identifying the region of computationally feasible solutions, we study the maximum load that the detector can support for a given SNR and quality of service, specified by the multiuser efficiency.
  • Keywords
    code division multiple access; least mean squares methods; multiuser detection; closed-form bounds; fixed-point equation; minimum mean-squared error; optimum multiuser detection; statistical-physics methodologies; Conferences; Detectors; Equations; Error analysis; Information analysis; Information theory; Multiaccess communication; Multiuser detection; Performance loss; Signal to noise ratio;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Theory Workshop, 2009. ITW 2009. IEEE
  • Conference_Location
    Taormina
  • Print_ISBN
    978-1-4244-4982-8
  • Electronic_ISBN
    978-1-4244-4983-5
  • Type

    conf

  • DOI
    10.1109/ITW.2009.5351171
  • Filename
    5351171