Power-line communications channel estimation and tracking by a competitive neural network

In this paper, a decision-directed method is proposed for channel estimation and equalization in power-line communication (PLC) based on orthogonal frequency-division multiplexing (OFDM). In the DDE (decision-directed estimation) method proposed, the received subcarrier-symbols are presented to a competitive neural network that adaptively finds the clusters of the QAM (quadrature amplitude modulation) constellation. This method does not require a priori know/edge on the powerline then allowing a blind estimation of the channel with tracking capabilities limited by constraints on the phase changes. Simulations on a realistic indoor power-line system show that the proposed method achieves very good channel estimation and equalization performances and that it is robust to impulsive noise and nonlinearities