NDLI: Blind continuous hidden Markov model-based spectrum sensing and recognition for primary user with multiple power levels

Content Provider	IET Digital Library
Author	Liu, Boyang Li, Zan Si, Jiangbo Zhou, Fuhui
Abstract	Spectrum sensing has been well studied because of its significance in cognitive radio. Different from the existing works which a primary user (PU) is assumed to have only one constant transmit power, a more practical scenario that the PU transmitting with multiple power levels is considered. A continuous hidden Markov model (CHMM)-based blind algorithm for not only detecting the presence of PU but also recognising the transmit power level of the PU is proposed. The training problem of CHMM is solved by combining the wavelet singularity detection with k-means clustering algorithm. An effective method for estimation of the number of power levels is proposed. Two different strategies are designed to perform spectrum sensing. Simulation results show the efficiency of the proposed algorithm.
Starting Page	1396
Ending Page	1403
Page Count	8
ISSN	17518628
Volume Number	9
e-ISSN	17518636
Issue Number	Issue 11, Jul (2015)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-com/9/11
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-com.2015.0090
Journal	IET Communications
Publisher Date	2015-05-20
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Blind Continuous Hidden Markov Model-based Spectrum Sensing CHMM-based Blind Algorithm Cognitive Radio Hidden Markov Model Integral Transforms in Numerical Analysis K-means Clustering Algorithm Markov Processes Multiple Power Level Pattern Clustering Primary User PU Transmit Power Level Recognition Radio Link And Equipment Radio Spectrum Management Signal Detection Spectrum Recognition Wavelet Singularity Detection Wavelet Transform
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering Computer Science Applications

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