GGMAC-based equalizer for nonlinear channels

This paper deals with the compensation for the nonlinear distortion introduced by power-efficient amplifiers on linear modulation by means of equalization. We propose a new equalizer based on a reduced-complexity network called the generalized cerebellar model arithmetic computer (GMAC) GCMAC. The GCMAC-based equalizer is compared with other well-known structures such as the Volterra filter and the multi-layer perceptron. Extensive computer simulations have been carried out. The obtained results show the effectiveness of the proposed structure to compensate for strong nonlinearities