Maximum likelihood blind equalization via blind separation using fractional sampling

Contrast to the adaptive equalization method, which need a training period, blind equalization technique, which only the output signal is known, is needed in many communication systems, such as multipoint data network or wireless communication systems. In this paper, a new blind equalization approach, called expectation maximization blind equalization (EM-BE), is proposed. First, transform the convolution model into an instantaneous mixture model using fractional sampling. Then, use the EM algorithm to realize blind separation. Finally, reconstruction the source signal by appropriate quantization using the known finite alphabet values. Comparing with the Bussgang algorithm, e.g. constant modulus algorithm (CMA), the simulation results show the proposed algorithm in this paper has improved bit-error-rate (BER) performance with the additional computation complexity.