Extreme URLLC: Vision, Challenges, and Key Enablers

TL;DR

This paper explores the limitations of 5G URLLC and proposes a new framework called xURLLC that integrates machine learning, multimodal sensing, and joint communication-control design to meet the demands of future ultra-reliable low-latency applications.

Contribution

It introduces the concept of xURLLC, outlining its core principles and research directions to advance beyond-5G ultra-reliable low-latency communication systems.

Findings

Identifies limitations of current 5G URLLC systems.

Proposes a holistic xURLLC framework with key enabling technologies.

Highlights potential for mission-critical applications in 6G.

Abstract

Notwithstanding the significant traction gained by ultra-reliable and low-latency communication (URLLC) in both academia and 3GPP standardization, fundamentals of URLLC remain elusive. Meanwhile, new immersive and high-stake control applications with much stricter reliability, latency and scalability requirements are posing unprecedented challenges in terms of system design and algorithmic solutions. This article aspires at providing a fresh and in-depth look into URLLC by first examining the limitations of 5G URLLC, and putting forward key research directions for the next generation of URLLC, coined eXtreme ultra-reliable and low-latency communication (xURLLC). xURLLC is underpinned by three core concepts: (1) it leverages recent advances in machine learning (ML) for faster and reliable data-driven predictions; (2) it fuses both radio frequency (RF) and non-RF modalities for modeling and combating rare events without sacrificing spectral efficiency; and (3) it underscores the much needed joint communication and control co-design, as opposed to the communication-centric 5G URLLC. The intent of this article is to spearhead beyond-5G/6G mission-critical applications by laying out a holistic vision of xURLLC, its research challenges and enabling technologies, while providing key insights grounded in selected use cases.