Electronic International Standard Serial Number (EISSN)
The Industry 4.0 paradigm aims to bring real-time production data analytics, cloud computing, and cyber-physical inter-connectivity to today's industries. This evolution fosters network-based use cases, such as remote-controlled mobile robots with stringent network latency requirements. 5G networks have become a promising technology for such use cases. However, 5G wireless communication is affected by time-varying random delays, which impact the use-case's reliability, stability, and performance. Thus, there is an urgent need to design mechanisms to compensate for these time-varying delays at the remote end. The delay estimation can be achieved by leveraging the MEC framework on top of 5G (MEC-based 5G). Thus, this work presents a novel architecture to exploit the radio network information provided by the MEC framework to improve the performance of remote-controlled mobile robots leveraging 5G. This radio network information is used to estimate the current network delays. Accordingly, these estimated delays together with the delayed information sent by the robot are availed to the robot controller at the remote end for compensation. Besides, the message-sequence flow between the different architecture components is analyzed in detail, and the modeling equations are described. Extensive simulations prove the effectiveness of the proposed approach. Our approach is compared with the network delay estimation based on the Kalman filter. An improvement of at least 55% and 33% in the tracking error and control effort, respectively, are observed for delay values ≥150 ms.