Sparse Vector Coding for Ultra Short Packet Transmission

Ji, Hyoungju; Kim, Sang-Tae; Shim, Byonghyo

doi:10.1109/ita.2018.8503179

Cited by 6 publications

(13 citation statements)

References 7 publications

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“…Based on Compressive Sensing [87], their studies started around 2017. The first results are promising for ultra-small values of K. In particular, for K below 100 bits, they show comparable performance with Polar codes [88]- [90]. However, the properties related to their generation matrix show worsened decoding performance at high Code Rates (R ≤ 1 4 ).…”

Section: A Block Codesmentioning

confidence: 96%

“…However, the properties related to their generation matrix show worsened decoding performance at high Code Rates (R ≤ 1 4 ). Furthermore, the required representation of data into sparse vector form limited the use of SVC exclusively to ultra-small K values [88]. Recently, the literature proposed some implementations related to these new techniques: [91] where also is estimated computational complexity, and [92] where are given reliability and decoding latency performance.…”

Section: A Block Codesmentioning

confidence: 99%

“…Examples are LDPC and Polar codes applied in 5G NR and TBCC and Turbo applied in LTE as observed in Section V-C. Moreover, the recent novelties SVC [88], [91], [92] and PAC Polar [139], which research is in a preliminary phase, could offer more alternatives for URLLC and FA future developments. Therefore, based on the results obtained in this study, we discuss some open issues that emerged for FEC techniques in FA environments as follows.…”

Section: Future Challengesmentioning

confidence: 99%

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A Survey on FEC Techniques for Industrial Wireless Communications

Fanari

Iradier

Bilbao

et al. 2022

IEEE Open J. Ind. Electron. Soc.

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Industry 4.0 aims to digitize industrial processes entirely, and wireless technologies represent one of the enablers for scalable and flexible communications. However, the current standards and proprietary solutions do not meet the industry's tight requirements in fundamental use cases such as Factory Automation (FA). One of the key research challenges towards replacing wired fieldbuses with wireless links is the design of techniques that enable real-time and deterministic behavior when transmitting short packets. Forward Error Correction (FEC) techniques are critical to this objective, and coding/decoding algorithms must comply with reliability and low latency specifications. This paper surveys existing FEC techniques for short packet transmissions. Compared to other survey papers in the field, we propose several FEC candidate techniques specifically suitable for FA wireless systems. We explore four of these techniques, also examining hardware architecture proposals. The paper proposes a methodology to evaluate their latency and reliability performance. We finally discuss the lessons learned and challenges for future research.

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Section: A Block Codesmentioning

confidence: 96%

Section: A Block Codesmentioning

confidence: 99%

Section: Future Challengesmentioning

confidence: 99%

See 1 more Smart Citation

A Survey on FEC Techniques for Industrial Wireless Communications

Fanari

Iradier

Bilbao

et al. 2022

IEEE Open J. Ind. Electron. Soc.

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“…We test the transmission of b bit information which consists of information bit b i and CRC bit b c . In the conventional PDCCH method, the convolution code with rate 1 3 with the 16-bit CRC is employed. Since the block size of the polar code is not flexible, we set the rate 1 4 to test similar conditions (b = 2 4 and m = 32).…”

Section: A Simulation Setupmentioning

confidence: 99%

“…In the conventional PDCCH method, the convolution code with rate 1 3 with the 16-bit CRC is employed. Since the block size of the polar code is not flexible, we set the rate 1 4 to test similar conditions (b = 2 4 and m = 32). In the proposed SVC algorithm, we set the random binary spreading codebook with N = 96 and K = 2.…”

Section: A Simulation Setupmentioning

confidence: 99%

Sparse Vector Coding for Ultra-Reliable and Low Latency Communications

Park

Shim

2017

Preprint

Self Cite

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Ultra reliable and low latency communication (URLLC) is a newly introduced service category in 5G to support delay-sensitive applications. In order to support this new service category, 3rd Generation Partnership Project (3GPP) sets an aggressive requirement that a packet should be delivered with 10 −5 packet error rate within 1 ms transmission period. Since the current wireless transmission scheme designed to maximize the coding gain by transmitting capacity achieving long codeblock is not relevant for this purpose, a new transmission scheme to support URLLC is required. In this paper, we propose a new approach to support the short packet transmission, called sparse vector coding (SVC). Key idea behind the proposed SVC technique is to transmit the information after the sparse vector transformation.By mapping the information into the position of nonzero elements and then transmitting it after the random spreading, we obtain an underdetermined sparse system for which the principle of compressed sensing can be applied. From the numerical evaluations and performance analysis, we demonstrate that the proposed SVC technique is very effective in URLLC transmission and outperforms the 4G LTE and LTE-Advanced scheme.

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