A New Key Features Extraction Algorithm for Automatic Digital Modulation Recognition

This paper introduces a new algorithm for key features extraction of digital modulations recognition. This new algorithm utilizes complexity approach in which a set of value of Lempel-Ziv complexity for identifying different types of modulations is developed. The set of value is derived from three important parameters - the instantaneous amplitude, phase, and frequency of the intercepted digitally modulated signals. Computer simulations of different types of band-limited digitally modulated signals corrupted by band-limited Gaussian noise sequences have been carried out to measure the performance of the developed algorithm.