RT Journal Article
T1 Dynamic Packet Duplication for Industrial URLLC
A1 Segura, David
A1 Khatib, Emil Jatib
A1 Barco-Moreno, Raquel
K1 Telecomunicaciones
AB The fifth-generation (5G) network is presented as one of the main options for Industry 4.0 connectivity. To comply with critical messages, 5G offers the Ultra-Reliable and Low latency Communications (URLLC) service category with a millisecond end-to-end delay and reduced probability of failure. There are several approaches to achieve these requirements; however, these come at a cost in terms of redundancy, particularly the solutions based on multi-connectivity, such as Packet Duplication (PD). Specifically, this paper proposes a Machine Learning (ML) method to predict whether PD is required at a specific data transmission to successfully send a URLLC message. This paper is focused on reducing the resource usage with respect to pure static PD. The concept was evaluated on a 5G simulator, comparing between single connection, static PD and PD with the proposed prediction model. The evaluation results show that the prediction model reduced the number of packets sent with PD by 81% while maintaining the same level of latency as a static PD technique, which derives from a more efficient usage of the network resources.
PB MDPI
YR 2022
FD 2022-01-13
LK https://hdl.handle.net/10630/36185
UL https://hdl.handle.net/10630/36185
LA eng
NO Segura, D.; Khatib, E.J.; Barco, R. Dynamic Packet Duplication for Industrial URLLC. Sensors 2022, 22, 587. https://doi.org/10.3390/s22020587
NO This work has been partially funded by Junta de Andalucía (Consejería de Transformación Económica, Industria, Conocimiento y Universidades, Proyecto de Excelencia PENTA, P18-FR-4647 and EDEL4.0, UMA18-FEDERJA-172) and ERDF.
DS RIUMA. Repositorio Institucional de la Universidad de Málaga
RD 21 ene 2026