A parallel multimodel: CMA/Godard adaptive filter bank approach to fractionally-spaced blind adaptive equalization

We consider the problem of blind equalization of digital communication channels using fractionally spaced samples. Fractionally sampled data are cyclo-stationary rather than stationary. The problem is cast into a mathematical framework of a vector stationary process with single input (information sequence) and multiple outputs, by using a time-series representation of a cyclostationary process. This leads to number of subchannels equal to number of samples per symbol. Each subchannel is first equalized independently using a baud-rate CMA/Godard (1980) blind equalizer. Several approaches are presented for selection and fusion of the equalized outputs of the various subchannels in order to achieve a performance that is much less sensitive to the symbol-timing-phase errors when compared with a band-rate equalizer. An illustrative simulation example 16-QAM (V22 source) signal is presented where effect of symbol-timing-phase offset is studied via computer simulations