Joint Detection Algorithm for Spectrum Sensing Over Multipath Time-Variant Flat Fading Channels
A popular approach to spectrum sensing is matched filter which could achieve the optimum performance in short sensing time. Under multipath time-variant flat fading channel, this conventional spectrum sensing method could be cumbersome to implement due to channel variation. This paper puts forward a new spectrum sensing algorithm in allusion to this defect. We firstly propose a dynamic state-space model which could thoroughly characterize the evolution of two hidden states: primary user state and the multipath fading channel. Then a promising joint estimation algorithm of these two states based on maximum a posteriori probability criteria and particle filtering technology is presented. Experimental simulations are provided to demonstrate the superior performance of our presented joint detection scheme.
KeywordsSpectrum sensing Multipath time-variant flat fading channel Dynamic state-space model Joint estimation Particle filtering
This work was supported by the National Natural Science Foundation of China (61271180), Major National Science and Technology Projects (2012zx03001022) and Special Foundation for State Internet of Things Program (Radio frequency and communication security testing service platform of Internet of things).
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