A comparison of detection methods in the presence of nonlinearities

In this paper we evaluate the detectability of nonlinear signals characteristic of high-density, magnetic recording channels read by a magneto-resistive (MR) head. We first introduce a signal model which performs nonlinear superposition of experimentally-collected MR-head transition responses. Feeding signals synthesized from this model through a detection simulator, we compare the performance of Decision Feedback Equalization (DFE), RAM DFE, Partial Response Maximum-likelihood detection with PR4, EPR4, and E/sup 2/PR4 targets, and Fixed Delay Tree Search with Decision Feedback (FDTS/DF) in the presence of time and amplitude nonlinearities. Signals are generated at a variety of signal-to-noise ratios (SNRs) and densities with runlength constraints of (0,3) and (1,7). We found that the most detrimental nonlinearities come from amplitude asymmetry characteristic of poorly biased MR heads, and such nonlinearities cause a loss of between 0.5 and 1 orders of magnitude in bit error rate. We found that of the schemes, FDTS/DF provided the great robustness against all nonlinearities in the presence of RLL(1,7) coding, and EPR4ML and E/sup 2/PR4ML preformed the best with RLL(0,3) coding.