Abstract
Wideband spectrum sensing remains an open challenge for cognitive radio networks due to the insufficient wideband sensing capability. This paper introduces the theory of Gaussian Markov Random Field to estimate the un-sensed sub-channel status. We set up a measurement system to capture the WiFi spectrum data. With the measurement data, we verify that the proposed model of Temporal Conditional Gaussian Random Field can efficient estimate the sub-channel status.
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© 2012 ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering
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Zhang, Z., Li, H., Ma, H., Zheng, K., Yang, D., Pei, C. (2012). Spectrum Prediction via Temporal Conditional Gaussian Random Field Model in Wideband Cognitive Radio Networks. In: Zhang, X., Qiao, D. (eds) Quality, Reliability, Security and Robustness in Heterogeneous Networks. QShine 2010. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 74. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29222-4_2
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DOI: https://doi.org/10.1007/978-3-642-29222-4_2
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-29221-7
Online ISBN: 978-3-642-29222-4
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