What Is 6G?
6G is the next generation of mobile wireless communication systems, envisioned to provide more inclusive and sustainable wireless connectivity. 6G research and development aims to substantially improve the performance of the current 5G communications systems, with 6G networks operating faster, handling more bandwidth, and operating with lower latencies.
As a result, 6G systems may enable new applications such as virtual and augmented reality (VR/AR), artificial intelligence (AI), connected cars, industries and automation, ubiquitous coverage through non-terrestrial networks (NTN), joint communications and sensing, and low-power wireless communications.
When you are ready to get started with 6G, you can accelerate your 6G system design with MATLAB® and its wireless communications tools.
- Leverage open, editable, and customizable algorithms in MATLAB as a starting point for your 6G design.
- Continuously test your designs with the easy custom waveform generation, hardware connectivity, and AI modeling capabilities in MATLAB.
- Simultaneously optimize the digital, RF, and antenna array components of your 6G systems, enabling you to explore multidimensional design space more effectively.
Each generation of wireless communication standard spans about 10 years before transitioning to the next generation. The 5G standard was first published in 2018 as part of 3GPP Release 15 and is incrementally evolving. For instance, the next 5G standard to be published in 2024 (Release 18) will be known as 5G Advanced. Meanwhile, research and development for next-generation 6G systems is ongoing. Most observers estimate that the standard body ITU (International Telecommunication Union) will publish the IMT-2030 document, setting the vision and requirements for 6G, sometime around 2026. The 3GPP (3rd Generation Partnership Project) standard body will then develop the 6G standard specifications, satisfying those requirements, sometime around 2028 to 2030.
Although 6G systems requirements are not yet finalized, many experts believe that 6G networks will build upon the success of 5G and 5G-Advanced systems, and enable the following new applications:
- Multisensory extended reality and haptics, supporting different devices, higher data rates, and much lower latency
- Volumetric media streaming and telepresence, enabling volumetric content, 3D data sets, and holographic presence
- Connected industries and automation, supporting industrial IoT and massive machine-type communications in areas such as mechanized agriculture and telemedicine
- Autonomous vehicles and swarm systems, enhancing V2X communications, connected cars, drones, and robots
- Extreme coverage and connecting the unconnected, bridging the “digital divide” and connecting people in remote, rural, and underserved areas using non-terrestrial networks (NTN) with satellite communications
- Ultra-low power and zero energy, harvesting energy directly from radio waves and substantially reducing power use in wireless systems
Key Enabling Technologies for 6G
Although the exact specifications of 6G systems are not yet defined, experts believe that the following enabling technologies are responsible for the introduction of new applications and capabilities:
- New frequencies including sub-THz communication
- Artificial intelligence and machine learning
- Reconfigurable intelligent surfaces (RIS)
- Joint communication and sensing
- New digital waveforms
New Frequencies Including Sub-THz Communication
The use of new frequencies in range (from 7–24 GHz) and sub-THz range (larger than 100 GHz) will most likely be part of the 6G communications systems. This in turn will enable new spectrum management methodologies and deliver performance gains in data rate and speed, augmenting 6G network capacity and transmission bandwidths while reducing network interference.
Joint Communication and Sensing
6G will take advantage of the integration of localization and sensing functions of a wireless network with its communication function. This will particularly improve performance in indoor communications scenarios by acquiring and sending better information about the indoor space, range, barriers, and positioning to the network. Also, by introducing new frequencies in the sub-THz spectrum, 6G systems may pave the way for very accurate sensing by leveraging radar-like technologies.
Artificial Intelligence and Machine Learning
Artificial intelligence and machine learning techniques are already included in 5G-Advanced systems. This trend is likely to continue with 6G networks using data-driven AI methodologies to better configure, optimize, and self-organize. The 6G wireless communication standard will support AI-based air interfaces to improve functions such as joint compression and coding, beamforming, channel state information (CSI) compression, and positioning.
Reconfigurable Intelligent Surfaces
6G research may also tap into the potential of reconfigurable intelligent surfaces (RIS), allowing control of the propagation of signals between a transmitter and a receiver dynamically and programmatically. The technology enables the reflection and active steering of incoming signals off surfaces by changing the electric and magnetic properties of their material.
6G Modeling and Simulation with MATLAB
Using MATLAB, 5G Toolbox™, and other wireless communications tools based in MATLAB, you can model and simulate 6G wireless communications systems today and evaluate the impact of their enabling technologies.
- Create and optimize your intellectual property (IP) for 6G using open MATLAB functions and compare your innovations to existing benchmarks.
- Explore 6G waveform generation beyond the parameters allowed in the current 5G standard (with new frequency ranges, bandwidths, numerologies).
- Scale your simulations for massive MIMO, larger bandwidths, and higher sampling rates. Manage large and long-running simulations by distributing them on multiple cores, clusters, or the cloud and by leveraging GPUs.
- Perform faster and more accurate RF component modeling for new mmWave and sub-THz frequencies.
- Simulate propagation loss and channel models in mmWave and sub-THz frequency ranges.
- Model non-terrestrial networks (NTN) by performing end-to-end link-level simulations, scenario modeling, orbit propagation, and visualization.
- Explore RF sensing and detect the presence of events or persons in a scene by analyzing RF waveforms.
- Examine the effect of reconfigurable intelligent surfaces (RIS) on overall system performance.
- Apply artificial intelligence (AI) techniques, including machine learning, deep learning, or reinforcement learning workflows to solve 6G wireless communications problems.