Data-Dependent Noise-Predictive Symbol-Based Detector for Perpendicular Magnetic Recording Channels
A. Poloni, Stefano Vincenti, Stefano Valle · IEEE Transactions on Magnetics · 2011
This work introduces a new formulation of the well-known data-dependent noise-predictive (DDNP) approach to whiten noise in partial response channel detection. The new approach is tailored for whitening the branches in the recently introduced symbol-based detectors that are demonstrated to have optimal performance in concatenation with non-binary error correction codes, such as non-binary low density parity check (LDPC) codes. This paper describes a new approach in the context of the perpendicular magnetic channel, where a symbol-based BCJR is concatenated with a non-binary LDPC decoder. Several approximations based on conventional DDNP implementations are suggested to quantify the performance of the new algorithm.