Performance analysis of a recursive fractional super-exponential algorithm

The super-exponential algorithm is a block-based technique for blind channel equalization and system identification. Due to its fast convergence rate, and no a priori parameterization other than the block length, it is a useful tool for linear equalization of moderately distortive channels. This paper presents a recursive implementation of the super-exponential algorithm for fractionally-sampled PAM signals. Although the resulting algorithm is still block-based, recursive propagation of several key variables allows the block length to be significantly reduced without compromising the algorithm's accuracy or speed, thereby enhancing its ability to track channel variations. The convergence rate is only mildly influenced by specific channel responses, and oversampling provides smaller output variance and almost perfect tolerance to sampling errors. Simulation results demonstrate the effectiveness of the proposed technique.