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Ratio-based multi-level resistive memory cells
Ratio-based encoding has recently been proposed for single-level resistive memory cells, in which the resistance ratio of a pair of resistance-switching devices, rather than the resistance of a single device (i.e. resistance-based encoding), is used for encoding single-bit information, which signifi...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7809403/ https://www.ncbi.nlm.nih.gov/pubmed/33446703 http://dx.doi.org/10.1038/s41598-020-80121-7 |
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author | Lastras-Montaño, Miguel Angel Del Pozo-Zamudio, Osvaldo Glebsky, Lev Zhao, Meiran Wu, Huaqiang Cheng, Kwang-Ting |
author_facet | Lastras-Montaño, Miguel Angel Del Pozo-Zamudio, Osvaldo Glebsky, Lev Zhao, Meiran Wu, Huaqiang Cheng, Kwang-Ting |
author_sort | Lastras-Montaño, Miguel Angel |
collection | PubMed |
description | Ratio-based encoding has recently been proposed for single-level resistive memory cells, in which the resistance ratio of a pair of resistance-switching devices, rather than the resistance of a single device (i.e. resistance-based encoding), is used for encoding single-bit information, which significantly reduces the bit error probability. Generalizing this concept for multi-level cells, we propose a ratio-based information encoding mechanism and demonstrate its advantages over the resistance-based encoding for designing multi-level memory systems. We derive a closed-form expression for the bit error probability of ratio-based and resistance-based encodings as a function of the number of levels of the memory cell, the variance of the distribution of the resistive states, and the ON/OFF ratio of the resistive device, from which we prove that for a multi-level memory system using resistance-based encoding with bit error probability x, its corresponding bit error probability using ratio-based encoding will be reduced to [Formula: see text] at the best case and [Formula: see text] at the worst case. We experimentally validated these findings on multiple resistance-switching devices and show that, compared to the resistance-based encoding on the same resistive devices, our approach achieves up to 3 orders of magnitude lower bit error probability, or alternatively it could reduce the cell’s programming time and programming energy by up 5–10[Formula: see text] , while achieving the same bit error probability. |
format | Online Article Text |
id | pubmed-7809403 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-78094032021-01-21 Ratio-based multi-level resistive memory cells Lastras-Montaño, Miguel Angel Del Pozo-Zamudio, Osvaldo Glebsky, Lev Zhao, Meiran Wu, Huaqiang Cheng, Kwang-Ting Sci Rep Article Ratio-based encoding has recently been proposed for single-level resistive memory cells, in which the resistance ratio of a pair of resistance-switching devices, rather than the resistance of a single device (i.e. resistance-based encoding), is used for encoding single-bit information, which significantly reduces the bit error probability. Generalizing this concept for multi-level cells, we propose a ratio-based information encoding mechanism and demonstrate its advantages over the resistance-based encoding for designing multi-level memory systems. We derive a closed-form expression for the bit error probability of ratio-based and resistance-based encodings as a function of the number of levels of the memory cell, the variance of the distribution of the resistive states, and the ON/OFF ratio of the resistive device, from which we prove that for a multi-level memory system using resistance-based encoding with bit error probability x, its corresponding bit error probability using ratio-based encoding will be reduced to [Formula: see text] at the best case and [Formula: see text] at the worst case. We experimentally validated these findings on multiple resistance-switching devices and show that, compared to the resistance-based encoding on the same resistive devices, our approach achieves up to 3 orders of magnitude lower bit error probability, or alternatively it could reduce the cell’s programming time and programming energy by up 5–10[Formula: see text] , while achieving the same bit error probability. Nature Publishing Group UK 2021-01-14 /pmc/articles/PMC7809403/ /pubmed/33446703 http://dx.doi.org/10.1038/s41598-020-80121-7 Text en © The Author(s) 2021 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Lastras-Montaño, Miguel Angel Del Pozo-Zamudio, Osvaldo Glebsky, Lev Zhao, Meiran Wu, Huaqiang Cheng, Kwang-Ting Ratio-based multi-level resistive memory cells |
title | Ratio-based multi-level resistive memory cells |
title_full | Ratio-based multi-level resistive memory cells |
title_fullStr | Ratio-based multi-level resistive memory cells |
title_full_unstemmed | Ratio-based multi-level resistive memory cells |
title_short | Ratio-based multi-level resistive memory cells |
title_sort | ratio-based multi-level resistive memory cells |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7809403/ https://www.ncbi.nlm.nih.gov/pubmed/33446703 http://dx.doi.org/10.1038/s41598-020-80121-7 |
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