Ad Hoc Networks. 8th International Conference, ADHOCNETS 2016, Ottawa, Canada, September 26-27, 2016, Revised Selected Papers

Research Article

Optimizing Power Allocation in Wireless Networks: Are the Implicit Constraints Really Redundant?

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  • @INPROCEEDINGS{10.1007/978-3-319-51204-4_12,
        author={Xiuhua Li and Victor Leung},
        title={Optimizing Power Allocation in Wireless Networks: Are the Implicit Constraints Really Redundant?},
        proceedings={Ad Hoc Networks. 8th International Conference, ADHOCNETS 2016, Ottawa, Canada, September 26-27, 2016, Revised Selected Papers},
        proceedings_a={ADHOCNETS},
        year={2017},
        month={4},
        keywords={Power allocation Water-filling Subgradient method},
        doi={10.1007/978-3-319-51204-4_12}
    }
    
  • Xiuhua Li
    Victor Leung
    Year: 2017
    Optimizing Power Allocation in Wireless Networks: Are the Implicit Constraints Really Redundant?
    ADHOCNETS
    Springer
    DOI: 10.1007/978-3-319-51204-4_12
Xiuhua Li1,*, Victor Leung1,*
  • 1: The University of British Columbia
*Contact email: lixiuhua@ece.ubc.ca, vleung@ece.ubc.ca

Abstract

The widely considered power constraints on optimizing power allocation in wireless networks, e.g., , and where and are given constants, imply the constraints, i.e., . However, the related implicit constraints are regarded as redundant in the most current studies. In this paper, we explore the question “Are the implicit constraints really redundant?” in the optimization of power allocation especially when using iterative methods that have slow convergence speeds. Using the water-filling problem as an illustration, we derive the structural properties of the optimal solutions based on Karush-Kuhn-Tucker conditions, propose a non-iterative closed-form optimal method, and use subgradient methods to solve the problem. Our theoretical analysis shows that the implicit constraints are not redundant, and their consideration can effectively speed up convergence of the used iterative methods and reduce the sensitivity to the chosen step sizes. Numerical results for the water-filling problem and another existing power allocation problem confirm the effectiveness of considering the implicit constraints.