Abstract—As the demand for radio spectrum continues to rise, one possible approach to addressing the problem with limited spectrum is cognitive radio. The most important aspect of effective cognitive radio implementation is spectrum sensing. In this context, we propose and examine the effectiveness of a K-means and eigenvalue-based learning method for Cooperative spectrum sensing in an α-κ-μ generalized fading channel. To measure how well the proposed method is working, we utilize receiver operating characteristic curves. In addition, a comparative analysis is performed with existing detection techniques like cooperative spectrum sensing using K-means-based energy detection specifically designed for κ-μ and α-κ-μ fading channels. Based on the findings of the MATLAB version of the simulation, the proposed approach is superior to an existing one in terms of comparison parameters.

Keywords—cooperative spectrum sensing, eigenvalues, K-means, detection probability


Cite: Srinivas Samala, Subhashree Mishra, and Sudhansu Sekhar Singh, “Machine Learning and an Eigenvalue-Based Technique to Improve Cooperative Spectrum Sensing in Generalized α-κ-μ Fading Channel," Journal of Communications, vol. 19, no. 5, pp. 222-228, 2024.



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