Noor Gul1,2, Saeed Ahmed1,3, Su Min Kim1, Muhammad Sajjad Khan4, Junsu Kim1,*
CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 5209-5227, 2023, DOI:10.32604/cmc.2023.026945
Abstract A cognitive radio network (CRN) intelligently utilizes the available spectral resources by sensing and learning from the radio environment to maximize spectrum utilization. In CRNs, the secondary users (SUs) opportunistically access the primary users (PUs) spectrum. Therefore, unambiguous detection of the PU channel occupancy is the most critical aspect of the operations of CRNs. Cooperative spectrum sensing (CSS) is rated as the best choice for making reliable sensing decisions. This paper employs machine-learning tools to sense the PU channels reliably in CSS. The sensing parameters are reconfigured to maximize the spectrum utilization while reducing sensing error and cost with improved… More >
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