A survey on FEC techniques for industrial wireless communications
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...
| Autores: | , , , , , , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2022 |
| País: | España |
| Institución: | Universidad del País Vasco |
| Repositorio: | Addi. Archivo Digital para la Docencia y la Investigación |
| OAI Identifier: | oai:addi.ehu.eus:10810/71792 |
| Acceso en línea: | http://hdl.handle.net/10810/71792 |
| Access Level: | acceso abierto |
| Palabra clave: | complexity factory automation (FA) forward error correction (FEC) industrial wireless communications industry 4.0 latency PHY reliability short packet transmission wireless communications |
| Sumario: | 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 toward 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 article 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. This article 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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