High Density Turbo TDMR Detection with Local Area Influence Probabilistic Model

This paper proposes probabilistic message-passing turbo detection algorithms for 2-D magnetic recording that locally estimate magnetic grain interactions with coded data bits, and thus iteratively assist channel decoding. Such local area influence probabilistic (LAIP) techniques are especially effective at densities ranging from about 4 magnetic grains per coded bit (GPB) down to about 1 GPB, wher...