@inproceedings{866c356a673b4645b94d6328a1d29551,
title = "A CLUSTERING-BASED ML SCHEME FOR CAPACITY APPROACHING SOFT LEVEL SENSING IN 3D TLC NAND",
abstract = "In a 3D TLC solid-state storage system, the LDPC decoding performance is significantly affected by the quality of soft-level sensing. Inspired by the capacity-approaching maximum mutual-information method, this work presents the data-driven approach to collect all the optimal 2-bit soft-read level pairs over the 3D TLC NAND. Due to the data transmission latency and limited configuration resources, a clustering method is proposed to extract the soft-read level pairs in the experiment data. Under the 3K Program Erase Cycles 228-hour data retention at 85°C channel condition, the proposed soft-read level pairs could provide an additional 73-error-bit tolerance in the 2K LDPC decoder.",
keywords = "3D NAND, Clustering, Machine Learning, Maximum Mutual Information",
author = "Liu, {Li Wei} and Liao, {Yen Ching} and Chang, {Hsie Chia}",
note = "Publisher Copyright: {\textcopyright} 2022 IEEE; 47th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2022 ; Conference date: 23-05-2022 Through 27-05-2022",
year = "2022",
doi = "10.1109/ICASSP43922.2022.9746590",
language = "English",
series = "ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "4078--4082",
booktitle = "2022 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2022 - Proceedings",
address = "United States",
}