6G: The Next Generation of Wireless Communication



6G communication is at the stage in which thought leaders from academia and industry lay out possibilities, dream big, and envision what the world could look like in 10 or 20 years. With new, futuristic use cases such as Tactile Internet, it’s easy to get caught up in the excitement of defining the next-generation cellular communication standard and geek out over novel technology pushing the bounds of what was ever thought possible. But in many respects, our industry is still waiting for the lofty promises of 5G to materialize, and as work continues on broader deployment and the next phase of 5G enhancements, we’re left wondering: Why are we already talking about 6G?

The Evolution of a G

Beginning with the first mobile phone call back in 1973, using what later became “1G,” our industry has observed major evolutions in cellular technology over roughly 10-year cycles. 4G’s timeline unfolded between 2000 and 2010. 3GPP began working toward 5G standardization in 2015, but academic research was already well underway by that point, with NYU Wireless and METIS having been founded in 2012. Phase 1 standardization was complete with Release 15 in 2018, field trials in 2019, and deployments starting to ramp up in 2020. Today, the pattern looks to be holding, with early 6G research happening in support of a 2025 standardization start and a 2030—or even earlier—deployment timeline. Although the prospect of consumers purchasing their first 6G devices may seem far away, academic and industry researchers at the forefront of these cycles already are experimenting and building an understanding of key technologies critical for standardization.    

Figure 1. Cellular Technology Evolution


What Could 6G Deliver?

The International Telecommunications Union, which laid out the goals for 5G in the IMT-2020 standard, has begun work on the vision for 6G under the Network 2030 Focus Group. They grouped performance vectors including throughput, reliability, coverage, latency, energy, cost, and massive connectivity into three 5G usage scenarios—enhanced mobile broadband (eMBB), massive machine type communications (mMTC), and ultrareliable low latency communications (URLLC)—supporting a myriad of applications across a diverse set of industries. 6G is expected to expand on these vectors, driving advances in existing applications while introducing new use cases and business models. Among these are holographic-type communications for fully immersive 3D experiences and Tactile Internet for real-time remote operation with audio, visual, and haptic feedback. These examples illustrate how important sensing is to 6G: It is the basis for all interaction with and emulation of the physical environment, and its potential extends to digital health, autonomous vehicles, and beyond. 


Promising Technologies for Exploration

As we look at 6G’s possibilities and promise, four candidate technologies stand out in terms of business opportunity and viability.

Joint Communication and Sensing

The 6G experience requires more data as well as more environmental sensing and awareness—and joint communications and sensing explores combining them. Autonomous vehicles, for example, have incredibly sophisticated sensing systems powered by machine-learning algorithms fusing data from an array of cameras, lidar, and radar sensors. The advanced communications systems in these vehicles use cellular networks for streaming infotainment, environment and performance data, and vehicle-to-everything communications. Those working on sensing are looking to communications technologies such as orthogonal frequency-division multiplexing (OFDM) waveforms or multiple-input, multiple-output (MIMO) phased-arrays to help improve their outcomes, while those working on communications see opportunity for more data bandwidth in the vast swaths of radar-allocated spectrum. The extent to which these two traditionally separate functions merge will depend on regulatory and technical factors, but the combination could potentially define 6G communication.


The perpetual demand for more data bandwidth is pushing researchers to explore underutilized spectrum in the sub-THz frequency bands. Frequency bands between 90 GHz and 300 GHz offer many times the amount of spectrum currently used for cellular communications. 3GPP already has identified 21.2 GHz above 100 GHz for possible 6G consideration. Pathloss at higher frequencies—one of the biggest hurdles in moving to sub-THz bands—is potentially mitigated by matching a frequency band’s attenuation properties with appropriate applications (for example, using high-attenuation bands for high-security applications, limiting how far the signal travels). Additionally, the inverse relationship between frequency and antenna size offers one way to overcome pathloss: As frequency increases, antenna geometry and spacing decreases, allowing for more elements, and thus more gain, in the same footprint. While expanding to sub-THz bands may seem premature given the delay in 5G mmWave deployments to date, leading industry and academic researchers are closely exploring it as a means to significantly increase network capacity.


Evolution of MIMO

With potential across many different use cases as well as frequency bands, MIMO continues to build on popular multiantenna techniques. Beamforming is key to overcoming sub-THz pathloss challenges, while multiuser MIMO greatly improves spectral efficiency for the most heavily used sub-8 GHz bands. Distributed MIMO, which disaggregates large antenna arrays into multiple smaller, geographically separated radio heads, is especially interesting for sub-8 GHz frequencies, where antenna size becomes prohibitively large. MIMO’s expansion to include higher system antenna counts for more users, and more precisely directed beam steering, aims to increase cell capacity and provide enhanced location services.

Artificial Intelligence and Machine Learning

The fourth technology sure to play a significant role is artificial intelligence and machine learning (AI/ML). As complexity increases and we seek to squeeze every bit of bandwidth out of the available spectrum, it becomes increasingly difficult to optimize the communications system with traditional signal-processing methods. Machine learning offers one way to deal with this complexity. AI/ML-driven design or adaptation seeking to dynamically optimize link performance could offer improvements through capabilities such as automatic spectrum allocation, beam management, and RF nonideality cancellation. Deploying AI/ML at the application layer can optimize Quality of Service (QoS), which considers application-specific requirements, along with the environment, for factors such as latency or energy efficiency. The availability of big, open datasets for AI/ML wireless communication research and training will play a significant part in 6G development.

The Hunt for the Killer App

While these 6G candidate technologies all offer an array of possibilities, they will inevitably live or die by the business case. It’s expensive to develop and deploy these technologies; billions of investment dollars demand large, forecasted returns, and spawn the age-old question, “What is the killer app?”


Throughout the recent global events, we’ve relied upon connectivity and virtual experiences—and many of us have a newfound appreciation for a reliable, high-speed network. 6G discussions are including social and sustainable goals and “connectivity for all,” in addition to tech buzzwords such as immersive XR and key performance indicators like 1 Tb/s data rates. As we work to continue building out 5G by expanding beyond enhanced mobile broadband, and the definition of 6G begins to coalesce, the answers to these business and social questions may be just as important as the technical ones.