On the Evaluation of an Entropy-Based Spectrum Sensing Strategy Applied to Cognitive Radio Networks | Zendy

Guillermo Prieto | Zendy; Angel G. Andrade | Zendy; Daniela M. Martinez | Zendy; Guillermo Galaviz | Zendy

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On the Evaluation of an Entropy-Based Spectrum Sensing Strategy Applied to Cognitive Radio Networks

Author(s) -

Guillermo Prieto,

Angel G. Andrade,

Daniela M. Martinez,

Guillermo Galaviz

Publication year - 2018

Publication title -

ieee access

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.587

H-Index - 127

ISSN - 2169-3536

DOI - 10.1109/access.2018.2876499

Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation

In this paper, the evaluation of a spectrum sensing strategy based on the frequency domain entropy applied to cognitive radio networks is presented. Entropy estimation is performed using Bartlett periodogram. A tradeoff between variance and the spectral resolution for Bartlett periodogram is presented. This tradeoff affects the probability of detection and false alarm of the spectrum sensing strategy in environments with low signal-to-noise ratio and noise uncertainty. The Entropy detector is optimal when the product of the number of segments and the number of points used is equal to the number of available samples of the received signal.

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