2012
DOI: 10.1109/lcomm.2012.092812.121648
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Adaptive Compressive Spectrum Sensing for Wideband Cognitive Radios

Abstract: This letter presents an adaptive spectrum sensing algorithm that detects wideband spectrum using sub-Nyquist sampling rates. By taking advantage of compressed sensing (CS), the proposed algorithm reconstructs the wideband spectrum from compressed samples. Furthermore, an l2 norm validation approach is proposed that enables cognitive radios (CRs) to automatically terminate the signal acquisition once the current spectral recovery is satisfactory, leading to enhanced CR throughput. Numerical results show that th… Show more

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Cited by 69 publications
(38 citation statements)
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“…In [119], an adaptive SS algorithm, which can adaptively adjust compressed measurements without any sparsity estimation efforts, has been studied. Consequently, the wideband signals are acquired block-by-block from multiple mini-time slots, and gradually reconstruct the wideband spectrum using compressed samples until the spectral recovery is satisfactory.…”
Section: Wideband Spectrum Sensingmentioning
confidence: 99%
“…In [119], an adaptive SS algorithm, which can adaptively adjust compressed measurements without any sparsity estimation efforts, has been studied. Consequently, the wideband signals are acquired block-by-block from multiple mini-time slots, and gradually reconstruct the wideband spectrum using compressed samples until the spectral recovery is satisfactory.…”
Section: Wideband Spectrum Sensingmentioning
confidence: 99%
“…Client nodes have to monitor the current band periodically to check PU activities before occupying it for data transmission. This protection shall include both PU transmitters and PU receivers [24]- [26]. PU receivers are particularly important for those applications with unidirectional transmission, such as TV broadcast.…”
Section: Literature Review Of Rpl Routing Protocolmentioning
confidence: 99%
“…To improve the probability of false alarm, we shall reduce the number of elements in the set Υ k in (23). This is mainly because the sum term…”
Section: Multi-rate Sub-nyquist Spectrum Sensingmentioning
confidence: 99%
“…Later on, the CSbased approach has attracted much attention [16]- [21] owing to its advantage of using much fewer samples to perform wideband spectrum sensing. In our previous work [23], to save system energy, adaptive CS-based spectrum sensing approach was proposed that could find the best spectral recovery with high confidence. Unfortunately, using CS-based approaches, the spectral recovery requires high computational complexity, leading to a high spectrum sensing overhead that may be a serious issue in CRs with restricted computational resources.…”
Section: Introductionmentioning
confidence: 99%