• DocumentCode
    2334676
  • Title

    SPC10-2: Iterative Water-filling for Optimal Resource Allocation in OFDM Multiple-Access and Broadcast Channels

  • Author

    Yu, David D. ; Cioffi, John M.

  • Author_Institution
    Dept. of Electr. Eng., Stanford Univ., Stanford, CA
  • fYear
    2006
  • fDate
    Nov. 27 2006-Dec. 1 2006
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    A class of optimal resource allocation problems in linear Gaussian multiple-access and broadcast channels (MAC and BC) can be summarized as weighted sum power minimization problem. In this paper an iterative water-filling algorithm is proposed to solve this problem efficiently. It is shown that by formulating an explicit rate expression for MAC, though non-convex of power spectral densities, the optimality conditions demonstrate a strong water-filling flavor. By iteratively solving the optimality conditions, whereas in each iteration a slightly modified single-user margin adaptive water-filling(MAWF) algorithm is applied to update the dual variable in a greedy manner, the power spectral density of each user converges to the optimal solution very fast. Simulations verify convergence and optimality. The problem in BC can be solved in its dual MAC.
  • Keywords
    OFDM modulation; broadcast channels; iterative methods; resource allocation; OFDM; broadcast channels; iterative water-filling; multiple-access channels; optimal resource allocation; power spectral densities; weighted sum power minimization problem; Broadcasting; Embedded computing; Fading; Intersymbol interference; Iterative algorithms; Iterative decoding; Minimization methods; OFDM; Quality of service; Resource management;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Global Telecommunications Conference, 2006. GLOBECOM '06. IEEE
  • Conference_Location
    San Francisco, CA
  • ISSN
    1930-529X
  • Print_ISBN
    1-4244-0356-1
  • Electronic_ISBN
    1930-529X
  • Type

    conf

  • DOI
    10.1109/GLOCOM.2006.587
  • Filename
    4151217