Abstract
A primary user (PU) is the licensed owner of the spectrum allocated to it. Studies have shown that, for most of the time, spectrum allotted to the PU is unused. This creates an opportunity for the secondary user (SU) to access the spectrum allocated to PU when it is not in use. While opportunistically accessing the unused spectrum, the first step is spectrum sensing. A prior knowledge of spectrum occupancy helps in observing the used spectrum and also detecting the spectrum holes (unused spectrum). In cognitive radio network (CRN), due to the stochastic nature of the spectrum usage, it is difficult to obtain the prior information about the spectrum occupancy of PU. Real-time spectrum sensing and its assignment to SU take a significant amount of time. Hence, to reduce latency for SU, we can resort to the prior prediction of the occupancy. In this paper, we investigate the existing spectrum prediction methods and propose a pattern-sequence-based forecasting (PSF) method for spectrum allocation to SU. The occupancy study of global system for mobile communication (GSM) downlink band from 935 to 960 MHz is carried out and compared to the predicted occupancy.
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Patil, J., Bokde, N., Mishra, S.K., Kulat, K. (2020). PSF-Based Spectrum Occupancy Prediction in Cognitive Radio. In: Venkata Rao, R., Taler, J. (eds) Advanced Engineering Optimization Through Intelligent Techniques. Advances in Intelligent Systems and Computing, vol 949. Springer, Singapore. https://doi.org/10.1007/978-981-13-8196-6_53
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DOI: https://doi.org/10.1007/978-981-13-8196-6_53
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