Predictive Quality of Service: Wide Industry Recognition and Best Practices
The 5G Automotive Association (5GAA) is driving the development, implementation and standardisation of Predictive Quality of Service across the automotive sector and beyond.
Mission-critical applications rely on QoS requirements being met since failure or suspended operation can have a high cost. This means overcoming challenges such as networks not always guaranteeing the required QoS of a service and the need to adapt to changes in the QoS in a given scenario or use case. For 5G in the automotive sector, use cases span high-density platooning, tele-operated driving, lane merge assist, infotainment, software updates, hazardous location warning.
QoS Key Performance Indicators for prediction include application-specific actions, such as changing inter-vehicular distance, handover to driver (e.g. platooning), changing video quality.
However, predictive QoS is applicable not only to the automotive sector but has wide industry recognition as the 5GAA webinar in March 2020 demonstrated.
- 5GAA and its Working Groups
- NESQO predictable QoS and end-to-end network slicing for automotive use cases: defined the requirements and architectural enhancements needed to support predictive QoS in the 3GPP system, addressing both MNO-based and OTT-based predictions.
- eNESQO enhanced E2E network slicing and predictive QoS: brings forward the results of previous WI NESQO, e.g. in the areas of making predictions, Prediction Function Location, Application and Network Reaction to QoS prediction and proposes 6 areas of improvement for the current 5G solution.
- MEC4AUTO multi-access edge computing technology for automotive services: studies the use of MEC in multi-MNO and multi-OEM scenarios. The WI evaluates support for in-advance QoS notification (IQN) management in multi-operator scenarios, including a potential definition of a NESQO-Edge API.
5GAA White Paper: Making 5G Proactive and Predictive for the Automotive Industry
- 5G-ACIA and its Working Groups
- ADAPT in-advance/predictive QoS notification for 5G: investigates the usage of Predictive QoS for industrial automation.
- 3GPP SA1; SA2; SA6
- SA1: TS 22.186 "Enhancement of 3GPP Support for V2X Scenarios" (Release 16): received 5GAA NESQO requirements on Predictive QoS.
- SA2: TS 23.288 "Architecture Enhancements for 5G System (5GS) to support network data analytics services" (Release 16): defines the QoS Sustainability Analytics that includes QoS predictions. QoS-related prediction analytics also introduced in the context of other key issues.
- SA2: TS 23.287 "Architecture Enhancements for 5G System (5GS) to support Vehicle-to-Everything (V2X) scenarios" (Release 16): includes procedure for V2X Application adjustment based on the QoS sustainability analytics.
- SA2: TR 23.700 "Enablers for Network Automation for 5G - phase 2": includes a key issue "NWDA-assisted predictable network performance", which addresses Predictive QoS topics.
- SA6: TR 23.764 "Study on Enhancements to application layer support for V2X services" (Release 17): includes a key issue (2a) about exposing potential change procedure in TS 23.287 to dynamically provide/adapt the service operation and related QoS requirements for single or groups of UEs.
- ETSI ISG MEC (Multi-access Edge Computing)
- Generic Slice Template (GST) NG.116 V2.0: includes performance prediction as one attribute for the capability of the mobile system to predict the network and service status.
- 5GCroCo - 5G Cross-border Control (5G PPP Horizon 2020 Innovation Action) has the objective to test and validate 5G features, including Predictive QoS.
5GAA Webinar on 26 March 2020: Predictive QoS - using 5G network data analytics to enable proactive C-V2X adaptation
The webinar helped the group behind this Standards Tracker to evolve its collaborative mapping of common requirements across industry verticals. It also underscored the importance of working together across verticals, related associations and the telecommunications industry on common priority topics to drive best practices underpinning standardisation.