High-speed voiceband QAM constellation classification in multipath environment

Abstract

We describe two real-time classifiers of unknown finite point QAM constellations over an nonideal channel. In the proposed schemes, first the transmitted symbols are recovered over a band-limited channel using the inherent cyclostationary characteristics of QAM signals. After equalization, the constellation is determined in the face of an unknown rotation due to an equalizer using a clustering approach, or Zernike moments. These methods are found to be effective in nonminimum. phase channels since they use the cyclostationary characteristics of the input signals to mitigate the destructive nature of the channel. The performance of the new classifiers are shown for high bit rate high density QAM constellations in presence of AWGN.