Fuzzy Adaptive Blind Equalizer Using Extended Kalman Filter Based Adaptation Algorithm For Powerline Channel

Fuzzy adaptive equalizer (FAE) is a knowledge based equalizer operating on linguistic variables. The advantages of using fuzzy logic adaptation scheme with respect to more traditional adaptation schemes in powerline communication system are the simplicity of the approach and the use of knowledge (fuzzy if-then rules and input output pairs information) about the communication medium. This paper presents a new adaptive blind equalization method based on fuzzy logic for powerline channel. We introduce a new type of fuzzy adaptive blind equalizer (FABE) using extended Kalman filter (EKF) based adaptation algorithm for powerline channel equalization. The proposed blind equalizer for powerline channel has the following merits: It is new and simple in design, and it does not requires training sequence. In a changeable distorted powerline channel, data transmission is continuous and do not stop for training the equalizer. The performance of EKF-based FABE is compared with two other types of FABEs based on the recursive least squares (RLS) and the least mean squares (LMS) adaptation algorithm. The simulation results show that EKF-based FABE has faster convergent and lower steady state probability of error compared to the other two FABEs. The bit error rate (BER) of the EKF-based FABE is close to that of the optimal equalizer