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Improving MRAM Performance with Sparse Modulation and Hamming Error Correction.

Sensors (Basel, Switzerland)ยท2025
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Updated: Mar 15, 2026

Tuning a Parallel Segmented Flow Column and Enabling Multiplexed Detection
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Joint Optimization of Codeword Bit Distribution and Detection Threshold for Asymmetric STT-MRAM Channel.

Thien An Nguyen1, Jaejin Lee1

  • 1Department of Information Communication Convergence Technology, Soongsil University, Seoul 06978, Republic of Korea.

Sensors (Basel, Switzerland)
|March 14, 2026
PubMed
Summary
This summary is machine-generated.

Asymmetric errors in spin-transfer torque magnetic random-access memory (STT-MRAM) degrade reliability. New threshold-matched probability codes (TMPCs) balance error probabilities for improved STT-MRAM system performance.

Keywords:
asymmetric write error ratecascaded channelcodeword bit distributiondetection threshold optimizationerror correction codes (ECCs)non-volatile memory reliabilitysparse modulationspin-transfer torque magnetic random-access memory (STT-MRAM)

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Area of Science:

  • Electrical Engineering
  • Computer Science
  • Materials Science

Background:

  • Spin-transfer torque magnetic random-access memory (STT-MRAM) offers non-volatility and low power, making it suitable for sensor networks.
  • Asymmetric error characteristics in STT-MRAM, specifically unequal probabilities of logical '0' and '1' errors, compromise system reliability.
  • Current error correction methods often assume fixed bit distributions or pre-set imbalances, neglecting their interaction with detection thresholds.

Purpose of the Study:

  • To minimize the bit error rate (BER) in STT-MRAM by jointly optimizing codeword bit distribution and detection threshold.
  • To develop a coding scheme that accounts for the asymmetric error channel inherent in STT-MRAM.
  • To enhance the reliability of STT-MRAM in sensor network applications.

Main Methods:

  • Formulated the BER minimization as a joint optimization problem over an asymmetric cascaded STT-MRAM channel.
  • Derived analytical results showing minimum BER is achieved when error probabilities for '0' and '1' are balanced.
  • Proposed threshold-matched probability codes (TMPCs) with codeword compositions tailored to the optimal detection threshold.

Main Results:

  • Identified an intrinsic coupling between the optimal detection threshold and codeword composition for minimum BER.
  • Demonstrated that TMPCs achieve lower BERs than existing sparse and fixed-distribution codes.
  • Showcased TMPC performance across various STT-MRAM operating conditions, including severe write asymmetry and resistance variations.

Conclusions:

  • Joint optimization of bit distribution and detection threshold is crucial for mitigating STT-MRAM asymmetric errors.
  • Threshold-matched probability codes (TMPCs) provide a principled and flexible approach to enhance STT-MRAM reliability.
  • The proposed TMPC framework offers significant improvements for STT-MRAM-based sensor networks and non-volatile memory systems.