Low complexity turbo equalization for high density magnetic recording

In the context of iterative decoding and equalization (a.k.a. turbo equalization) of high density magnetic recording (MR) channels, we propose a low complexity soft-in soft-out (SISO) algorithm which implements the constrained delay a-posteriori probability (CD-APP) estimation utilizing either hard or soft decision feedback (HDF/SDF). Through BER simulation, we show that for an MR channel with user density 3.2, our proposed iterative scheme based on SDF enjoys a 6+ dB coding gain over the uncoded system and is superior to HDF by 2.2 dB at BER of 10^-5. It also performs comparably to the iterative system in which the BCJR algorithm matched to a generalized E2PR4 (GE2PR4) target is used for channel detection. Through captured burst error statistics, we show that SDF can significantly mitigate the detrimental effect of error propagation typically observed in systems based on RDF. The short burst error feature of SDF is most attractive in light of an outer error correcting code (ECC), such as the Reed-Solomon code.