Open AccessDiscrete Markov Chain Based Spectrum Sensing for Cognitive Radio
Author(s) -
Mohammad Reza Amini,
Asra Mirzavandi,
Mosrafa Rezaei
Publication year - 2015
Publication title -
international journal of electrical and computer engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.277
H-Index - 22
ISSN - 2088-8708
DOI - 10.11591/ijece.v5i2.pp297-303
Subject(s) - cognitive radio , computer science , false alarm , markov chain , constraint (computer aided design) , idle , throughput , real time computing , spectrum (functional analysis) , transmission (telecommunications) , channel (broadcasting) , wireless sensor network , collision , algorithm , wireless , computer network , telecommunications , artificial intelligence , mathematics , computer security , physics , geometry , quantum mechanics , machine learning , operating system
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.