Flexibility is key when navigating the future of 6G

The differences between 5G and 6G are not just about what collection of bandwidths will make up 6G in the future and how users will connect to the network, but also about the intelligence built into the network and devices. “The collection of networks that will create the fabric of 6G must work differently for an augmented reality (AR) headset than for an e-mail client on a mobile device,” says Shahriar Shahramian, a research lead with Nokia Bell Laboratories. “Communications providers need to solve a plethora of technical challenges to make a variety of networks based on different technologies work seamlessly,” he says. Devices will have to jump between different frequencies, adjust data rates, and adapt to the needs of the specific application, which could be running locally, on the edge of the cloud, or on a public service.

“One of the complexities of 6G will be, how do we bring the different wireless technologies together so they can hand off to each other, and work together really well, without the end user even knowing about it,” Shahramian says. “That handoff is the difficult part.”

Although the current 5G network allows consumers to experience more seamless handoffs as devices move through different networks — delivering higher bandwidth and lower latency — 6G will also usher in a self-aware network capable of supporting and facilitating emerging technologies that are struggling for a foothold today —Virtual reality and augmented reality technologies, for example, and self-driving cars. Artificial intelligence and machine learning technology, which will be integrated into 5G as that standard evolves into 5G-Advanced, will be architected into 6G from the beginning to simplify technical tasks, such as optimizing radio signals and efficiently scheduling data traffic.

Credit: Nokia; used with permission.

“Eventually these [technologies] could give radios the ability to learn from one another and their environments, “two Nokia researchers wrote in a post on the future of AI and ML in communications networks. “Rather than engineers telling the nodes of the network how they can communicate, those nodes could determine for themselves — choosing from millions of possible configurations — the best possible way to communicate.”

Testing technology that doesn’t exist yet

Although this technology is still nascent, it is complex, so it’s clear that testing will play a critical role in the process. “The companies creating the testbeds for 6G must contend with the simple fact that 6G is an aspirational goal, and not yet a real-world specification,” says Jue. He continues, “The network complexity needed to fulfill the 6G vision will require iterative and comprehensive testing of all aspects of the ecosystem; but because 6G is a nascent network concept, the tools and technology to get there need to be adaptable and flexible. ”

Even determining which bandwidths will be used and for what application will require a great deal of research. Second- and third-generation cellular networks used low- and mid-ranged wireless bands, with frequencies up to 2.6GHz. The next generation, 4G, extended that to 6Ghz, while the current technology, 5G, goes even further, adding so-called “mmWave” (millimeter wave) up to 71GHz.

To power the necessary bandwidth requirements of 6G, Nokia and Keysight are partnering to investigate the sub-terahertz spectrum for communication, which raises new technical issues. Typically, the higher the frequency of the cellular spectrum, the wider the available contiguous bandwidths, and hence the greater the data rate; but this comes at the cost of decreased range for a particular strength of signal. Low-power wi-fi networks using the 2.6Ghz and 5Ghz bands, for example, have a range in tens of meters, but cellular networks using 800Mhz and 1.9Ghz, have ranges in kilometers. The addition of 24-71GHz in 5G means that associated cells are even smaller (tens to hundreds of meters). And for bands above 100GHz, the challenges are even more significant.

“That will have to change,” says Jue. “One of the new key disruptors for 6G could be the move from the millimeter bands used in 5G, up to the sub-terahertz bands, which are relatively unexplored for wireless communication,” he says. “Those bands have the potential to offer broad swaths of spectrum that could be used for high data-throughput applications, but they present a lot of unknowns as well.”

Adding sub-terahertz bands to the toolbox of wireless communications devices could open up massive networks of sensing devices, high-fidelity augmented reality, and locally networked vehicles, if technology companies can overcome the challenges.

In addition to different spectrum bands, current ideas for the future 6G network will have to make use of new network architectures and better methods of security and reliability. In addition, the devices will need extra sensors and processing capabilities to adapt to network conditions and optimize communications. To do all of this, 6G will require a foundation of artificial intelligence and machine learning to manage the complexities and interactions between every part of the system.

“Every time you introduce a new wireless technology, every time you bring in a new spectrum, you make your problem exponentially harder,” Nokia’s Shahramian says.

Nokia expects to start rolling out 6G technology before 2030. Because the definition of 6G remains fluid, development and testing platforms need to support a diversity of devices and applications, and they must accommodate a wide variety of use cases. Moreover, today’s technology may not even support the requirements necessary to test potential 6G applications, requiring companies like Keysight to create new testbed platforms and adapt to changing requirements.

Simulation technology being developed and used today, such as digital twins, will be used to create adaptable solutions. The technology allows real-world data from physical prototypes to be integrated back into the simulation, resulting in future designs that work better in the real world.

“However, while real physical data is needed to create accurate simulations, digital twins would allow more agility for companies developing the technology,” says Keysight’s Jue.

Simulation helps avoid many of the interative, and time-consuming, design steps that can slow down development that relies on successive physical prototypes.

“Really, kind of the key here, is a high degree of flexibility, and helping customers to be able to start doing their research and their testing, while also offering the flexibility to change, and navigate through that change, as the technology evolves, “Jue says. “So, starting design exploration in a simulation environment and then combining that flexible simulation environment with a scalable sub-THz testbed for 6G research helps provide that flexibility.”

Nokia’s Shahramian agrees that this is a long process, but the goal is clear For technology cycles, a decade is a long loop. For the complex technological systems of 6G, however, 2030 remains an aggressive goal. To meet the challenge, the development and testing tools must match the agility of the engineers striving to create the next network. The prize is significant — a fundamental change in the way we interact with devices and what we do with technology. ”

This content was produced by Insights, the custom content arm of MIT Technology Review. It was not written by MIT Technology Review’s editorial staff.

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