Wideband Spectrum Sensing for Cognitive Radios: A Multistage Wiener Filter Perspective

A wideband spectrum sensing scheme for cognitive radios is put forward in this letter. The proposed method operates over the total frequency bands simultaneously rather than a single band each time. It first estimates the number of occupied subbands, and then determines the accurate locations of occ...

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Veröffentlicht in:IEEE signal processing letters Jg. 22; H. 3; S. 332 - 335
Hauptverfasser: Qing, Haobo, Liu, Yuanan, Xie, Gang, Gao, Jinchun
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York IEEE 01.03.2015
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:
Algorithms
Blind detection
Blinds
Cognitive radio
Computational complexity
Detection
Eigenvalues
Estimating
Noise
noise uncertainty
Signal to noise ratio
Uncertainty
Wideband
wideband spectrum sensing
Wiener filters
ISSN:1070-9908, 1558-2361
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Zusammenfassung:A wideband spectrum sensing scheme for cognitive radios is put forward in this letter. The proposed method operates over the total frequency bands simultaneously rather than a single band each time. It first estimates the number of occupied subbands, and then determines the accurate locations of occupied subbands as well as the vacant ones. Applying the ideas of multi stage Wiener filter to Gerschgorin disk estimator, this approach jointly makes the decision. In this way, the detection performance is enhanced because of capturing the signal information and suppressing the additive noise. Meanwhile, this approach avoids estimating the covariance matrix as well as the eigenvalue decomposition, and thus achieves a low computational complexity. Distinct from the conventional algorithms, neither noise power estimation nor prior knowledge of primary user signal is required, making the proposed algorithm robust to noise uncertainty and suitable for blind detection. Simulations under various conditions are presented to demonstrate the benefits of this approach and the results indicate that it surpasses the existing sensing algorithms.
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ISSN:1070-9908
1558-2361
DOI:10.1109/LSP.2014.2359491