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R&D: Track Mis-Registration Estimator Based on K-Means Algorithm for Bit-Patterned Media Recording

Proposing TMR estimator based on K-means algorithm for estimating TMR levels and prevent performance degradation of the BPMR system

IEEE Xplore has published, in 2022 IEEE 33rd Magnetic Recording Conference (TMRC) proceedings, an article written by Seongkwon Jeong, and Jaejin Lee, School of Electronic Engineering, Soongsil University, Seoul, Korea.

Abstract: Bit-patterned media recording (BPMR) has been considered as a one of the key technologies to extend recording densities to 1 Tb/in 2 and beyond. However, BPMR system encounters challenges of not only two-dimensional intersymbol interference but also track mis-registration (TMR). In this paper, we propose a TMR estimator based on K-means algorithm for estimating the TMR levels and prevent the performance degradation of the BPMR system. The TMR estimator calculates the distance between the centroid of readback signal and the predetermined centroids according to TMR level, and equalizer coefficients and partial response target are adjusted to the corresponding TMR level.

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