NeXt generation/dynamic spectrum access/cognitive radio wireless networks: a survey
Computer Networks: The International Journal of Computer and Telecommunications Networking
Optimal multiband joint detection for spectrum sensing in cognitive radio networks
IEEE Transactions on Signal Processing
Invariant wideband spectrum sensing under unknown variances
IEEE Transactions on Wireless Communications
Blind detection of wideband interference for cognitive radio applications
EURASIP Journal on Advances in Signal Processing - Special issue on dynamic spectrum access for wireless networking
EURASIP Journal on Wireless Communications and Networking - Special issue on dynamic spectrum access: from the concept to the implementation
Optimal Wideband Spectrum Sensing Framework for Cognitive Radio Systems
IEEE Transactions on Signal Processing
A survey of spectrum sensing algorithms for cognitive radio applications
IEEE Communications Surveys & Tutorials
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Spectrum sensing plays a central role in cognitive radio (CR), because it represents the way that the radio looks for unused (and thus available) portions of the spectrum, often called spectrum holes. The detection of spectrum holes requires wideband spectrum sensing techniques, capable to observe a wide frequency band and to correctly identify which portions of such band contain only noise. In this work, we propose a novel wideband spectrum sensing technique relying on a model order selection problem, which in turn is solved by information theoretic criteria (ITC). This strategy exploits jointly spectral correlation and received energy to discern signals from noise in a blind way. Indeed the proposed algorithm does not require neither the knowledge of the noise power nor any a-priori information about the number, and the characteristics, of the signals to be detected. Numerical results reveal that the algorithm proposed outperforms the existing ones, especially in the presence of spectral correlation.