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

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. Neural 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 distortion 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, however, 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.