IDEAS home Printed from https://ideas.repec.org/a/spr/jcomop/v35y2018i2d10.1007_s10878-017-0186-1.html
   My bibliography  Save this article

A low complexity semidefinite relaxation for large-scale MIMO detection

Author

Listed:
  • Rupaj Kumar Nayak

    (International Institute of Information Technology)

  • Mahendra Prasad Biswal

    (Indian Institute of Technology Kharagpur)

Abstract

Many wireless communication problems is based on a convex relaxation of the maximum likelihood problem which further can be cast as binary quadratic programs (BQPs). The two standard relaxation methods that are widely used for solving general BQPs such as spectral methods and semidefinite programming problem (SDP), each have their own advantages and disadvantages. It is widely accepted that small and medium sized SDP problems can be solved efficiently by interior point methods. Albeit, semidefinite relaxation has a tighter bound for large scale problems, but its computational complexity is high. However, Row-by-Row method (RBR) for solving SDPs could be opted for an alternative for large-scale MIMO detection because of low complexity. The present work is a spectral SDP-cut formulation to which the RBR is applied for large-scale MIMO detection. A modified RBR algorithm with tighter bound is presented to specify the efficiency in detecting massive MIMO.

Suggested Citation

  • Rupaj Kumar Nayak & Mahendra Prasad Biswal, 2018. "A low complexity semidefinite relaxation for large-scale MIMO detection," Journal of Combinatorial Optimization, Springer, vol. 35(2), pages 473-492, February.
    • Handle: RePEc:spr:jcomop:v:35:y:2018:i:2:d:10.1007_s10878-017-0186-1
    DOI: 10.1007/s10878-017-0186-1
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10878-017-0186-1
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10878-017-0186-1?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.

    Citations

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


    Cited by:

    1. Rupaj Kumar Nayak & Nirmalya Kumar Mohanty, 2019. "Improved row-by-row method for binary quadratic optimization problems," Annals of Operations Research, Springer, vol. 275(2), pages 587-605, April.
    2. Rupaj Kumar Nayak & Nirmalya Kumar Mohanty, 2020. "Solution of boolean quadratic programming problems by two augmented Lagrangian algorithms based on a continuous relaxation," Journal of Combinatorial Optimization, Springer, vol. 39(3), pages 792-825, April.

    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:spr:jcomop:v:35:y:2018:i:2:d:10.1007_s10878-017-0186-1. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.