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Features for Read Reference Voltage Estimation in NAND Flash Memory

  • Reliability is a crucial aspect of non-volatile NAND flash memories, and it is essential to thoroughly analyze the channel to prevent errors and ensure accurate readout. Es-timating the read reference voltages (RRV s) is a significant challenge due to the multitude of physical effects involved. The question arises which features are useful and necessary for the RRV estimation. Various possible features require specialized hardware or specific readout techniques to be usable. In contrast we consider sparse histograms based on the decision thresholds for hard-input and soft-input decoding. These offer a distinct advantage as they are derived directly from the raw readout data without the need for decoding. This paper focuses on the information-theoretic study of different features, especially on the exploration of the mutual information (MI) between feature vector and RRV. In particular, we investigate the dependency of the MI on the resolution of the histograms. With respect to the RRV estimation, sparse histograms provide sufficient information for near-optimum estimation.

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Metadaten
Author:Daniel Nicolas BailonORCiD, Sergo ShavgulidzeORCiD, Jürgen FreudenbergerORCiDGND
DOI:https://doi.org/10.1109/ICCE-Berlin58801.2023.10375586
ISBN:979-8-3503-2415-0
ISBN:979-8-3503-2416-7
Parent Title (English):13th International Conference on Consumer Electronics (ICCE-Berlin), 3.-5. Sept. 2023, Berlin, Germany
Publisher:IEEE
Document Type:Conference Proceeding
Language:English
Year of Publication:2023
Release Date:2024/01/11
Page Number:6
Note:
Volltextzugriff für Angehörige der Hochschule Konstanz via Datenbank IEEE Xplore möglich
Institutes:Institut für Systemdynamik - ISD
Relevance:Peer reviewed nach anderen Listungen (mit Nachweis zum Peer Review Verfahren)
Open Access?:Nein
Licence (German):License LogoUrheberrechtlich geschützt