• DocumentCode
    3603945
  • Title

    Solving a Class of Sum Power Minimization Problems by Generalized Water-Filling

  • Author

    He, Peter ; Lian Zhao

  • Author_Institution
    Dept. of Electr. & Comput. Eng., Ryerson Univ., Toronto, ON, Canada
  • Volume
    14
  • Issue
    12
  • fYear
    2015
  • Firstpage
    6792
  • Lastpage
    6804
  • Abstract
    Radio resource management (RRM) plays an important role in wireless communication systems, especially in more advanced systems with more constraint conditions. In this paper, we first propose a generalized water-filling approach to solve the power allocation problem of minimizing sum power while meeting the target sum rate constraint with weights. Based on this sum power objective function, we extend the proposed method to more complicated RRM problems with more stringent constraints. The proposed algorithms with this generalized approach possess several distinguished features. They provide exact optimal solutions based on non-derivative methods, as the implementation of the proposed algorithms invokes neither the derivative nor the gradient. With geometric interpretation, the proposed algorithms provide more insights into and intuitions of the problems and could be used to efficiently solve a family of the sum power minimization problems. Optimality of the proposed algorithms is strictly proved. Numerical results that illustrate the steps and demonstrate efficiency of the proposed algorithms are presented.
  • Keywords
    channel capacity; geometry; minimisation; radio networks; wireless channels; channel capacity; generalized water-filling approach; geometric interpretation; power allocation problem; radio resource management; sum power minimization problems; sum power objective function; target sum rate constraint; wireless communication systems; Linear programming; Minimization; Resource management; Throughput; Wireless communication; QoS; Water-filling; channel capacity; maximum sum data rate; minimum sum power; optimal radio resource management (RRM); optimization methods;
  • fLanguage
    English
  • Journal_Title
    Wireless Communications, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1536-1276
  • Type

    jour

  • DOI
    10.1109/TWC.2015.2459714
  • Filename
    7164347