Low-complexity adaptive decision-feedback equalization of MIMO channels

A new adaptive MIMO channel equalizer is proposed based on adaptive generalized decision-feedback equalization and ordered-successive interference cancellation. The proposed equalizer comprises equal-length subequalizers, enabling any adaptive filtering algorithm to be employed for coefficient updates. A recently proposed computationally efficient recursive least squares algorithm based on dichotomous coordinate descents is utilized to solve the normal equations associated with the adaptation of the new equalizer. Convergence of the proposed algorithm is examined analytically and simulations show that the proposed equalizer is superior to the previously proposed adaptive MIMO channel equalizers by providing both enhanced bit error rate performance and reduced computational complexity. Furthermore, the proposed algorithm exhibits stable numerical behavior and can deliver a trade-off between performance and complexity.

► A new adaptive MIMO channel equalizer based on generalized DFE and OSIC is proposed.
► The proposed equalizer can employ any adaptive filtering algorithm for coefficient updates.
► The RLS–DCD algorithm is used to solve the normal equations in the adaptation of the new equalizer.
► Performance of the proposed equalizer is examined both analytically and by simulations.
► The proposed equalizer provides enhanced BER performance and reduced computational complexity.