IDEAS home Printed from https://ideas.repec.org/a/eee/apmaco/v318y2018icp215-226.html
   My bibliography  Save this article

An efficient DCA based algorithm for power control in large scale wireless networks

Author

Listed:
  • Le Thi, Hoai An
  • Ta, Anh Son
  • Pham Dinh, Tao

Abstract

In recent years, power control and resource allocation techniques for cellular communication systems are very active research areas. Power control is typically used in wireless cellular networks in order to optimize the transmission subject to quality of service (QoS) constraints. One of the most popular power control problems is based on maximizing the weighted sum of data rates under the peak power constraints for all users. It is a difficult nonconvex optimization problem for which standard approach Geometric Programming is not applicable in large scale setting. In this paper, we propose an efficient method based on DC (Difference of Convex functions) programming and DCA (DC Algorithm), an innovative approach in nonconvex programming framework for solving this problem. The purpose is to develop fast and scalable algorithms able to handle large scale systems. The two main challenges in DC programming and DCA that are the effect of DC decomposition and the efficiency of solution methods to convex subproblems are carefully studied. The computational results on several datasets show the robustness as well as the efficiency of the proposed method in terms of both quality and rapidity, and their superiority compared with the standard approach Geometric Programming.

Suggested Citation

  • Le Thi, Hoai An & Ta, Anh Son & Pham Dinh, Tao, 2018. "An efficient DCA based algorithm for power control in large scale wireless networks," Applied Mathematics and Computation, Elsevier, vol. 318(C), pages 215-226.
    • Handle: RePEc:eee:apmaco:v:318:y:2018:i:c:p:215-226
    DOI: 10.1016/j.amc.2017.08.061
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0096300317306197
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.amc.2017.08.061?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. N. Maculan & C.P. Santiago & E.M. Macambira & M.H.C. Jardim, 2003. "An O(n) Algorithm for Projecting a Vector on the Intersection of a Hyperplane and a Box in Rn," Journal of Optimization Theory and Applications, Springer, vol. 117(3), pages 553-574, June.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Chen, Yong & Li, Jiarui & Sun, Miaoping & Niu, Fuxi, 2024. "Robust distributed Nash equilibrium seeking for high-order systems with disturbances and coupling constraints," Applied Mathematics and Computation, Elsevier, vol. 477(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Patriksson, Michael, 2008. "A survey on the continuous nonlinear resource allocation problem," European Journal of Operational Research, Elsevier, vol. 185(1), pages 1-46, February.
    2. Shiyun Wang, 2020. "The Geometric Properties of a Class of Nonsymmetric Cones," Indian Journal of Pure and Applied Mathematics, Springer, vol. 51(3), pages 989-1002, September.
    3. K. C. Kiwiel, 2007. "On Linear-Time Algorithms for the Continuous Quadratic Knapsack Problem," Journal of Optimization Theory and Applications, Springer, vol. 134(3), pages 549-554, September.
    4. Aviad Aberdam & Amir Beck, 2022. "An Accelerated Coordinate Gradient Descent Algorithm for Non-separable Composite Optimization," Journal of Optimization Theory and Applications, Springer, vol. 193(1), pages 219-246, June.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:apmaco:v:318:y:2018:i:c:p:215-226. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/applied-mathematics-and-computation .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.