NDLI: Cooperative sensing based on permutation entropy with adaptive thresholding technique for cognitive radio networks

Content Provider	IET Digital Library
Author	Srinu, Sesham Mishra, Amit Kumar
Abstract	Spectrum sensing in the low signal-to-noise ratio (SNR) environment is vital task for the evolution of cognitive radio technology. The numerous signal processing algorithms have since been proposed to improve the spectrum sensing performance. In the recent past, entropy based sensing methods are shown to be robust in a low SNR environment with small data sets. However, these methods only focus on information content and ignore temporal order of the signal. Hence, selection of appropriate entropy technique that considers both information content and temporal order is important. In addition, many works consider that the distribution of noise follows Gaussian under assumption that the sample size is infinity. The detection threshold designed using this assumption yield unreliable decisions. On the contrary, the captured data is limited in real-time and it should be minimum to reduce the computational complexity. To address these two issues, empirical permutation entropy with adaptive thresholding detection technique is proposed. Then, the work is extended to weighted gain cooperative sensing that uses Higuchi fractal dimension method to generate weight for each node. Simulation results reveal that the proposed method is robust, less sensitive to sample size, and improves the single node as well as multinode sensing performance.
Starting Page	934
Ending Page	942
Page Count	9
ISSN	17518822
Volume Number	10
e-ISSN	17518830
Issue Number	Issue 8, Nov (2016)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-smt/10/8
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-smt.2016.0152
Journal	IET Science, Measurement & Technology
Publisher Date	2016-11-01
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Adaptive Threshold Framing Adaptive Thresholding Technique Cognitive Radio Cognitive Radio Network Communication Complexity Computational Complexity Cooperative Communication Cooperative Sensing Entropy Fractals Gaussian Distribution Gaussian Noise Gaussian Noise Distribution Higuchi Fractal Dimension Method Legislation, Frequency Allocation And Spectrum Pollution Multinode Sensing Performance Permutation Entropy Detection Method Radio Link And Equipment Radio Network Radio Spectrum Management Signal Detection Signal Processing Algorithm Signal to Noise Ratio SNR Spectrum Sensing Performance Statistics
Content Type	Text
Resource Type	Article
Subject	Atomic and Molecular Physics, and Optics Electrical and Electronic Engineering

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