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Channel Capacity and Soft-Decision Decoding of LDPC Codes for Spin-Torque Transfer Magnetic Random Access Memory (STT-MRAM)

机译:自旋扭矩传递磁随机存取存储器(STT-MRAM)的LDPC码的信道容量和软判决解码

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Spin-torque transfer magnetic random access memory (STT-MRAM) has emerged as a promising nonvolatile memory (NVM) technology, featuring compelling advantages in scalability, speed, endurance, and power consumption. In this paper, we focus on large-capacity standalone 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.
机译:自旋扭矩转移磁性随机存取存储器(STT-MRAM)已经成为一种很有前途的非易失性存储器(NVM)技术,在可伸缩性,速度,耐用性和功耗方面具有明显优势。在本文中,我们将重点放在大容量的独立STT-MRAM上,并研究信道容量以及应用低密度奇偶校验(LDPC)码和软判决解码来纠正存储单元错误并改善存储性能的可行性。 STT-MRAM的密度。我们建议使用具有短码字长度的LDPC码,以及基于可靠性的最小和(RB-MS)算法进行解码。此外,我们建议使用容量最大化准则来设计量化器,并最小化量化位数。仿真结果证明了将短块长LDPC码与软判决解码一起应用的潜力,以提高产量并突破STT-MRAM的缩放限制。

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