The 5G Phase-2 and beyond wireless systems will focus more on vertical applications such as autonomous driving and the Industrial Internet of Things, many of which are categorized as uRLLC. In this article, an alternative view of uRLLC is presented, information latency, measuring the distortion of information resulting from time lag of its acquisition process, which is more relevant than conventional communication latency of uRLLC in wireless networked control systems. An AI-assisted SMART is presented to address the information latency optimization challenge. Case studies of typical applications (i.e., dense platooning and intersection management) in AD are demonstrated, which show that SMART can effectively optimize information latency, and more importantly, information latency-optimized systems outperform conventional uRLLC-oriented systems significantly in terms of AD performance such as traffic efficiency, thus pointing out a new research and system design paradigm.

中文翻译：

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人工智能辅助的低信息延迟无线网络

5G第二阶段及以后的无线系统将更加专注于垂直应用，例如自动驾驶和工业物联网，其中许多都归为uRLLC。在本文中，提出了uRLLC的另一种观点，即信息等待时间，用于测量由于其获取过程的时滞而导致的信息失真，这比uRLLC在无线网络控制系统中的常规通信等待时间更为相关。提出了一种AI辅助的SMART，以解决信息延迟优化挑战。演示了AD中典型应用（即密集排和交叉路口管理）的案例研究，表明SMART可以有效地优化信息延迟，更重要的是，