Likelihood-Ratio Approaches to Automatic Modulation Classification

Adaptive modulation and automatic modulation classification are highly demanded in software-defined radio (SDR) for both commercial and military applications. Various design options of automatic classifiers have attracted researchers in developing 3G and 4G wireless communication systems. There is an urgent need to investigate the different methods of coherent and noncoherent modulation estimations, discuss the challenges in cooperative and noncooperative communication environment, and understand the distinct requirements in real-time modulation classifications. This survey paper focuses on the automatic modulation classification methods based on likelihood functions, studies various classification solutions derived from likelihood ratio test, and discusses the detailed characteristics associated with all major algorithms.