Information Theoretic Bounds Based Channel Quantization Design for Emerging Memories
@article{Mei2018InformationTB, title={Information Theoretic Bounds Based Channel Quantization Design for Emerging Memories}, author={Zhen Mei and Kui Cai and Long Shi}, journal={2018 IEEE Information Theory Workshop (ITW)}, year={2018}, pages={1-5} }
Channel output quantization plays a vital role in high-speed emerging memories such as the spin-torque transfer magnetic random access memory (STT-MRAM), where high-precision analog-to-digital converters (ADCs) are not applicable. In this paper, we investigate the design of the 1-bit quantizer which is highly suitable for practical applications. We first propose a quantized channel model for STT-MRAM. We then analyze various information theoretic bounds for the quantized channel, including the…
6 Citations
Union Bound Analysis for Spin-Torque Transfer Magnetic Random Access Memory (STT-MRAM) With Channel Quantization
- Computer ScienceIEEE Transactions on Magnetics
- 2022
A union bound analysis which can accurately predict the word error rates (WERs) of ECCs with maximum-likelihood (ML) decoding over the quantized STT-MRAM channel is proposed and results show that the proposed union-bound-optimized (UBO) quantizer can achieve better error rate performance than the state-of-art quantizers for STTs.
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- 2019
A sufficient condition on the channel transition probability is given, under which the two low-complexity techniques can be applied for designing quantizers that maximize the α-mutual information, which is a generalized objective function for channel quantization.
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The proposed MIM-QBP decoder with only 3 bits per message can outperform the floating-point belief propagation (BP) decoder at high signal-to-noise ratio (SNR) regions with a maximum of 10 iterations.
Dynamic Programming for Discrete Memoryless Channel Quantization
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- 2019
Theoretical analysis and simulation results demonstrate that IDP can improve the quantizer design over the state-of-the-art methods in the literature, and propose a new idea, called iterative DP (IDP).
Dynamic Programming for Sequential Deterministic Quantization of Discrete Memoryless Channels
- Computer ScienceIEEE Transactions on Communications
- 2021
The DP method to obtain an optimal sequential deterministic quantizer (SDQ) for binary-input discrete memoryless channel (DMC) is presented and a sufficient condition under which the optimal SDQ is optimal among all quantizers is derived and the two techniques are applicable.
Deep Learning-Aided Dynamic Read Thresholds Design for Multi-Level-Cell Flash Memories
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- 2020
A novel recurrent neural network (RNN)-based detector to effectively detect the data stored in the multi-level-cell (MLC) flash memory without the prior knowledge of the channel, and an RNN-aided (RNNA) dynamic threshold detector, whose detection thresholds can be derived based on the outputs of the RNN detector.
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