Discrete Markov Chain Based Spectrum Sensing for Cognitive Radio

Abstract

Spectrum sensing is one of the functionalities of cognitive radios to exploit spectrum holes without interrupting primary users transmission. The more efficient of the spectrum sensing, the highest the throughput of secondary and primary network. This paper presents spectrum sensing method based on phase type modelling that is simple to do for secondary users to conclude about the channel state (idle or busy) under collision constraint. The parameters of phase type model can be adjusted based on desired operating point of the receiver sensor in its ROC curve. The presented approach can run a trade off between sensing time and the two error probabilities of sensor false alarm and miss-detection.