Ultra-reliable and low-latency communications (URLLC) is introduced as one of three main components of 5G new radio (5G NR). By providing high-quality wireless links with ultra-reliability (i.e., up to 99.99999\%) and near-zero latency (i.e., 1 ms), URLLC is powerfully realising a wide range of mission-critical applications in different domains such as telesurgery, immersive entertainment, tactile internet, and autonomous industry. In industrial automation, the enhancement of URLLC plays a significant role in enabling time-sensitive applications like motion control, mobile robots, video-driven machine-human interaction, and augmented reality (AR) / virtual reality (VR) for maintenance. Therefore, the development and deployment of URLLC have been recently drawing much attention in both academia and industry.This thesis mainly focuses on URLLC and its applications in industrial automation. The contributions of this thesis can be summarised as follows. We first summarise the overview of URLLC and mobile edge computing (MEC) technologies, their applications, and state-of-the-art literature. Then, research problems relating to URLLC reliability and end-to-end latency for industrial automation are addressed by mathematical formulations and solutions. The considered problems span various aspects of wireless communication resources like blocklength, bandwidth, power control, and computing resource management in MEC-based systems. Finally, extensive results from simulations are depicted to validate the effectiveness of the proposed schemes in terms of improving transmission reliability, reducing latency, as well as optimising system resources in studied models.
| Date of Award | Dec 2023 |
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| Original language | English |
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| Awarding Institution | - Queen's University Belfast
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| Supervisor | Trung Q. Duong (Supervisor) & Thai Son Mai (Supervisor) |
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- Ultra-reliable and low-latency communications
- mobile edge computing
- digital twin
- industrial automation
- convex optimisation
Ultra-reliable and near zero-latency communications for industrial automation
Huynh, D. V. (Author). Dec 2023
Student thesis: Doctoral Thesis › Doctor of Philosophy