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Taking adaptiveness in QoS to the next level in 6G

Taking adaptiveness in QoS to the next level in 6G

Recently, 3GPP held a key workshop to explore potential use cases for 6G technology. These use cases will shape the design, construction and feature sets of 6G technology. Amongst a plethora of innovative use cases that catered to both consumers and enterprises, some of the most promising were interactive applications such as extended reality (XR), metaverse, compute off-load (incl. AI/ML capabilities), real-time digital twins, remote-X, and industrial control. These applications will need high bandwidth, high DL/UL data rates and very low latency.

There are always a limited number of resources available in any network that need to be shared among connected users, so traffic management and quality of service (QoS) targets are always essential. In generations before 5G, however, there wasn’t such a diversity of applications with such widely differing requirements. With 5G and, as the above use cases demonstrate, with 6G, the need for managing network resources will only increase and network adaptiveness will need to be taken to a whole new level.

To cope with the complexity of future services, recent and future innovations aim to enhance cellular network adaptability and responsiveness. Examples of those innovations include Nokia’s Network as Code (NAC) and Low Latency, Low Loss, Scalable Throughput (L4S). NAC offers a platform and empowers developers and end users to further exploit application programming interfaces (APIs) to directly request the services they need from the network. It also enables programmable networks. Application developers and end users can then, for instance, request a specific QoS via these APIs. Nokia-pioneered L4S technology, which reduces the latency experienced by packets even under congestion, enables support for consistent low latency thereby reducing and/or eliminating the jitter.

The enriched QoS framework of 5G

When considering how to enforce QoS in cellular networks, especially when there is contention for resources, there are similar traffic management principles applied as on the internet (e.g., based on traffic differentiation and prioritization). Cellular networks need to go one step further, however, as they need to ensure a minimum QoS offering while also managing the variations incurred due to the air interface. Furthermore, cellular networks also offer the ability to support both guaranteed and best effort QoS services. Guaranteed QoS is based on the standardized 3GPP QoS framework for 5G/5G-Advanced.

The recently finalized Release 18 has introduced many enablers to enhance the 5G-Advanced QoS framework and support for XR services. These include enabling a finer QoS granularity than before (i.e., PDU set or application data unit such as a video frame), providing additional assistance information to the cellular network on how to treat XR traffic as well as application awareness. These features are building a good foundation for future services in 6G, while at the same time, they help identify those aspects that remain challenging for the current QoS framework.

Understanding the boundaries of the current QoS framework is crucial to determine the improvements needed for relevant 6G day-one use cases. With the emerging NextGen-XR and immersive/cloud gaming services, one of the key challenges is in being able to provide the best possible QoS and quality of experience (QoE) considering demanding application needs (high bandwidth, changing traffic characteristics, low latency, high data rate) and also considering wireless network conditions (e.g., high resources needed in the cell edge). These services also require seamless real-time interaction between users and devices. They will be omnipresent and consumer centric.

Typically, radio resource allocation strategies in cellular networks fall into two categories: best effort or strict guarantees. The first provides no guarantees, which does not always meet the needs of XR or NextGen-XR applications that require low latency and high bandwidth. The second does provide strict guarantees for data traffic (e.g., strict QoS requirements defined and protected by the cellular network for a service), but this approach has scalability issues for a wide area network. However, for high data rate and interactive services that can adapt to the changing traffic characteristics of XR applications, we need adaptive QoS framework for 6G on day-1.

Cellular network adaptability will be needed during the 6G era

A higher need for adaptiveness will not only come from new services in 6G. The network will also need to optimize its operations to deliver today’s well-known services such as video on demand, live streaming, embedded video, and video conferencing. An adaptive QoS framework can be achieved in 6G by extending the current QoS framework to operate with soft QoS guarantees.

Instead of relying on hard, absolute QoS guarantees, service agreements can, alternatively, define the soft guarantees the network must fulfil. Soft QoS guarantees enable the service to indicate a range of values for QoS attributes (e.g., data rate, latency, packet error rate). These attributes define what the service can tolerate from a minimum to an optimal QoE for a given user, as illustrated in Figure 1. Soft QoS guarantees can be achieved by adding a new resource type, i.e., Adaptive QoS, and the related operation of the soft QoS guarantees to the current QoS framework in 3GPP.

Figure 1. Comparison of 6G QoS guarantee options

Figure 1

One simple example of how soft QoS could work with the other types of QoS offering is illustrated in Figure 2, which compares an optimal scenario with a congested scenario. For hard QoS guarantees, enough resources need to be reserved to ensure the service for N1 users at the bit rate G. If the users have bad coverage, this will be resource intensive and lead to scalability issues. For no QoS guarantees (i.e., best effort) or soft QoS guarantees, the offered bit rate can change to adjust the resources allocated to those data flows. With soft QoS guarantees, operators can do their best to, at least, meet the minimum QoS requirements while striving to provide QoS at or near the target values of the indicated QoS attribute ranges to achieve better QoE for end users. 

Figure 2. Resource allocation treatment for the envisioned 6G QoS guarantee options

Figure 2

The use of soft QoS guarantees could change how 6G networks manages resources while simultaneously improving the end user experience. This change will benefit various actors in the network. Soft QoS guarantees could further incentivize service differentiation in cellular networks, as hard QoS guarantees are resource intensive. Additionally, services that do not require hard QoS guarantees could benefit from tiered service offering based on adaptive QoS framework.

An adaptive QoS framework with soft QoS guarantees will provide a strong foundation for a more flexible QoS system for 6G, making it ready for high-bandwidth adaptive applications in the 2030 era.

Pilar Andres

About Pilar Andres

Pilar is a Senior Research Specialist at Nokia, where she has been actively involved in research related to 5G standardization for industrial internet of things and time synchronization. Currently, her focus is on 6G research, specially on quality of service area.

Devaki Chandramouli

About Devaki Chandramouli

Devaki is a Bell Labs Fellow and Head of North American Standardization at Nokia. She serves as Next G Alliance Steering Group Co-chair and is the rapporteur and lead for 5G System Architecture specification in 3GPP. She also serves as a rapporteur for many key work items related to private networks, industrial 5G, timing resiliency and URLLC enhancements in 3GPP SA2.

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