Investigation of blind detection of modulation schemes using cyclostationarity in underwater communication channels

Abstract

Blind detection of modulation, i.e., without any prior knowledge of the signal, the carrier frequency, timing, etc., is a challenging task for receivers. With growing advancement in communications, more emphasis is placed on computationally efficient ways to detect modulation schemes. This forms the basis for automatic modulation recognition that is being used in cognitive radios. This dissertation looks into Cyclostationary techniques for modulation detection, which is still constantly advancing. Spectral Correlation Density Function (SCF) which computes the correlation between spectrally shifted versions of a signal, is used in the detection of some of the digital modulations such as Binary Phase Shift Keying (BPSK), Quartenary Phase Shift Keying (QPSK), Differentially encoded BPSK and Binary Continuous Phase Frequency Shift Keying (Binary-CPFSK). This dissertations investigates the use of SCF in the detection of these modulations in Additive White Gaussian Noise (AWGN) and Underwater channel. It is found that the SCF features can be used reasonably well to classify most of these modulations in a noisy environment such as the model considered for the underwater channel.