Performance of the hybrid MLPNN based VE (h MLPNN-VE) for the nonlinear PMR channels

Wongsathan, Rati; Phakphisut, Watid; Supnithi, Pornchai

doi:10.1063/1.5006128

Performance of the hybrid MLPNN based VE (h MLPNN-VE) for the nonlinear PMR channels

Author(s)

Wongsathan, Rati

Phakphisut, Watid

Supnithi, Pornchai

Date Issued

May 1, 2018

Type

Article

DOI

10.1063/1.5006128

Abstract

This paper proposes a hybrid of multilayer perceptron neural network (MLPNN) and Volterra equalizer (VE) denoted hMLPNN-VE in nonlinear perpendicular magnetic recording (PMR) channels. The proposed detector integrates the nonlinear product terms of the delayed readback signals generated from the VE into the nonlinear processing of the MLPNN. The detection performance comparison is evaluated in terms of the tradeoff between the bit error rate (BER), complexity and reliability for a nonlinear Volterra channel at high normalized recording density. The proposed hMLPNN-VE outperforms MLPNN based equalizer (MLPNNE), VE and the conventional partial response maximum likelihood (PRML) detector.

Citation

Aip Advances, 8(5), 2018