Cyclic Spectrum Analysis of FSK Modulated Signals

In this paper, we provide a comprehensive analysis of cyclic cross-correlation functions for FSK modulated signals and their corresponding cyclic spectral diagrams. The cyclic cross-correlation function serves as a method to measure signal similarity and detect periodic components within signals. The cyclic spectrum represents the frequency-domain expression of this correlation function, revealing the signal's frequency distribution characteristics. These visualizations can be effectively represented using both three-dimensional coordinate plots and two-dimensional slice diagrams, enabling clearer understanding of signal properties. From an implementation perspective, the algorithm utilizes Fourier transform operations to compute cyclic frequencies and spectral correlation densities. Key functions would involve spectral estimation techniques and cyclic frequency detection algorithms to properly identify signal periodicities. Additionally, we present efficient computational algorithms to facilitate improved processing and analysis of these signals, including optimization methods for reducing computational complexity in practical applications.