Abstract
The correlations between spectrum state evolutions, as a kind of similarity measure, have been revealed to optimize the spectrum usage model or improve the performance in spectrum prediction. However, most existing similarity analyses only end up with the superficial similarity phenomenon. It is of great need for us to conduct the deep investigation and analysis on the similarity of spectrum state evolutions. Firstly, we design a similarity index for spectrum state evolutions based on the Euclidean distance. Then, a network of spectrum state evolutions in the frequency domain can be formed for further analysis by comparing the proposed similarity indexes of frequency points with the decision threshold. Experiments with real-world spectrum data prove the feasibility and rationality of the above similarity analysis.
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Acknowledgments
This work is supported in part by the National Natural Science Foundation of China (Grants No. 61501510 and No. 61631020), Natural Science Foundation of Jiangsu Province (Grant No. BK20150717), China Postdoctoral Science Foundation Funded Project (Grant No. 2016M590398) and Jiangsu Planned Projects for Postdoctoral Research Funds (Grant No. 1501009A).
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Sun, J., Yu, L., Li, J., Ding, G. (2020). Similarity Analysis on Spectrum State Evolutions. In: Liang, Q., Liu, X., Na, Z., Wang, W., Mu, J., Zhang, B. (eds) Communications, Signal Processing, and Systems. CSPS 2018. Lecture Notes in Electrical Engineering, vol 516. Springer, Singapore. https://doi.org/10.1007/978-981-13-6504-1_61
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DOI: https://doi.org/10.1007/978-981-13-6504-1_61
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