IDEAS home Printed from https://ideas.repec.org/a/spr/telsys/v67y2018i2d10.1007_s11235-017-0327-y.html
   My bibliography  Save this article

Performance analysis of end-to-end SNR estimators for AF relaying

Author

Listed:
  • Yulin Zhou

    (University of Warwick)

  • Yunfei Chen

    (University of Warwick)

Abstract

Many existing signal-to-noise ratio (SNR) estimators were designed and evaluated for conventional one-hop communications systems. However, for a relaying system, it is the end-to-end SNR that determines the system performance. In this paper, we will fill this gap by evaluating the performances of the existing SNR estimators in a dual-hop relaying system used for each hop. The probability density functions of the SNR estimators are first derived, whose parameters are fitted as functions of the sample size and the true value of SNR. Using them, the cumulative distribution functions of the end-to-end SNR and the bit error rate performance for a relaying system are derived. Numerical results show that the squared signal-to-noise variance estimator has the best performance for small SNRs and the second-order fourth-order moments estimator has the best performance for large SNRs, while the signal-to-variation ratio estimator has the worst performance, among the existing SNR estimators, for AF relaying systems.

Suggested Citation

  • Yulin Zhou & Yunfei Chen, 2018. "Performance analysis of end-to-end SNR estimators for AF relaying," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 67(2), pages 269-280, February.
  • Handle: RePEc:spr:telsys:v:67:y:2018:i:2:d:10.1007_s11235-017-0327-y
    DOI: 10.1007/s11235-017-0327-y
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11235-017-0327-y
    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/s11235-017-0327-y?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.

    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:telsys:v:67:y:2018:i:2:d:10.1007_s11235-017-0327-y. 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.