Similarity Analysis on Spectrum State Evolutions

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.