Will 6G Require eXtreme Ultra-reliable Low-latency Communication (xURLLC)?

In an IEEE Comsoc article, Mehdi Bennis, Head of the Intelligent Connectivity and Networks/Systems Group (ICON) and Professor at University of Oulu explains:

URLLC is about extreme and rare events, where the goal is tantamount to characterizing and taming the TAIL distribution of latency/throughput (as opposed to the average-based design as in eMBB). While industry rushed towards system level simulations (In 3GPP reliability is calculated by counting the erroneous packets and the obtained number is divided by the total transmitted packets in the observed period), it is now back to understanding the fundamentals driving the tail behavior of URLLC.  In addition, and quite interestingly two extremes emerge when it comes to URLLC, which further underscores the importance of the codesign. On one hand predicting the rare events (9-nines) requires different modalities since relying on RF data modality alone may not be sufficient due to lack of data, or statistical irrelevance of the data. On the other hand, for some control applications (robotic arm) few consecutive packets can be lost, which suggests that the very stringent 9-nines requirements can be significantly relaxed in some cases! This begs the questions: instead of maximizing communication reliability as in 3GPP, what is the maximum number consecutive packets that can be lost/delayed while ensuring stability and safety of the control application. Unlike the prevailing model-based URLLC ensuring communication reliability when no models are available is a daunting task. This falls under the category of statistical learning whereby reliability must be coupled with sample complexity (how many samples are needed to learn a model for a given target reliability) while being robust to out of sample distributions, noisy data and other aspects such as generalization, dynamics, etc. While confronting the known unknown problem is one side of the coin, combating errors arising from the unknown unknowns, is more difficult to overcome and requires more wireless resources (more tx power, more bandwidth and so forth).


In a research paper (available here) where Prof. Mehdi was one of the contributors, xURLLC is explained as follows:

eXtreme ultra-reliable and low-latency communication (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.

You can get the PDF here.

At the 6G Global 2020, Prof. Mehdi did a presentation on EXTREME Ultra-reliable Low-latency Communication. The slides from that is available here and the video is available here.

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