Joint Modulation and Coding Recognition Using Deep Learning

Abstract

Blind identification of modulation and channel coding parameters is a very important research topic in civil-military communication systems. The traditional algorithm is mainly implemented in the way of hierarchical recognition, that is, modulation recognition of the signal first, then demodulation of the signal, and finally coding type recognition and parameter estimation of the demodulated information stream, so as to realize the joint recognition of modulation and coding. In this paper, we propose a deep learning (DL)-based joint recognition algorithm for modulation and coding, which can achieve the recognition of modulation type and coding parameters simultaneously without using additional demodulation algorithms. Simulation results show that the proposed method performs well for the recognition of various modulation and coding types under high signal-to-noise ratio (SNR) conditions.