Fast Two-Step Energy Detection for Spectrum Sensing
Joint Authors
Lai, Meiling
Peng, Shengliang
Yang, Xi
Zhou, Lin
Source
Journal of Electrical and Computer Engineering
Issue
Vol. 2015, Issue 2015 (31 Dec. 2015), pp.1-6, 6 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2015-03-30
Country of Publication
Egypt
No. of Pages
6
Main Subjects
Information Technology and Computer Science
Abstract EN
Spectrum sensing is one of the key tasks in cognitive radio.
This paper proposes a fast two-step energy detection (FED) algorithm for spectrum sensing via improving the sampling process of conventional energy detection (CED).
The algorithm adaptively selects N -point or 2 N -point sampling by comparing its observed energy with prefixed double thresholds, and thereby is superior in sampling time and detection speed.
Moreover, under the constraint of constant false alarm, this paper optimizes the thresholds from maximizing detection probability point of view.
Theoretical analyses and simulation results show that, compared with CED, the proposed FED can achieve significant gain in detection speed at the expense of slight accuracy loss.
Specifically, within high signal-to-noise ratio regions, as much as 25% of samples can be reduced.
American Psychological Association (APA)
Lai, Meiling& Peng, Shengliang& Yang, Xi& Zhou, Lin. 2015. Fast Two-Step Energy Detection for Spectrum Sensing. Journal of Electrical and Computer Engineering،Vol. 2015, no. 2015, pp.1-6.
https://search.emarefa.net/detail/BIM-1068132
Modern Language Association (MLA)
Lai, Meiling…[et al.]. Fast Two-Step Energy Detection for Spectrum Sensing. Journal of Electrical and Computer Engineering No. 2015 (2015), pp.1-6.
https://search.emarefa.net/detail/BIM-1068132
American Medical Association (AMA)
Lai, Meiling& Peng, Shengliang& Yang, Xi& Zhou, Lin. Fast Two-Step Energy Detection for Spectrum Sensing. Journal of Electrical and Computer Engineering. 2015. Vol. 2015, no. 2015, pp.1-6.
https://search.emarefa.net/detail/BIM-1068132
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1068132