On the Design of 7/9-Rate Sparse Code for Spin-Torque Transfer Magnetic Random Access Memory

Abstract

A design of 7/9-rate sparse code for spin-torque transfer magnetic random access memory (STT-MRAM) is proposed in this work. The STT-MRAM using spin-polarized current through magnetic tunnel junction (MTJ) to write data is regarded as the most promising candidate for the next-generation nonvolatile memory technologies in both consumer and data center applications. The proposed code is designed based on exploiting the asymmetric write failure feature of the STT-MRAM. In particular, 7-bit user-data sequences incoming the encoder is encoded into 9-bit codewords, where the Hamming weights of the codewords are equal to 2 and 4 only. A single look-up table accomplishes encoding, whereas the maximum likelihood decoding is deployed in this work. Simulation results demonstrate that the designed code can provide significant improvements for the reliability of STT-MRAM under the effect of both write and read errors.

Exploring the application and performance of extended hamming code in IoT devices

“…Each data bit generates corresponding check bits, and an additional parity check bit, 'Pa', is also computed, representing the XOR operation of all data bits and check bits. Furthermore, an overall check code, 'Ga', is calculated as the XOR operation of 'Pa', all data bits, and the inverse of all check bits [9]. This encoding procedure ensures that, even in the event of transmission errors, the original data can be reconstructed using the error detection and correction mechanism.…”

Sparse Code With Minimum Hamming Distance of Three for Spin-Torque Transfer Magnetic Random Access Memory

“…Among these channels, the cascaded channel model in [27] can support error-rate simulations and be considered a communication channel model. Subsequently, based on the cascaded channel model, Nguyen discovered that the errors of STT-MRAM appear independently, with an asymmetric probability between 0 and 1 bit [28]. Therefore, in [28], the authors proposed a 7/9 sparse code to solve the asymmetric error probability problem in STT-MRAM.…”

“…Subsequently, based on the cascaded channel model, Nguyen discovered that the errors of STT-MRAM appear independently, with an asymmetric probability between 0 and 1 bit [28]. Therefore, in [28], the authors proposed a 7/9 sparse code to solve the asymmetric error probability problem in STT-MRAM. The sparse code had more 0s than 1s for each codeword.…”

“…The sparse code had more 0s than 1s for each codeword. To improve sparse code, Nguyen and Lee proposed a method to increase the minimum Hamming distance (MHD) to three for the sparse code [29]. However, to encode the sparse code in [29], the authors used mapping methods based on Euclidean distance decoding, which requires more time and has a large memory capacity.…”

“…To improve sparse code, Nguyen and Lee proposed a method to increase the minimum Hamming distance (MHD) to three for the sparse code [29]. However, to encode the sparse code in [29], the authors used mapping methods based on Euclidean distance decoding, which requires more time and has a large memory capacity. Therefore, we propose an encoder based on a generator matrix to directly create sparse code with an MHD of three.…”