Communication-Control Co-design for Robotic Manipulation in 5G Industrial IoT

Arvind Merwaday, R. Vannithamby, Mark Eisen, Susruth Sudhakaran, D. Cavalcanti, V. Frascolla
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Abstract

Industrial Internet of Things (IIoT) use cases have stringent reliability and latency requirements to enable real-time wireless control systems, which are supported by the 5G ultra-reliable low-latency communications (URLLC). However, extremely high quality-of-service (QoS) requirements in 5G URLLC causes huge radio resource consumption and low spectral efficiency, thus limiting network capacity in terms of the number of supported devices. Industrial control applications typically incorporate redundancy in their design and may not always require extreme QoS to achieve the expected control performance. Therefore, we propose both communication-control co-design and dynamic QoS to address the capacity issue for robotic manipulation use cases in 5G-based IIoT. We have developed an advanced co-simulation framework that includes a network simulator, physics simulator, and compute emulator, for realistic performance evaluation of the proposed methods. Through simulations, we show significant improvements in network capacity (i.e., the number of supported URLLC devices), and about 2x gain for the robotic manipulation use case.
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5G工业物联网机器人操作的通信控制协同设计
工业物联网(IIoT)用例具有严格的可靠性和延迟要求,以实现5G超可靠低延迟通信(URLLC)支持的实时无线控制系统。但由于5G URLLC对服务质量(QoS)的要求极高,导致无线资源消耗巨大,频谱效率较低,因此在支持设备数量上限制了网络容量。工业控制应用程序通常在其设计中包含冗余,并且可能并不总是需要极高的QoS来实现预期的控制性能。因此,我们提出通信控制协同设计和动态QoS来解决基于5g的工业物联网中机器人操作用例的容量问题。我们开发了一个先进的联合仿真框架,包括网络模拟器、物理模拟器和计算模拟器,用于对所提出的方法进行现实的性能评估。通过模拟,我们展示了网络容量(即,支持的URLLC设备的数量)的显著改进,并且在机器人操作用例中获得了大约2倍的增益。
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