Skew-Dependent Performance Evaluation of Array-Reader-Based Magnetic Recording With Dual-Reader

Abstract

Array-reader-based magnetic recording (ARMR) shows potential to achieve areal density capability (ADC) beyond 1 Tb/in <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> by jointly processing multiple readback streams. Dual-reader ARMR with two read sensors and associated read channel signal processing algorithms are currently being actively investigated. In this paper, dual-reader ARMR performance is evaluated focusing on skew-induced variation in cross-track separation (CTS) between the two read sensors. Spin-stand captured waveforms based evaluation is presented for the cases where a dual-reader with certain CTS and skew is emulated using captures from a single-reader at different cross-track locations as well as for the case of actual dual-reader-based captures, where the latter also accounts for head rotation. Based on bit error rate scan along cross-track under various squeezed recording and skew conditions, squeeze-to-death margin-based ADC gain of ARMR is predicted. Dual-reader ARMR shows 5%-10% ADC gain over single-reader for CTS less than 0.6 track pitch, while showing limited gains for larger CTS. Also presented is the performance evaluation of dual-reader ARMR on spin-stand using a hardware accelerated ARMR performance evaluation platform, called Stingray, which uses four Avago read channel silicon chips and a customized field programmable gate array to enable high-speed joint equalization and detection using dual-reader readback streams.