A MAP Decoder for TVB Codes on a Generalized Iyengar–Siegel–Wolf BPMR Markov Channel Model

We present a generalization of the Iyengar-Siegel-Wolf Markov channel model for bit-patterned media recording media to allow negative drift, and adapt the maximum a posteriori decoder for time-varying block codes to work on this generalized model while minimizing complexity. We also describe a method for designing near-optimal codes for this channel using simulated annealing, obtaining better performance than alternative designs. In concatenation with a (999, 888)16 low-density parity-check (LDPC) code, we achieve a frame error rate (FER) of 10
^-3
at a channel error rate that is 1.73× higher than the best result with existing designs. A simple extension to include substitution errors allows the channel to approximate the dependent insertion, deletion, and substitution (DIDS) channel, with a decoding complexity that is 10× lower than that of Wu and Armand's RC2 decoder. The performance in the absence of burst errors is almost identical. When the DIDS channel includes burst substitution errors, our decoder performs worse than the RC2 decoder, but maintains its complexity advantage. For the same concatenated code, our decoder achieves an FER of 10
^-3
at a channel error rate that is 1.68× lower than the RC2 decoder. Finally, simulation results show that our code designs improve on existing constructions for the DIDS channel.