Balanced Gray Codes With Flexible Lengths

Wang, Lu; Wang, Zulin; Huang, Qin; Zhang, Mu

doi:10.1109/lcomm.2015.2501291

Cited by 4 publications

(1 citation statement)

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“…Moreover, as the data is usually operated in bytes, where each byte contains 8 bits, in order to make the package codes suitable for the data operations, we choose the modified Hamming product code, which is ( , ) = (48, 16). It is worth noting that some other short algebraic codes could be adopted to constitute the product code, such as Gray codes in [24], at the cost of complexity.…”

Section: Construction Of Adaptive Hamming Product Codementioning

confidence: 99%

Design and Analysis of Adaptive Message Coding on LDPC Decoder with Faulty Storage

Yin

2018

Wireless Communications and Mobile Computing

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Unreliable message storage severely degrades the performance of LDPC decoders. This paper discusses the impacts of message errors on LDPC decoders and schemes improving the robustness. Firstly, we develop a discrete density evolution analysis for faulty LDPC decoders, which indicates that protecting the sign bits of messages is effective enough for finite-precision LDPC decoders. Secondly, we analyze the effects of quantization precision loss for static sign bit protection and propose an embedded dynamic coding scheme by adaptively employing the least significant bits (LSBs) to protect the sign bits. Thirdly, we give a construction of Hamming product code for the adaptive coding and present low complexity decoding algorithms. Theoretic analysis indicates that the proposed scheme outperforms traditional triple modular redundancy (TMR) scheme in decoding both threshold and residual errors, while Monte Carlo simulations show that the performance loss is less than 0.2 dB when the storage error probability varies from 10 −3 to 10 −4 .

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Section: Construction Of Adaptive Hamming Product Codementioning

confidence: 99%