Low complexity generalized EM algorithm for blind channel estimation and data detection in optical communication systems

Expectation–Maximization algorithm (EM) has been used in the past for blind estimation of intersymbol interference channels characterized by additive white Gaussian noise. When the channel is characterized by non-Gaussian, signal-dependent noise, the computational complexity of direct application of EM becomes prohibitively high. In this paper, a low complexity generalized EM algorithm is presented. The proposed algorithm achieves a major reduction in computational complexity compared to the EM algorithm and can be applied to nonlinear finite memory channels with non-Gaussian signal-dependent noise. Simulation results are presented for intensity modulated direct detection optical channel that is characterized by non-central chi-square distribution noise.