What Is 6G Technology? - MATLAB
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    What Is 6G Technology?

    Research to develop 6G technology is well underway. What is 6G and what are the new technologies powering 6G for new use cases? Watch an overview and learn how engineers can use MATLAB® to jump-start their research and design for 6G networks and systems.

    Published: 16 Oct 2023

    6G research is actively underway as researchers and engineers are creating the next generation of global wireless systems. 6G will provide wireless connectivity that is more ubiquitous, efficient, and immersive than 5G and enable multiple new technologies and use cases. Wireless engineers can use MATLAB and Simulink to begin researching and experimenting with 6G designs.

    In this video, we'll cover four main topics-- what is 6G, which technologies it will power, what new use cases it will enable, and how MATLAB can help with 6G system design. The 6G standard will be specified in the coming years and is expected to be ready by 2030. 6G requirements will first be set by the International Telecommunication Union with their IMT 2030 vision projects. The 3rd Generation Partnership Project will then work on delivering specifications to meet those requirements.

    Since 6G networks can handle high data rates, new applications will be available to end users. To enable all these applications, 6G will use several enabling technologies, including higher frequency bands, such as sub-terahertz, artificial intelligence and machine learning, intelligent reflecting surfaces, non-terrestrial networks, and joint communication and sensing. Let's take a deeper look.

    6G will provide maximum data rates in the order of hundreds of gigabits per second. To achieve this, signal bandwidth will have to increase, higher spectral efficiencies must be attained, and the use of higher frequency bands should be introduced. The main challenge in using higher frequencies is the high attenuation and path loss. Engineers need to use MIMO techniques and accurate channel models in millimeter-wave and sub-terahertz bands.

    Channel models based on ray tracing have already provided good prediction capabilities at millimeter wave and are expected to do the same at higher frequencies. Engineers can apply artificial intelligence, including machine learning, deep learning, or reinforcement learning to configure, optimize, and self-organize 6G wireless communication systems. An AI workflow requires architecting, deep neural networks, and generating vast amounts of data for training them, which, in turn, needs GPU and parallel computing support for efficient training.

    Reconfigurable intelligence surfaces allow us to control the propagation of signals between transmitters and receivers. You can control the surface properties dynamically through an array of reflecting elements. This way, 6G engineers have more flexibility in controlling radio environments and suppression of interference in high-density, urban, outdoor scenarios.

    The present decade is marked by the emergence of non-terrestrial networks. NTNs include commercial drones, HAPS, and low Earth orbit satellites all working together to provide near universal coverage. 6G networks need to accurately localize wireless devices to optimize the transmissions. By introducing new frequencies, wireless networks can furnish highly accurate sensing and yield spatial knowledge of their physical surroundings. This is why 6G will use joint communication and sensing that integrates a wireless network's localization, sensing, and communication functions.

    Building upon MATLAB's 5G solutions, you can explore new 6G frequency ranges, bandwidths, and numerologies. You can scale simulations from MIMO designs and explore higher sampling rates with MATLAB algorithms. MATLAB is equipped with an array of propagation and channel models, including powerful functionality for ray tracing. These functions allow you to add losses due to rain, terrain diffractions, and atmospheric scattering and absorption.

    MATLAB helps you build, model, and visualize complete NTN scenarios consisting of large-scale satellite constellation. MATLAB comes with a large set of executable designs for AI for wireless applications, including CSI feedback, beam selection, digital predistortion, and autoencoders. In MATLAB, you can model and design scattering and intelligent reflecting surfaces.

    All of these MATLAB algorithms come in open, editable, customizable formats, enabling continuous and easy prototyping and testing with hardware connectivity. There is a lot more can do with MATLAB to test what is possible with 6G networks. If you want to learn more, click on the links below.

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