Adaptive Cooperative Spectrum Sensing Using Group Intelligence

Sreenivasan, Rajagopal; Gvk, Sasirekha; Bapat, Jyotsna

doi:10.5121/ijcnc.2011.3303

Cited by 3 publications

(2 citation statements)

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“…Note that the Rice fading distribution in equation (6) presents two extreme cases: 1. If the dominant signal A = 0, p(r) become the Rayleigh fading distribution in equation (5).…”

Section: Multipath Fading Channelmentioning

confidence: 99%

“…Transmitter detection and interference-based detection [2] are the two broad categories for frequency spectrum 'holes' detection methods. Transmitter detection method includes matched filter detection [3], energy detection [4,5], cyclostationary feature detection [6] and wavelet detection [7]. Matched filter detection approach is a coherent detector, it is optimal in stationary Gaussian noise, and achieves high gain in less time.…”

Section: Introductionmentioning

confidence: 99%

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Dynamic Spectrum Detection Via Compressive Sensing

Odejide¹

2012

IJCNC

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Spectrum congestion is a major concern in both military and commercial wireless networks. To support growing demand for ubiquitous spectrum usage, Cognitive Radio is a new paradigm in wireless communication that can be used to exploit unused part of the spectrum by dynamically adjusting its operating parameters. While cognitive radio technology is a promising solution to the spectral congestion problem, efficient methods for detecting white spaces in wideband radio spectrum remain a challenge. Conventional methods of detection are forced to use the high sampling rate requirement of Nyquist criterion. In this paper, the feasibility and efficacy of using compressive sensing (CS) algorithms in conjunction with Haar wavelet for identifying spectrum holes in the wideband spectrum is explored. Compressive sensing is an emerging theory that shows that it's possible to achieve good reconstruction, at sampling rates lower than that specified by Nyquist. CS approach is robust in AWGN and fading channel.

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“…Note that the Rice fading distribution in equation (6) presents two extreme cases: 1. If the dominant signal A = 0, p(r) become the Rayleigh fading distribution in equation (5).…”

Section: Multipath Fading Channelmentioning

confidence: 99%