Future network trends driving universal metaverse mobility


Many networking capabilities will need to grow exponentially over the next decade to realize the full potential of technologies like XR, artificial intelligence (AI), the Internet of Things (IoT), and the Internet of Senses. Having successfully managed the exponential growth of each previous generation of technology, our industry is now investing in the advanced 5G and 6G research to meet the demands of the future.

Industry leadership requires 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 core compute and application actors. This requires collaboration between the different actors in the ecosystem to establish open standards that enable global scale, innovation, interoperability and performance.

Open the door to augmented reality

Starting with more basic functionality, XR applications will evolve as devices and network capabilities advance. Important application clusters for this development are, for example, gaming, entertainment, social communication, retail, shopping and virtual work.

Existing XR applications primarily focus on a single user physically residing in a predefined static environment with immersive content that is semi-static in the sense that it only partially adapts to the environment, e.g. B. by fixing it to the floor or another flat surface. This will evolve into dynamic environments containing moving objects and people, meaning applications will need to adapt to these dynamics.

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Eventually, as XR matures, it will be possible for multiple users to be physically present in dynamic environments with content that dynamically adapts to the environment. Real-time occlusion of rendered content enables a fully spatial digital experience.

In order to render the immersive content, the physical environment must be replicated in a digital format known as a spatial map. Spatial maps are based on static physical environment data, such as real estate and streets, overlaid with real-time physical environment data, such as moving cars and pedestrians.

In order to master rendering, the spatial map information must also include the application user’s location and orientation, including their head movement and foveal area – that is, the area covered by the part of the human eye responsible for sharp vision.

network development

XR applications require new system design optimization across the E2E ecosystem of device, connectivity, edge and cloud. For example, the spatial map calculation and the rendering distribution have a strong impact on the power consumption, weight and size of the device. Spatial mapping and rendering processing must be offloaded to design iconic devices with glasses style, slim form factor and long battery life. Our research at Ericsson shows that offloading XR applications to the edge reduces device power consumption by 3x to 7x, depending on the amount of processing offloaded on the device.

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The transition from traditional 2D media to advanced immersive media services increases the information load due to the multitude of media streams and increased media quality requirements. It puts asymmetrically high pressure on processing and transmission bitrates across the entire communications chain, depending on how the XR use case is implemented – meaning it can impact the uplink, the downlink, or a combination of both. For example, offloading computing power for device spatial mapping (to edge/cloud) results in more symmetrical traffic load in downlink and uplink compared to mobile broadband (MBB) traffic, which is mainly heavy downlink traffic.

To ensure QoE for XR applications, stringent requirements for limited latency are required when device data is offloaded to the edge and cloud. To reduce the limited latency requirements, intelligent processing techniques are implemented on the device, such as B. Asynchronous time-remapping that transforms network-rendered content to compensate for pose changes between the time it is rendered and when it is displayed.

To optimize QoE for all network users, traffic for XR applications can be separated from other MBB traffic using intent-based network slicing. To ensure latency requirements are met, it also introduces time-sensitive communication features such as RAN-assisted rate matching (low-latency, low-loss, scalable throughput technology) and latency-optimized scheduling.

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There is a strong relationship between wide area cellular network coverage, capacity and latency requirements. The key parameters for improving wide area cellular network coverage are allocation spectrum efficiency and distance between sites. For 2030, the Ericsson Mobility Report predicts a traffic increase that is higher than the expected frequency gains. As this will not be enough to support the projected increase in traffic, network densification will become more important to ensure capacity and increased uplink coverage for limitless connectivity.

The increasing differentiation of XR services and the variety of new device types require a smarter interaction with the network. In a cognitive network, orchestrating these interactions involves tasks such as device onboarding, connectivity management, and QoS policy selection. The network must be able to dynamically distribute actions across devices, RAN, core, edge and application to dynamically secure QoE with minimal E2E resource usage. A first step in this direction is Ericsson’s Dynamic End-User Boost, a smartphone app that allows the user to dynamically optimize QoE.



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