Fuzzy logic-based adaptive equaliser for non-linear perpendicular magnetic recording channels

This paper proposes the fuzzy logic equaliser (FLE) for the detection of non-linear perpendicular magnetic recording (PMR) channels. The multi-objective genetic algorithm (MOGA) is utilised to optimise all of the fuzzy parameters and reduce the complexity while maintaining the accuracy. By means of this optimisation, the total number of fuzzy rules is significantly reduced about 44%. The bit error rate (BER) performance of the proposed FLEs are compared with those of the conventional detector and traditional non-linear equalisers for Volterra channel, in presence of non-linear amplitude distortions in high-density PMR channels. The proposed FLE outperforms existing detectors by 1 to 12 dB SNR gains. Furthermore, the complexity in terms of multiplication counts per execution and reliability of detectors with regard to the number of system parameters through the Akaike's information criterion (AIC) are assessed to verify the effectiveness of the proposed FLEs. An extension to PMR channel with jitter noise proves the robustness of the proposed FLEs.