Short Block-length Codes for Ultra-Reliable Low-Latency Communications

Shirvanimoghaddam, Mahyar; Sadegh, Mohamadi, Mohamad; Abbas, Rana Zamin; Minja, Aleksandar; Yue, Chentao; Matuz, Balázs; Han, Guangjie; Lin, Zihuai; Li, Yonghui; Johnson, Sarah J.; Vucetic, Branka

doi:10.48550/arxiv.1802.09166

Cited by 3 publications

(3 citation statements)

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“…Therefore, short channel coding that has powerful error correcting capability may be required for such applications. As already shown in the literature [15,16], polar codes concatenated with cyclic redundancy check (CRC) have an advantage over low-density parity-check (LDPC) codes in short block-length regime, which indicates that polar codes may be a potential candidate for error-correcting codes in molecular communication systems.…”

Section: Introductionmentioning

confidence: 86%

Polar Coding with Chemical Reaction Networks

Matsumine,

Koike-Akino,

Wang

2019

Preprint

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In this paper, we propose a new polar coding scheme with molecular programming, which is capable of highly parallel implementation at a nano-scale without a need of electrical power sources. We designed chemical reaction networks (CRN) to employ either successive cancellation (SC) or maximumlikelihood (ML) decoding schemes for short polar codes. From ordinary differential equation (ODE) analysis of the proposed CRNs, we demonstrate that SC and ML decoding achieve accurate computations across fully-parallel chemical reactions. We also make a comparison in terms of the number of required chemical reactions and species, where the superiority of ML decoder over SC decoder is observed for very short block lengths.

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Section: Introductionmentioning

confidence: 86%

Polar Coding with Chemical Reaction Networks

Matsumine,

Koike-Akino,

Wang

2019

Preprint

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“…In addition to large bandwidth and high-speed enhanced Mobile BroadBand (eMBB) scenarios, 5G has put forward the demand for ultra-reliable and low latency communications (uRLLC). For uRLLC, reducing the latency mandates the use of short block-length codes and conventionally designed moderate/long codes are not suitable [4]. Short code design and the related decoding algorithms have rekindled a great deal of interest among industry and academia recently [5], [6].…”

Section: Introductionmentioning

confidence: 99%

Segmentation-Discarding Ordered-Statistic Decoding for Linear Block Codes

Yue

Shirvanimoghaddam

et al. 2019

2019 IEEE Global Communications Conference (GLOBECOM)

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In this paper, we propose an efficient reliability based segmentation-discarding decoding (SDD) algorithm for short block-length codes. A novel segmentation-discarding technique is proposed along with the stopping rule to significantly reduce the decoding complexity without a significant performance degradation compared to ordered statistics decoding (OSD). In the proposed decoder, the list of test error patterns (TEPs) is divided into several segments according to carefully selected boundaries and every segment is checked separately during the reprocessing stage. Decoding is performed under the constraint of the discarding rule and stopping rule. Simulations results for different codes show that our proposed algorithm can significantly reduce the decoding complexity compared to the existing OSD algorithms in literature.

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“…While convolutional codes are state-of-the-art in the low latency regime, in the moderate latency regime, Extended Bose-Chaudhuri-Hocquenghem Code (eBCH) is shown to perform well [10].…”

mentioning

confidence: 99%

LEARN Codes: Inventing Low-Latency Codes via Recurrent Neural Networks

Jiang

Kim

Asnani

et al. 2020

IEEE J. Sel. Areas Inf. Theory

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Designing channel codes under low latency constraints is one of the most demanding requirements in 5G standards. However, sharp characterizations of the performances of traditional codes are only available in the large block-length limit. Code designs are guided by those asymptotic analysis and require large block lengths and long latency to achieve the desired error rate. Furthermore, when the codes designed for one channel (e.g. Additive White Gaussian Noise (AWGN) channel) are used for another (e.g. non-AWGN channels), heuristics are necessary to achieve any non trivial performancethereby severely lacking in robustness as well as adaptivity. Obtained by jointly designing Recurrent Neural Network (RNN) based encoder and decoder, we propose an end-to-end learned neural code which outperforms canonical convolutional code under block settings. With this gained experience of designing a novel neural block code, we propose a new class of codes under low latency constraint -Low-latency Efficient Adaptive Robust Neural (LEARN) codes, 2 which outperforms the state-of-the-art low latency codes as well as exhibits robustness and adaptivity properties. LEARN codes show the potential of designing new versatile and universal codes for future communications via tools of modern deep learning coupled with communication engineering insights.

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Short Block-length Codes for Ultra-Reliable Low-Latency Communications

Cited by 3 publications

References 0 publications

Polar Coding with Chemical Reaction Networks

Polar Coding with Chemical Reaction Networks

Segmentation-Discarding Ordered-Statistic Decoding for Linear Block Codes

LEARN Codes: Inventing Low-Latency Codes via Recurrent Neural Networks

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