Classification of BPSK and QPSK signals with unknown signal level using the Bayes technique

Automatic modulation classification through digital signal processing has found many applications in wireless communication systems, including interference identification, spectrum management and electronic warfare. In practice, wireless communication environments suffer from ill-characterized interference, fading and multipath. As a result, the level of the received signal is always time-varying and not known. This paper studies the use of the Bayes method to distinguish BPSK signal and QPSK signal without a priori knowledge of the received signal level. The maximum a posteriori classifier is derived with Rayleigh distributed signal amplitude. Simulations show that the classifier using the Bayes technique is superior to the classifier without considering the variation of signal level.