Error Event Corrections Using List-NPML Decoding and Error Detection Codes

Abstract

A List-Noise Predictive Maximum Likelihood (List-NPML) decoding algorithm based on a periodic error detection mechanism is proposed for magnetic recording systems to minimize the number of error events. The proposed detector keeps a list of candidate paths ( candidates per state of a trellis) based on the observation that most of the error events can be recovered by finding a set of most likely paths. A periodic decision making process is utilized for every bits based on error detection codes. With this approach, a tradeoff between performance and complexity is studied with various combinations of and . The proposed structure is robust to miscorrections and time-varying error events, eliminating the need for knowing the error event distributions prior to its operation. We also introduced a novel design of parity bits that meets the run length constraints of the channel and a trellis update architecture for improved performance. Simulation results show that the proposed List-NPMLD gives us significant BER performance and post-ECC gains at the expense of some increase in complexity.