Feature extraction from digital communication signals using wavelet transforms

Abstract

Proportional bandwidth processing and wavelet transforms are applied to extract transient features from digital communication signals. Switching times of noisy BPSK, QPSK, FSK, and ASK signals are detected. The scalogram based on a variety of wavelet functions is used to detect the switching times above a threshold signal to noise ratio. Classical wavelets, proportional bandwidth processing schemes and the Morlet wavelet transform are applied.