Modulated signals used in communication systems exhibits cyclic periodicity. This is primarily due to sinusoidal product modulators, repeating preambles, coding and multiplexing in modern communication. This property of signals can be analyzed using cyclostationary analysis. SCF (Spectral correlation function) of cyclic autocorrelation (CAF) has unique features for different modulated signals and noise. Different techniques are applied to SCF for extracting features on the basis of which decision of detecting a signal or noise is made. In this chapter, study and analysis of different modulated signals used in satellite communication is presented using SCF. Also comparison of several signal detection techniques is provided on the basis of utilizing unique feature exhibit by a normalized vector calculated on SCF along frequency axis. Moreover a signal detection technique is also proposed which identifies the presence of a signal or noise in the analyzed data within the defined threshold limits.
Spectrum Sensing with Combining Spectral Correlation Density for ATSC Signal Detection
