Machine Learning-Based Cooperative Spectrum Sensing in A Generalized α-κ-μ Fading Channel
NOPR - NISCAIR Online Periodicals Repository
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Title |
Machine Learning-Based Cooperative Spectrum Sensing in A Generalized α-κ-μ Fading Channel
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Creator |
Samala, Srinivas
Mishra, Subhashree Singh, Sudhansu Sekhar |
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Subject |
Cooperative spectrum sensing
Classification k-means clustering α-κ-μ channel |
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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. |
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Date |
2023-02-08T05:21:46Z
2023-02-08T05:21:46Z 2023-02 |
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Type |
Article
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Identifier |
0022-4456 (Print); 0975-1084 (Online)
http://nopr.niscpr.res.in/handle/123456789/61363 https://doi.org/10.56042/jsir.v82i2.69927 |
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Language |
en
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Publisher |
NIScPR-CSIR,India
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Source |
JSIR Vol.82(02) [February 2023]
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