Spectrum sensing-focused cognitive radio network for 5G revolution

The cognitive radio network (CRN), an instrumental part of the next-generation wireless communication systems, is mainly dependent on spectrum sensing to function properly. can help in clean energy transition and load capacity factors by providing a more efficient accurate utilization. By using it, number spectrums that used for be optimized, which reduce amount consumed network. Additionally, 5G identify classify different types signals, interference improve efficiency It also allow digitization infrastructure facilitate better decision-making processes take into account environmental impacts while optimizing use because its characteristics like non-linearity, detection, scalability, robustness, generalization, non-stationarity environments, dynamic entity, weighted sum Gaussian functions centered at specific frequencies, robustness against noise interference. adapt adjusting parameters, this allows distinguishing between primary secondary users spectrum, why radial basis popular choice networks. Radial networks (RBFNs) work signal classification, adaptation, fast faster decision-making, improved reduction. One most sought-after goals field research creation spectrum-sensing technology dependable intelligent multilayer learning approaches are inappropriate dealing with time-series data due higher misclassification rate inherent computational complexity. To address this, study proposed learns temporal aspects from spectral makes additional statistics such as frequency, efficiency, energy, allocation, distance, duty-cycle time, considered may fine-tune sensor performance. scheme simulated real-time results quite promising terms evaluation parameters.