Channel capacity and soft-decision decoding of LDPC codes for spin-torque transfer magnetic random access memory (STT-MRAM)

K. Cai, Zhiliang Qin, Bingjin Chen
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引用次数: 18

Abstract

Spin-torque transfer magnetic random access memory (STT-MRAM) has emerged as a promising non-volatile memory (NVM) technology, featuring compelling advantages in scalability, speed, endurance, and power consumption. In this paper, we focus on large-capacity stand-alone STT-MRAM, and investigate the channel capacity and the viability of applying low-density parity-check (LDPC) codes with soft-decision decoding to correct the memory cell errors and improve the storage density of STT-MRAM. We propose to use LDPC codes with short codeword lengths, with the reliability-based min-sum (RB-MS) algorithm for decoding. Furthermore, we propose to use the capacity-maximization criterion to design the quantizer and minimize the number of quantization bits. Simulation results demonstrate the potential of applying short-block-length LDPC codes with soft-decision decoding to improve the yield and push the scaling limitation of STT-MRAM.
自旋转矩转移磁随机存储器(STT-MRAM) LDPC码的信道容量及软判决译码
自旋转矩传输磁随机存取存储器(STT-MRAM)已成为一种有前途的非易失性存储器(NVM)技术,在可扩展性、速度、耐用性和功耗方面具有引人注目的优势。本文以大容量单机STT-MRAM为研究对象,研究了采用低密度奇偶校验码(LDPC)进行软判决译码来纠正存储单元错误和提高STT-MRAM存储密度的信道容量和可行性。我们建议使用短码字长度的LDPC码,并使用基于可靠性的最小和(RB-MS)算法进行解码。此外,我们提出使用容量最大化准则来设计量化器,并尽量减少量化比特数。仿真结果表明,采用短块长度LDPC码进行软判决译码可以提高成品率,突破STT-MRAM的尺度限制。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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