Cooperative Bayesian Compressed Spectrum Sensing for Correlated Signals in Cognitive Radio Networks 


Vol. 38,  No. 9, pp. 765-774, Sep.  2013


PDF
  Abstract

In this paper, we present a cooperative compressed spectrum sensing scheme for correlated signals in decentralized wideband cognitive radio networks. Compressed sensing is a signal processing technique that can recover signals which are sampled below the Nyquist rate with high probability, and can solve the necessity of high-speed analog-to-digital converter problem for wideband spectrum sensing. In compressed sensing, one of the main issues is to design recovery algorithms which accurately recover original signals from compressed signals. In this paper, in order to achieve high recovery performance, we consider the multiple measurement vector model which has a sequence of compressed signals, and propose a cooperative sparse Bayesian recovery algorithm which models the temporal correlation of the input signals.

  Statistics
Cumulative Counts from November, 2022
Multiple requests among the same browser session are counted as one view. If you mouse over a chart, the values of data points will be shown.


  Cite this article

[IEEE Style]

H. Jung, K. Kim, Y. Shin, "Cooperative Bayesian Compressed Spectrum Sensing for Correlated Signals in Cognitive Radio Networks," The Journal of Korean Institute of Communications and Information Sciences, vol. 38, no. 9, pp. 765-774, 2013. DOI: .

[ACM Style]

Honggyu Jung, Kwangyul Kim, and Yoan Shin. 2013. Cooperative Bayesian Compressed Spectrum Sensing for Correlated Signals in Cognitive Radio Networks. The Journal of Korean Institute of Communications and Information Sciences, 38, 9, (2013), 765-774. DOI: .

[KICS Style]

Honggyu Jung, Kwangyul Kim, Yoan Shin, "Cooperative Bayesian Compressed Spectrum Sensing for Correlated Signals in Cognitive Radio Networks," The Journal of Korean Institute of Communications and Information Sciences, vol. 38, no. 9, pp. 765-774, 9. 2013.

Search
(IN TITLE, AUTHOR, ABSTRACT,KEYWORDS)

Advanced Search ▼

POPULAR KEYWORDS
(TOP 10 KEYWORDS)

Recent Publications
(LAST 3 YEARS)






pISSN : 1226 - 4717
eISSN : 2287 - 3880