Abstract
In this work, we propose an efficient decision fusion scheme for CSS, which achieves target cooperative probability of detection while maintaining a lower cooperative false alarm probability which eventually enhances the network throughput. The proposed scheme enables the fusion center (FC) to select secondary users (SUs) for decision fusion according to their reliability weights. For every SU, the reliability weight is computed by jointly considering the reporting information of SUs for past K time slots along with their detection and false alarm probabilities. The value of K is determined by computing the entropy on primary user (PU) activities observed on a designated channel over a certain period of time. Simulation-based study shows the efficacy of the proposed scheme in terms of reducing in cooperative probability of false alarm and improving the network throughput compared to conventional approach.
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Chauhan, P., Deka, S.K., Sarma, N. (2021). An Efficient Decision Fusion Scheme for Cooperative Spectrum Sensing for Cognitive Radio Networks. In: Mandal, J., Mukhopadhyay, S., Roy, A. (eds) Applications of Internet of Things. Lecture Notes in Networks and Systems, vol 137. Springer, Singapore. https://doi.org/10.1007/978-981-15-6198-6_7
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DOI: https://doi.org/10.1007/978-981-15-6198-6_7
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