A robust and effective fuzzy adaptive equalizer for powerline communication channels

Fuzzy adaptive equalizers (FAEs) are adaptive equalizers that apply the concepts of fuzzy logic. The main merit of applying FAEs in powerline channel equalization is that linguistic information (fuzzy IF–THEN rules) and numerical information (input–output pairs) can be combined into the equalizers. The adaptive algorithms adjust the parameters of the membership functions which characterize the fuzzy concepts in the IF–THEN rules, by minimizing some criterion function. In this paper, we propose a new FAE, using the extended Kalman filter (EKF) algorithm for powerline channel equalization. The simulation results show that the EKF-based FAE has lower steady state bit error rate (BER) and faster convergent speed compared to decision feedback recursive least-squares adaptive equalizer, recursive least squares (RLS) based FAE and least mean squares (LMS) based FAE. We also propose a robust improvement scheme for the new FAE. Simulation results show that the performance of the proposed robust FAE is improved in powerline channel equalization and outperforms all the equalizers considered above. The BER of the proposed scheme is very close to the optimum performance.