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Home / Archives / Volume-3 / Issue-2 / Article-6

Volume - 3 | Issue - 2 | june 2021

Nakagami-m Fading Detection with Eigen Value Spectrum Algorithms
B Vivekanandam  338  207
Pages: 138-149
Cite this article
Vivekanandam, B. (2021). Nakagami-m Fading Detection with Eigen Value Spectrum Algorithms. Journal of Electronics and Informatics, 3(2), 138-149. doi:10.36548/jei.2021.2.006
Published
12 July, 2021
Abstract

One of the most crucial roles of the cognitive radio (CR) is detection of spectrum ‘holes’. The ‘no a-priori knowledge required’ prospective of blind detection techniques has attracted the attention of researchers and industries, using simple Eigen values. Over the years, a number of study and research has been carried out to determine the impact of thermal noise in the performance of the detector. However, there has not been much work on the impact of man-made noise, which also hinders the performance of the detector. As a result, both man-made impulse noise and thermal Gaussian noise are examined in this proposed study to determine the performance of blind Eigen value-based spectrum sensing. Many studies have been conducted over long sample length by oversampling or increasing the duration of sensing. As a result, a research progress has been made on shorter sample lengths by using a novel algorithm. The proposed system utilizes three algorithms; they are contra-harmonic-mean minimum Eigen value, contra-harmonic mean Maximum Eigen value and maximum Eigenvalue harmonic mean. For smaller sample lengths, there is a substantial rise in the number of cooperative secondary users, as well as a low signal-to-noise ratio when employing the maximum Eigen value Harmonic mean. The experimental analysis of the proposed work with respect to impulse noise and Gaussian signal using Nakagami-m fading channel is observed and the results identified are tabulated.

Keywords

machine learning sentiment analysis deep learning ensemble performance

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