Many network capabilities will need to grow exponentially during the decade ahead in order to unleash the full potential of technologies such as XR, artificial intelligence (AI), the Internet of Things (IoT) and the Internet of Senses. After successfully handling the exponential growth of each previous technology generation, our industry is now investing in evolved 5G and 6G research to meet future requirements.
Industry leadership will require QoE differentiation from the best-effort services that have traditionally dominated the IT industry. Guaranteed QoE requires solutions that span the end-to-end (E2E) ecosystem of devices, networks, distributed and central computing, and application actors. This calls for collaboration among the different actors in the ecosystem to establish open standards that enable global scale, innovation, interoperability and performance.
Opening the door for extended reality
Starting from more basic functions, XR applications will develop as devices and network capabilities advance. Important application clusters for this evolution involve gaming, entertainment, social communication, retail, shopping and virtual work, for example.
Existing XR applications primarily focus on a single user who is physically present in a predefined static environment with immersive content that is semi-static in the sense that it only partially adapts to the environment, such as attaching to the floor or another flat surface. This will evolve to dynamic environments that contain moving objects and people, which means that applications need to start adapting to such dynamics.
As XR continues to mature, it will eventually be possible for multiple users to be physically present in dynamic environments with content that dynamically adapts to the surroundings. Real-time occlusion of the rendered content will enable a fully spatialized digital experience.
To render the immersive content, the physical environment needs to be replicated in a digital format known as a spatial map. Spatial maps are built on static physical environmental data, such as real estate and roads, overlaid by real-time physical environmental data such as moving cars and pedestrians.
To master the rendering, the spatial map information also needs to include the location and orientation of the application user, including their head movement and foveal area – that is, the area covered by the part of the human eye that is responsible for high-acuity vision.
XR applications will demand new system design optimization across the E2E system of device, connectivity, edge and cloud. For instance, spatial-map computation and rendering distribution will have a strong influence on device energy consumption, weight and size. Spatial mapping and rendering processing will need to be offloaded in order to design iconic devices with eyeglass-style, slim form factor and long battery life. Our research at Ericsson indicates that processing offload of XR applications to the edge reduces device energy consumption by threefold to sevenfold depending on the level of device processing offload.
The move from traditional 2D media to advanced immersive media services increases the informational load, due to the multiplicity of media streams and the increased media quality requirements. It puts high pressure on processing and transmission bitrates across the whole communication chain asymmetrically depending on how the XR use case is implemented – that is, it can impact the uplink, the downlink or a combination of both. For instance, device spatial-mapping compute offload (to edge/cloud) will result in a more symmetric traffic load in the downlink and uplink compared with mobile broadband (MBB) traffic, which is mainly heavy downlink traffic.
To guarantee QoE for XR applications, stringent bounded latency requirements are needed when device computing is offloaded to the edge and the cloud. To reduce the bounded latency requirements smart on-device processing techniques will be implemented, such as asynchronous time warp that transforms network-rendered content to compensate for pose changes between time of rendering and display.
To optimize QoE for all network users, the traffic for XR applications can be separated from other MBB traffic with the help of intent-based network slicing. Further, to ensure that latency requirements are met, time-critical communication features such as radio access network (RAN) assisted rate adaptation (using low-latency, low-loss, scalable throughput technology) and latencyoptimized scheduling will be introduced.
There is a strong relationship between wide-area cellular network coverage, capacity and latency demands. The key parameters for improving wide-area cellular network coverage are spectrum allocation efficiency and inter-site distance. For 2030, the Ericsson Mobility Report forecasts a traffic increase that is higher than the expected spectrum gains. As this will not be sufficient to support the forecasted traffic increase, network densification will grow in importance to ensure capacity and increased uplink coverage for unlimited connectivity.
The growing differentiation of XR services and the variety of new device types require more intelligent interaction with the network. In a cognitive network, the orchestration of these interactions involves tasks such as device onboarding, connectivity management and QoS policy selection. The network must have the ability to distribute actions among devices, the RAN, core, edge and application to dynamically secure the QoE with minimal E2E resource utilization. A first step in this direction is the Dynamic End-user Boost developed by Ericsson, a smartphone app that enables the user to dynamically optimize QoE.