Classification of digital modulations by MCMC sampling

This paper addresses the problem of classification of digital modulations. The proposed solution uses the Bayes classifier, which is implemented by the Markov chain Monte Carlo scheme. In the proposed implementation, classifications in presence of phase and frequency offsets as well as residual filtering effects coming from imperfect channel equalization are considered. The proposed approach has been tested for many scenarios and its performance has been compared with the maximum likelihood classifier and the 4th order cumulant-based method. The obtained results show that our classifier outperforms the other methods considerably.