KEYWORDS: Cognitive modeling, Interference (communication), Performance modeling, Sensing systems, Statistical analysis, Databases, Time-frequency analysis, Systems modeling, Signal to noise ratio, Received signal strength
Spectrum sensing in cognitive radio is a key technology to improve spectrum utilization. However, the current spectrum sensing algorithms have limited accuracy and are not flexible enough in complex communication environment. In this paper, a spectrum sensing algorithm based on adaptive regional model is proposed. The spatial information of the regional model is used to improve the performance of spectrum sensing. Through the adaptive adjustment, the cognitive nodes at different distances in the regional model ensures the sensing performance of the whole region. Results show that the regional model can improve the spectrum efficiency and deal with the complex environment of multi primary user base stations. The spectrum utilization of single region model is improved by 9% and the average difference between actual model accuracy and prediction accuracy is 0.48%. Through this regional model, a spectrum sensing algorithm with adaptive adjustment and high frequency spectrum utilization is realized.
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