Improving BER Performance by Using V-Shaped Read Head Array in Heat-Assisted Magnetic Recording

Abstract

Heat-assisted magnetic recording (HAMR) is the leading candidate for the next generation of magnetic recording. In HAMR, the thermal profile (with circular contours produced by the near-field transducer) combined with the current writer structures results in recording transitions with noticeable curvature, which causes edge erasure at high linear density and increased transition noise. This transition curvature affects the bit error rate (BER) and is thus important to the model. As the micromagnetic simulations are computationally demanding, in this paper we investigate a fast and simplified write model to capture the transition curvature of HAMR. As the transition curvature causes signal degradation in normally oriented read head array (NHA) having straight gaps, we propose a V-shaped read head array (VHA) by rotating the side readers at appropriate angles to follow the curvature shapes and improve the readback signal. Simulations indicate that, with 2-D signal processing, VHA can provide improved BER performance compared to the NHA in the presence of readback transition curvature on HAMR media. Also this paper indicates that the Curie temperature variance affects BER performance more severely than the anisotropy field variance.