Wavelet Packet Transform Technique Based on Entropy Estimation for Cognitive Radio Networks
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Abstract
To resolve the issue of spectrum underutilization, Cognitive Radio (CR) arises to be an enticing solution. Among its fundamental functions, the key function of CR system is spectrum sensing where it senses the electromagnetic environment to detect spectrum holes (vacant frequency bands), which can be utilized by Secondary User’s (SU) to achieve increased spectral efficiency. This requires high accuracy and minimal complexity. In this paper, Wavelet Packet Transform Technique Based on Entropy Estimation for Sensing Spectrum Holes in Cognitive Radio Networks is proposed. The proposed technique needs no prior information about Primary User (PU) signal. The wavelet packet probability vector can estimate spectrum holes in the radio spectrum with simple and less computationally complex structure, as it contains vital information about frequency locations of wavelet sub-bands.
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Keywords: Cognitive Radio, spectrum sensing, primary user detection, wavelet packet transform, entropy
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