Dependable Connectivity for Industrial Wireless Communication Networks

TL;DR

The paper addresses the need for dependable IWCNs in 6G by arguing that end-to-end reliability, safety, and security must be considered beyond URLLC. It develops a theoretical dependability framework that defines attributes (availability, reliability, safety, security, resilience) and analytical tools to quantify them, while linking these concepts to practical design challenges. It then proposes concrete enablers, including adaptive multiple access with real-time monitoring and TSN-based end-to-end scheduling, and supports the approach with a case study on intelligent wake-up radios that yields substantial improvements in timely event detection. The work highlights open research questions and maps out directions for realizing CPS-grade dependability in dynamic industrial environments, with implications for 6G-driven IWCN deployments (e.g., latencies on the order of $0.5$ ms and failure probabilities around $10^{-9}$ in critical cases).

Abstract

Dependability - a system's ability to consistently provide reliable services by ensuring safety and maintainability in the face of internal or external disruptions - is a fundamental requirement for industrial wireless communication networks (IWCNs). While 5G ultra-reliable low-latency communication (URLLC) addresses some aspects of this challenge, its evolution toward holistic dependability in 6G must encompass reliability, availability, safety, and security. This paper provides a comprehensive framework for dependable IWCNs, bridging theory and practice. We first establish the theoretical foundations of dependability, including outlining its key attributes and presenting analytical tools to study it. Next, we explore practical enablers, such as adaptive multiple access schemes leveraging real-time monitoring and time-sensitive networking to ensure end-to-end determinism. A case study demonstrates how intelligent wake-up protocols improve event detection probability by orders of magnitude compared to conventional duty cycling. Finally, we outline open challenges and future directions for a 6G-driven dependable IWCN.

Figures (5)

• Figure 1: Examples of delay and error sources at the radio access network, core network, and the user-end.
• Figure 2: Representation of availability, reliability, and maintainability-related metrics.
• Figure 3: $N$ energy-harvesting devices monitoring critical events to report to a BS. Some sleep to conserve energy, while others remain sensing/active for critical event detection. Activation is spatially correlated, with probability decreasing as distance from the event, e.g., a faulty machine vibration epicenter, increases. The BS wakes up and assigns fast grants to devices that may provide additional information about an event, only possible for those at within a maximum distance from the event's epicenter as indicated by the dotted circle.
• Figure 4: Probability of the BS receiving enough event information within 5 ms vs. the number of devices for an intelligent duty-cycling/wake-up method and a benchmark, and using both group and individual WuS. The benchmark relies solely on spatial correlation, while the intelligent approach exploits the K-nearest neighbor algorithm to dynamically adjust duty cycling and wake-up decisions, incorporating both spatial correlation and battery state predictions. The group-dedicated WuS is formed by $\lceil \sqrt{N} \rceil$ devices, and $e^{-d}$ captures the activation probability of a device at distance $d$ from an event epicenter. The BS initially receives event data within a 1 ms slot, while receiving information from additional devices introduces two extra slots (for the wake-up request and subsequent sensing/transmission).
• Figure 5: A simplified illustration of the integration of a 5G network as a logical TSN switch in a TSN network. The TSN translators are deployed at BS and the user equipment side to synchronize with the external TSN network.