Equalization techniques using neural networks for digital versatile disk–read-only memory systems

Abstract

Several equalizers are applied to digital versatile disk-read- only memory (DVD-ROM) systems. As a result of an imperfect writing process, nonlinear distortion may be generated in the replay signal. Neu- ral equalizers, which have strong nonlinear mapping capabilities, are applied to the system to compensate for the nonlinear distortion. We perform computer simulations for two systems: a DVD-ROM system with and without run-length-limited (RLL) modulation code. Nonlinear distor- tion such as domain bloom is the dominant interference of the channel in a DVD-ROM system with RLL code because this code reduces the linear intersymbol interference (ISI). Thus the experimental results with RLL code show that the signal-to-noise ratio (SNR) gain of equalizers using neural networks over conventional equalizers increases in proportion to the nonlinearity of the DVD-ROM channel. When RLL is not used, how- ever, linear and nonlinear ISI is the dominant interference of a DVD- ROM channel. Therefore equalizers with a decision-feedback section in a DVD-ROM system with RLL code outperform equalizers without a decision-feedback section in eliminating ISI. Consequently among the equalizers in our computer simulations, the neural decision-feedback equalizer (NDFE) showed the best bit error rate (BER) performance.