A Lattice Shalvi-Weinstein Algorithm for Blind Equalization

In blind equalization, the constant modulus algorithm (CMA) and Shalvi-Weinstein algorithm (SWA) present an unfavorable tradeoff between convergence rate and computational cost. Inspired in supervised order-recursive algorithms, we propose a lattice SWA, which has the number of operations per iteration of the equalizer order and maintains the SWA convergence rate. It presents a more robust behavior than that of SWA, avoiding numerical divergence when implemented in finite precision.