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Machine Learning-Based Cooperative Spectrum Sensing in A Generalized α-κ-μ Fading Channel

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Field Value
 
Title Machine Learning-Based Cooperative Spectrum Sensing in A Generalized α-κ-μ Fading Channel
 
Creator Samala, Srinivas
Mishra, Subhashree
Singh, Sudhansu Sekhar
 
Subject Cooperative spectrum sensing
Classification
k-means clustering
α-κ-μ channel
 
Description 219-225
An improvement in spectrum usage is possible with the help of a cognitive radio network, which allows secondary users’
access to the unused licensed frequency band of a primary user. Thus, spectrum sensing is a fundamental concept in
cognitive radio networks. In recent years, Cooperative spectrum sensing using machine learning has garnered a great deal of
attention as a technique of enhancing sensing capability. In this study, K-means clustering is taken into consideration for the
purpose of analyzing the effectiveness of cooperative spectrum sensing in a generalized α-κ-μ fading channel. The proposed
approach is examined using receiver operating characteristic curves to determine its performance. The effectiveness of the
proposed strategy is contrasted with that of the existing detection techniques such as Cooperating spectrum sensing based on
energy detection and OR-fusion-based cooperative spectrum sensing for fading channels κ-μ, α-κ-μ. As demonstrated by
results, the proposed method outshines an existing method in terms of comparison parameters, as determined by simulation
results in the MATLAB version.
 
Date 2023-02-08T05:21:46Z
2023-02-08T05:21:46Z
2023-02
 
Type Article
 
Identifier 0022-4456 (Print); 0975-1084 (Online)
http://nopr.niscpr.res.in/handle/123456789/61363
https://doi.org/10.56042/jsir.v82i2.69927
 
Language en
 
Publisher NIScPR-CSIR,India
 
Source JSIR Vol.82(02) [February 2023]