journal article·2025-12-23Open access

MAP Detection for Double-Layer Bit-Patterned Media Recording

Thien An Nguyen, Jaejin Lee

Applied Sciences· Volume 16· Issue 1

Abstract

The rapid increase in global data generation has intensified the demand for magnetic storage systems with substantially higher areal density. Double-layer bit-patterned media recording (DLBPMR), which integrates the benefits of bit-patterned media recording (BPMR) and double-layer magnetic recording (DLMR), provides a promising pathway by combining nanoscale patterned islands with multilayer recording structures. However, severe two-dimensional intersymbol interference (ISI) within each layer, together with interlayer interference (ILI) between stacked layers, continues to present significant challenges for reliable data detection. To address these issues, this work investigates and advances the structure of DLMR to improve signal separation and recovery. In particular, we emphasize that detection plays a crucial role in mitigating both ISI and ILI. Accordingly, we propose a maximum a posteriori (MAP) detection scheme derived for a newly developed generalized two-layer partial-response (PR) model that accurately characterizes intra-layer ISI and cross-layer interference coupling. A parallel detection architecture is designed and employed for the upper and lower layers of the DLMR system, enabling the exchange of extrinsic information and enhancing MAP detection performance. Simulation results demonstrate that the proposed PR modeling and MAP-based detection framework achieves significant bit error rate (BER) improvements over existing detection methods, highlighting its strong potential for next-generation ultra-high-density DLBPMR systems.
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Research context

OpenAlex topics: Magnetic properties of thin films · Ferroelectric and Negative Capacitance Devices · Advanced Data Storage Technologies

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Department of Information Communication Convergence Technology, Soongsil University, Seoul 06978, Republic of Korea

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