Keep the bursts and ditch the interleavers

An, Wei; Médard, Muriel; Duffy, Ken R.

doi:10.1109/globecom42002.2020.9322303

Cited by 39 publications

(32 citation statements)

References 21 publications

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“…When permutation exhausts, an extra nonflipped bit is included and the permutation process restarts. This pattern generator gives the decoder some advantages with burst errors (specifically treated in [28]) and the resulted algorithm is named as GRAND with simple order sweeping (GRAND-SOS).…”

Section: Guessing Random Additive Noise Decoding a Grand-sos For Hard...mentioning

confidence: 99%

“…GRAND's universality stems from its effort to identify the effect of the noise, from which the code-word is deduced. Originally introduced as a hard detection decoder [26]- [28], a series of soft detection variants, SRGRAND [29], [30], ORBGRAND [31] and SGRAND [32], have since been proposed that make distinct quantization assumptions. Both hard and soft detection versions of GRAND are ML decoders.…”

Section: Introductionmentioning

confidence: 99%

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CRC Codes as Error Correction Codes

Médard

Duffy

2021

ICC 2021 - IEEE International Conference on Communications

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CRC codes have long since been adopted in a vast range of applications. The established notion that they are suitable primarily for error detection can be set aside through use of the recently proposed Guessing Random Additive Noise Decoding (GRAND). Hard-detection (GRAND-SOS) and softdetection (ORBGRAND) variants can decode any short, high-rate block code, making them suitable for error correction of CRCcoded data. When decoded with GRAND, short CRC codes have error correction capability that is at least as good as popular codes such as BCH codes, but with no restriction on either code length or rate.The state-of-the-art CA-Polar codes are concatenated CRC and Polar codes. For error correction, we find that the CRC is a better short code than either Polar or CA-Polar codes. Moreover, the standard CA-SCL decoder only uses the CRC for error detection and therefore suffers severe performance degradation in short, high rate settings when compared with the performance GRAND provides, which uses all of the CA-Polar bits for error correction.Using GRAND, existing systems can be upgraded from error detection to low-latency error correction without re-engineering the encoder, and additional applications of CRCs can be found in IoT, Ultra-Reliable Low Latency Communication (URLLC), and beyond. The universality of GRAND, its ready parallelized implementation in hardware, and the good performance of CRC as codes make their combination a viable solution for low-latency applications.

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Section: Guessing Random Additive Noise Decoding a Grand-sos For Hard...mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

CRC Codes as Error Correction Codes

Médard

Duffy

2021

ICC 2021 - IEEE International Conference on Communications

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“…Coded packets are transmitted after the entire interleaving block, which is multiple times greater than the generation size. The authors of [30] showed that replacing interleaving techniques with RLC at the link layer can reduce latency, despite losing the ability to recover burst losses.…”

Section: Coding Variants and Characteristicsmentioning

confidence: 99%

Robust QUIC: Integrating Practical Coding in a Low Latency Transport Protocol

et al. 2021

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We introduce rQUIC, an integration of the QUIC protocol, and a coding module. rQUIC has been designed to feature different coding/decoding schemes and is implemented in go language. We conducted an extensive measurement campaign to provide a thorough characterization of the proposed solution. We compared the performance of rQUIC with that of the original QUIC protocol for different underlying network conditions as well as different traffic patterns. Our results show that rQUIC not only yields a relevant performance gain (shorter delays), especially when network conditions worsen, but also ensures a more predictable behavior. For bulk transfer (long flows), the delay reduction almost reached 70% when the frame error rate was 5%, while under similar conditions, the gain for short flows (web navigation) was ≈ 55%. In the case of the video streaming the QoE gain (p1203 metric) was, approximately, 50%.

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“…The theoretical foundations and properties of GRAND were laid in [3] and [4]. A practical implementation of the GRAND framework, referred to as GRAND Markov order (GRAND-MO), was presented in [5]. GRAND-MO is a hard detection decoder of binary codewords that have been impaired by errors correlated over time.…”

Section: Introductionmentioning

confidence: 99%

Transversal GRAND for Network Coded Data

Chatzigeorgiou¹

2021

Preprint

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This paper considers a transmitter, which uses random linear coding (RLC) to encode data packets. The generated coded packets are broadcast to one or more receivers. A receiver can recover the data packets if it gathers a sufficient number of coded packets. We assume that the receiver does not abandon its efforts to recover the data packets if RLC decoding has been unsuccessful; instead, it employs syndrome decoding in an effort to repair erroneously received coded packets before it attempts RLC decoding again. A key assumption of most decoding techniques, including syndrome decoding, is that errors are independently and identically distributed within the received coded packets. Motivated by the 'guessing random additive noise decoding' (GRAND) framework, we develop transversal GRAND: an algorithm that exploits statistical dependence in the occurrence of errors, complements RLC decoding and achieves a gain over syndrome decoding, in terms of the probability that the receiver will recover the original data packets.

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Keep the bursts and ditch the interleavers

Cited by 39 publications

References 21 publications

CRC Codes as Error Correction Codes

CRC Codes as Error Correction Codes

Robust QUIC: Integrating Practical Coding in a Low Latency Transport Protocol

Transversal GRAND for Network Coded Data

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