In the first blog of this series, Getting Ready for 6G, I introduced some of the common technical aspirations of 6G cellular technology, such as high bandwidth, low latency, increased security, AI integration & extended reality (XR). Given that all of these technical aspirations are already available today, the question arises: what will set 6G apart and make it different from existing technology?
While the services that make up the later stages of 5G are still under development, in current 5G networks are predominantly based on Release 15 & 16. Currently, 5G releases primarily prioritize Enhanced Mobile Broadband (eMBB) for faster and more reliable broadband, while also reserving space for future technologies such as Massive Machine Type Communications (mMTC) and Ultra Reliable Low Latency Communications (URLCC). These technologies are critical components of 5G, facilitating connections of a massive number of devices and delivering industrial-grade robust communication. Proposed in Release 17/18, these additional features are part of an incremental roadmap that should be technically viable by 2024/2025. Enhancements (R19/R20) of these features are anticipated to be commercially available by the end of the decade. Collaboration among all stakeholders in in industry, academia, and society is essential, as each element must be scalable, commercially viable, and serve a relevant use case.
Figure 1 – Tentative 6G Timelines
In the upcoming blogs of this series, I will explore the vast and varied potential use cases for 6G networks, ranging from sustainability and urban planning to remote work and human-robot collaboration. By leveraging new features such as cognitive networks, embedded devices, and massive compute fabrics, 6G has the potential to revolutionize the way we live, work, and interact with the world around us. Before exploring the potential of 6G to enable exciting use cases such as massive digital twins, hyper-immersive environments, collaborative industrial robots, and zero-power connected clothing, it is important to understand the enabling features that will be available to future network operators. These features will be crucial in a in a fully converged, hyper-connected network that utilizes millions of low Earth orbit satellites. Additionally, we will explore the two-way interactions with society that will drive the success of 6G features and their user capabilities.
As mentioned in the previous blog, there is no single definitive source or knowledge that dictate which features will be deployed in 6G technologies. Various innovators have provided their input, focusing on technical features and high level drivers to identify and create potential use cases. Vendors, 6G research centres and collaborative projects have presented these inputs to standards bodies like the ITU.
Although each of these enabling features had the potential to be included in the 5G/5.5G cadence, they were deemed too futuristic, impractical to implement with current technology, or just beyond the realm of existing thought. However, as technology has advanced, these once visionary ideas and features have become feasible, allowing them to converge and provide a clearer picture of what will be included in 6G.
The primary difference between 5G and 6G will be the use of even higher frequencies to support the increased bandwidth. To achieve this higher capacity, experts recommend expanding the spectrum bandwidth to include the centimetric spectrum between 3 GHz and 30 GHz, as well as the higher frequency ranges of 100-300 GHz and even into terahertz spectrum. While this may seem like a presumptive grab for high bandwidth that is currently used in few niche fields, it is being accompanied by advancements in short-range non-network communications. This includes device-to-device communication with extremely high throughput, super-accurate location services, and moving the power requirement from the mobile device to dense radio networks. These connectivity challenges will require parallel spectrum requirements and will need AI-driven adaptability to perform.
Besides emerging radio technologies like NR-RedCap (Reduced Capability), which offers better radio performance with lower power requirements, 6G will use new artificial intelligence (AI) powered air interfaces to optimize channel efficiency of the radio channels, as described in a later section of this blog. Furthermore, meet the high demands for capacity and throughput, location sensitive beamforming at any spectrum, improvements must be made to the radio technology itself. This includes a significant increase in number of components in massive arrays to work with these new wavelengths, which will also need to be supported by increased intelligence near every communication device.
In the 2030s, 6 G networks will have a comprehensive understanding of the data they carry, thanks to the increased use of edge devices. Distributed edge resources will not only provide computational power close users and devices, but will also serve as network linked tactile senses. This includes sensing air quality, capturing visual and haptic input, and identifying gesture and signs to provide feedback to the network and improve end-to-end performance. Although early critical networks have access to this form of networked sensing, this information is often overlooked or excluded from design in most 5G networks, both in the private and public sectors.
Figure 2 – With 6G, The network will be everywhere
There are differing approaches being considered for the computational infrastructure of the 6G network. Some envision dependable compute enablers made available as a service to the network controllers, while other predict that large scale, distributed cost-efficient edge computing will become the norm to allow logic to be available closer to the source of the data entering the network. Similar to the required radio advancements for 6G, semiconductor innovation will be crucial to meet the demand for large scale, distributed, and cost-efficient edge computing. However, the progress in non-noisy, high q-bit quantum computing could render traditional semiconductor innovation in this area redundant, making it necessary to closely monitor developments in this field.
Further increasing the number of devices, we can also expect to see more zero or near-zero energy sensor devices, also known as Zero-energy Devices (ZEDs), which have already demonstrated low power communication and are expected to proliferate as the transceivers transfer radio power to the devices. This will meet a number of sustainability targets in allowing long-term devices to be deployed, as well as optimizing the power requirements of macro and micro networks.
The role of AI will be substantial in the roadmap for 6G technology. The vision is to create an autonomous, zero touch network with predictive performance and distributed intelligence. Achieving this goal will require the latest innovations in transformers and machine learning, enabling the network to self-evolve and make intelligent decisions that support its operation as both an both mMTC+ and URLCC+ networking. Hyper sensitive location data will be fed into the network’s intelligence to bridge the gap between time sensitive, constrained, fixed networks and those currently being deployed in a private environment using R16/R17 features.
Figure 3 – AI will permeate 6G, but will need observation and control
The transition from service-based and software-defined network operations to AI-embedded architectures with complete network intelligence, will significantly reduce the burden of operations and support. The initial versions of 6G will augment AI enabled networking features, with large language models (LLMs) capable of understanding and translating business and user needs into network requirements. The ubiquitous sensor data that will be pervasive in fully converged 6G networks will provide input for autonomous configuration and network decision making.
By 2030, networks will possess a complete and comprehensive, built in-digital twin of all elements of performance, optimization, and sustainable power utilization, resulting in a fully autonomous network available to all providers. This technology can be used to build smart-cities, smart-industry, and beyond.
Overall, 6G networks will be permeated with AI throughout every layer of its fabric. So where are the humans?
As networks become more autonomous, network management will also require automation. By 2030, networks will need to incorporate advances in zero-touch deployment and management, and can learn from the best practices of every network deployment from 1999 onwards.
Figure 4 – Operations will be as simple, and important, as watching an Autopilot
However, there will still be a requirement to reintroduce human involvement. Improved observability, service-specific reporting with multiple perspectives, and a single view will enable human observers to work alongside AI-powered network management.
Which brings us to where operations will evolve. As networks become more integrated into our daily lives in homes, cities, hospitals, and schools, providers will need to explain every decision made and ensure the network is behaving ethically. This requires the field of explainable AI, which is still in its early stages, and regulators are putting controls in place to mitigate any negative impact on society. If AI makes a decision that affects the public, there needs to be a trail. Weaving AI into sensors, edges, cores, and clouds could be a significant operational burden for communications providers, so resources must be available to manage this.
Without getting too far into dystopia, we also know that 6G will not solve all problems, and existing networks must be integrated. To achieve the desired performance, protocol convergence will be necessary. Mobile networks cannot do this alone, and we will see a gradual convergence of IEEE technologies, leading to the integration of Wi-Fi into the mobile sphere of influence. This marks only the beginning of the process.
The networks in 2030 will not be confined to the cell towers that are visible today. First introduced in Release 17/18 of the 5G standards, Non-terrestrial networks (NTNs) expanded beyond simply integrating with other network access technologies like Wi-Fi, and began incorporating space-based hardware into their systems. Using satellites for network backhaul has been around since the early stages of global communications. However, the latency between geostationary satellites at 35km was not very efficient for high bandwidth communications in terms of resource usage and cost, despite being suitable for remote voice circuits. Nevertheless, the proliferation of high altitude drones and an increasing number of low/very low earth orbit satellite constellations has made them a viable alternative for global coverage.
Figure 5 – 6G Non-Terrestrial Networks
What makes these satellite constellations very exciting is that they are positioned low enough to provide a radio link directly to mobile device, without the need to connect to a local radio in a ‘bent-pipe’ relay configuration which can be supported by current satellite technology. The upcoming iteration of NTN will support more efficient use of very low Earth orbit (VLEO) spectrum, enabling communication to multi-user earth-based terminal devices. As this is 6G technology, changes to the radio access layer and convergence of the network infrastructure will necessary to accommodate ‘mobile gNodeBs’ or other terminology that might be used to describe the satellite gateways. This could potentially offer the benefit of a zero base station global communications system with almost no dead zones.
Why is this important? A third of the people on our planet do not have access to the Internet, and by 2030, this technology has the potential to bring connectivity to everyone else.
This blog provided a high-level overview of the enabling features that 6G networks are expected to support to deliver faster speeds, higher capacity, and ultra-low latency. These features have the potential to bring us closer to a fully connected planet and enable a hyperconnected society, laying the foundation for future advancements. In future blog posts, I will discuss where the Metaverse, AR/VR/XR, and security and identity endeavours such as 6G Blockchain fit into this vision.
New capabilities such as integrated sensing and communication, all-scenario supporting IoT, distributed computing, and embedded AI will require significant research and innovation. Integrating AI into different domains, rather than just integrating existing machine learning (ML) capabilities will lead to a more focused use of resources and data making 6G networks more intelligent, efficient, and sustainable.
As 6G is still in the early stages of development, it will be interesting to see how these features evolve and how they will impact the way we interact with technology in the future. The next blog post in the series will continue this discussion.