Proactive dual connectivity for automated guided vehicles in outdoor industrial environment - Mendoza, Jessica; Kovács, István Z.; López, Melisa; Sørensen, Troels B.; Adeogun, Ramoni; De la Bandera Cascales, Isabel; Barco-Moreno, Raquel (IEEE, 2022)
5G communication systems are one of the major enabling technologies to meet the needs of Industry 4.0. This paper focuses on the use case of automated guided vehicles (AGVs) in an outdoor industrial scenario. To meet the communication requirements in these type of use cases, dual connectivity (DC) with resource aggregation in the uplink (UL) is generally proposed. However, uncontrolled use of DC schemes may negatively affect the network causing effects such as reduced network capacity, increased signaling, and increased interference. To overcome these issues, this paper proposes and evaluates the use of a proactive DC activation algorithm based on the instantaneous quality of service (QoS) and network conditions. The proposed algorithm has two phases, a first phase in which the QoS prediction is performed, and a second phase in which the DC activation decision is made. The performance evaluation of the algorithm has been carried out in two different scenarios: a single-frequency (SF) network and a dualfrequency (DF) network; and compared to two baselines. Our results show that our predictive DC algorithm is sufficiently robust and can offer benefits in terms of reduced signaling and increased UL performance, especially in scenarios with low to medium traffic load.
Keywords: Vehículos autodirigidos; Robots industriales; Algoritmos computacionales; Automated guided vehicles; Dual connectivity; Industry 4.0; Proactive network management; Quality of service; Uplink