Adaptive double threshold energy detection based on Markov model for cognitive radio

Yulei Liu, Jun Liang, Nan Xiao, Xiaogang Yuan, Zhenhao Zhang, Meng Hu and Yulong Hu

PLOS ONE, 2017, vol. 12, issue 5, 1-18

Abstract: The rapid development in the area of cognitive radio technology leads the society to higher standards of spectrum sensing performance, particularly in low signal-to-noise ratio (SNR) environment. This article proposes an adaptive double-threshold energy sensing method based on Markov model (ADEMM). When using the double-threshold energy sensing method, the modified Markov model that accounts for the time varying characteristic of the channel occupancy was presented to resolve the ‘confused’ channel state. Furthermore, in order to overcome the effect of noise uncertainty, the findings of this article introduce an adaptive double-threshold spectrum sensing method that adjusts its thresholds according to the achievable maximal detection probability. Numerical simulations show that the proposed ADEMM achieves better detection performance than the conventional double-threshold energy sensing schemes, especially in very low SNR region.

Date: 2017
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0177625 (text/html)
https://journals.plos.org/plosone/article/file?id= ... 77625&type=printable (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0177625

DOI: 10.1371/journal.pone.0177625

Access Statistics for this article

More articles in PLOS ONE from Public Library of Science
Bibliographic data for series maintained by plosone ().