Low-complexity channel-estimate based adaptive linear equalizer

In this letter, we propose a low-complexity channel-estimate based adaptive linear equalizer. The equalizer exploits coordinate descent iterations for computation of equalizer coefficients. The proposed technique has as low complexity as O(N_u(K+M)) operations per sample, where K and M are the equalizer and channel estimator length, respectively, and N_u is the number of iterations such that N_u ≪ K and N_u ≪ M. Moreover, with dichotomous coordinate descent iterations, the computation of equalizer coefficients is multiplication-free and division-free, which makes the equalizer attractive for hardware design. Simulation shows that the proposed adaptive equalizer performs close to the minimum mean-square-error equalizer with perfect knowledge of the channel.