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Tag: 6G

  • Magnetic Gearing Transforms The Yagi–Uda Antenna For 6G

    Magnetic Gearing Transforms The Yagi–Uda Antenna For 6G

    As 6G development accelerates, demand grows for antennas that adapt to changing signals. A key 6G feature is smart beam control, enabling real-time signal optimization for high speed, low latency, and massive connectivity.
    Yagi-Uda antenna. Image Credits: Tohoku University

    As 6G development accelerates, demand grows for antennas that adapt to changing signals. A key 6G feature is smart beam control, enabling real-time signal optimization for high speed, low latency, and massive connectivity.

    Novel Antenna Concept and Underlying Principles

    Researchers from Tohoku University and University of Surrey have created a pattern-reconfigurable Yagi–Uda antenna with a magnetic gear. This design enables accurate beam steering while overcoming many limitations associated with conventional reconfigurable antenna technologies.

    The study was published in IEEE Transactions on Antennas and Propagation.

    Challenges of Existing Reconfigurable Antenna Technologies

    Pattern-reconfigurable antennas are vital for upcoming 6G systems because they can dynamically steer radiation patterns toward specific users or devices. Current methods typically fall into two main categories: electronic and mechanical—each with notable compromises.

    Electronic reconfigurable antennas, which use diodes and bias circuits, enable extremely rapid beam switching within microseconds. However, they often experience high insertion loss, nonlinear effects, and non-reciprocal behavior. Mechanical methods offer linear, reciprocal performance but rely on complex parts prone to friction and wear.

    Operating Principle of the Magnetic Gear–Based Approach

    To address these challenges, the researchers introduced a magnetic gear directly into the antenna architecture. A magnetic gear transfers torque without physical contact by harnessing magnetostatic interactions between arrays of small magnets.

    In the proposed design, the lower section of the magnetic gear is mechanically driven, while the upper section—magnetically coupled—rotates without contact, even across the antenna’s ground plane.

    This contactless design eliminates direct linkage, nearly removing friction and wear. Constant spacing between the magnetic gear components ensures a stable, highly linear magnetostatic force.

    Performance Advantages and Design Enhancements

    This approach enables easy multi-step or even continuous antenna reconfiguration, without the nonlinear effects commonly seen in systems that use electromagnets with adjustable spacing.

    The design also preserves low insertion loss, which is crucial for high-frequency wireless applications. Dielectric losses can be reduced by optimizing the infill density when 3D-printing the magnetic gear frame, while magnetic losses remain minimal as long as the magnets are small relative to the operating wavelength.

    “Integrating a magnetic gear allows for stable, low-loss, and maintenance-free pattern reconfiguration, opening new opportunities for adaptive antennas in future wireless networks,” explains Keisuke Konno, one of the project’s lead researchers.

    Experimental Verification and Link to Yagi–Uda Heritage

    Numerical simulations and experimental tests verified that the proposed antenna achieves the anticipated radiation performance and clearly outperforms traditional reconfigurable antennas.

    The design draws on a long history of innovation. The Yagi–Uda antenna, one of the most widely used directional antennas globally, was first developed in the 1920s at Tohoku University by Shintaro Uda alongside Hidetsugu Yagi.

    By integrating this classic antenna design with modern magnetic-gear technology, the team has established a versatile new platform for next-generation wireless communications.

    Read the original article on: Tech Xplore

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  • Speeds On This New 6G Chip are Ten Times Those Of 5G

    Speeds On This New 6G Chip are Ten Times Those Of 5G

    Chinese and American engineers have unveiled a 6G chip capable of reaching speeds beyond 100 Gbps, which is roughly 10 times faster than 5G's maximum potential and about 500 times quicker than current average 5G speeds.
    Image Credits: (Eugene Mymrin/Moment/Getty Images)

    Chinese and American engineers have unveiled a 6G chip capable of reaching speeds beyond 100 Gbps, which is roughly 10 times faster than 5G‘s maximum potential and about 500 times quicker than current average 5G speeds.

    While the deployment of 6G networks is not anticipated before the 2030s, the industry must establish the foundational work now.

    A Single Chip Spanning 0.5 to 115 GHz

    Scientists from Peking University, the City University of Hong Kong, and the University of California, Santa Barbara, have developed a new, highly efficient chip that achieves speeds previously only seen in a few prototypes.

    Despite its tiny size of 11 by 1.7 millimeters, the chip operates across an ultrabroadband frequency range from 0.5 GHz to 115 GHz. This feat requires it to cover nine different radio bands, a task that typically demands a wider array of components.

    Image Credits: Diagrams of the new chip. (Tao et al., Nature, 2025)

    Transforming Radio to Light for 100+ Gbps Speeds, Far Beyond 5G’s Limits

    This process uses an electro-optic modulator to transform radio signals into light. Conversely, optoelectronic oscillators on the chip produce ultra-wideband radio frequencies.

    This enables the new chip to achieve speeds exceeding 100 Gbps. In contrast, while 5G’s theoretical maximum is 10 Gbps, its real-world performance is significantly slower, with U.S. providers typically offering average speeds of just 150 to 300 Mbps.

    Though significant infrastructure development remains, 6G is inevitable. Experts expect this technology to arrive within the next decade to meet our soaring data demands, driven by UHD streaming and the pervasive integration of AI.

    Read the original article on: Sciencealert

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  • Photonic Processor may Streamline 6G Signal Processing

    Photonic Processor may Streamline 6G Signal Processing

    With more connected devices requiring greater bandwidth for activities like teleworking and cloud computing, managing the limited wireless spectrum available to all users will become increasingly difficult.
    Image Credits: Pixabay

    With more connected devices requiring greater bandwidth for activities like teleworking and cloud computing, managing the limited wireless spectrum available to all users will become increasingly difficult.

    Engineers are turning to artificial intelligence to manage wireless spectrum more efficiently, aiming to reduce latency and enhance performance. However, most AI techniques used to classify and process wireless signals consume significant power and struggle to operate in real time.

    MIT Unveils Ultrafast Optical AI Chip for Wireless Signal Processing

    To address this, MIT researchers have developed a new AI hardware accelerator tailored for wireless signal processing. Their optical processor uses light to carry out machine learning tasks, enabling it to classify wireless signals within nanoseconds. The study is published in Science Advances.

    This photonic chip is roughly 100 times faster than leading digital alternatives and achieves about 95% accuracy in signal classification. It’s also scalable and adaptable, making it suitable for a range of high-performance computing tasks—while being more compact, lightweight, cost-effective, and energy-efficient than traditional digital AI accelerators.

    The device holds strong potential for future 6G applications, such as cognitive radios that can boost data rates by adjusting wireless modulation formats based on real-time environmental conditions.

    Expanding Applications Beyond Signal Processing

    By allowing edge devices to run deep-learning computations instantly, this new hardware accelerator could significantly accelerate tasks far beyond signal processing. For example, it could enable autonomous vehicles to respond instantly to environmental shifts or allow smart pacemakers to continuously track and assess a patient’s heart health.

    “There are many applications that could benefit from edge devices capable of analyzing wireless signals,” says Dirk Englund, professor in MIT’s Department of Electrical Engineering and Computer Science, and senior author of the paper. “What we’ve introduced could pave the way for real-time, dependable AI inference. This is just the beginning of something with far-reaching impact.”

    Collaborative Effort Behind the Breakthrough Optical AI Research

    Englund co-authored the paper with lead author Ronald Davis III, Ph.D.; Zaijun Chen, former MIT postdoc and now assistant professor at the University of Southern California; and Ryan Hamerly, visiting scientist at MIT’s Research Laboratory of Electronics (RLE) and senior scientist at NTT Research.

    Current digital AI accelerators for wireless signal processing typically convert signals into images and process them through deep-learning models for classification. While this method delivers high accuracy, the heavy computational demands of deep neural networks make it unsuitable for time-critical applications.

    Optical systems offer a faster, more energy-efficient alternative by using light to encode and process data. However, general-purpose optical neural networks have struggled to achieve high performance in signal processing while remaining scalable.

    A Tailored Optical Neural Network for Signal Processing

    To address this, the researchers developed a specialized optical neural network architecture for signal processing, named the multiplicative analog frequency transform optical neural network (MAFT-ONN).

    MAFT-ONN solves scalability challenges by encoding all signal data and conducting machine-learning operations entirely in the frequency domain—prior to digitizing the wireless signals.

    The team designed the network to carry out both linear and nonlinear operations directly within the optical pathway, which are essential for deep learning. This approach allows them to use just one MAFT-ONN device per network layer, unlike other techniques that require separate devices for each neuron.

    “With this method, we can pack 10,000 neurons onto a single device and perform all the necessary multiplications in one step,” explains Davis.

    Photoelectric Multiplication Powers Efficiency and Scalability

    They achieve this efficiency through photoelectric multiplication, a technique that significantly enhances performance. It also enables easy scaling of the optical neural network by adding more layers without additional complexity.

    MAFT-ONN processes incoming wireless signals by analyzing their data and passing the results to the edge device for further tasks. For example, by identifying a signal’s modulation type, MAFT-ONN allows the device to recognize the signal format and extract the embedded information.

    A major challenge in developing MAFT-ONN was figuring out how to translate machine-learning computations onto optical hardware.

    Customizing Machine Learning to Harness Optical Hardware

    “We couldn’t just apply a standard machine-learning framework—we had to tailor it specifically to our hardware and find ways to leverage the underlying physics to perform the desired computations,” explains Davis.

    When tested through simulations for signal classification, the optical neural network achieved 85% accuracy in a single measurement and could quickly reach over 99% accuracy with multiple measurements. MAFT-ONN completed the entire classification process in just 120 nanoseconds.

    “The more you measure, the more accurate it becomes. Since MAFT-ONN performs inference in nanoseconds, you gain accuracy without sacrificing speed,” Davis adds.

    While leading digital RF systems handle machine-learning inference in microseconds, optical systems can achieve it in nanoseconds—or even faster.

    Looking ahead, the team aims to implement multiplexing strategies to increase the processing capacity and scale of MAFT-ONN. They also plan to expand the architecture to support more advanced deep learning models, such as transformers and large language models (LLMs).

    Read the original article on: Techxplore

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  • Space-Time-Coding Metasurface Enhances 6G Wireless Networks

    Space-Time-Coding Metasurface Enhances 6G Wireless Networks

    Left: A conceptual illustration of the system. Right: Experimental results demonstrating the system’s

    Programmable metasurfaces (PMs), also known as reconfigurable intelligent surfaces, not only reflect wireless signals but also dynamically control electromagnetic waves in real time. These smart surfaces are crucial for advancing sensing technologies and next-generation wireless communication systems.

    Researchers from Southeast University, the University of Sannio, and Université Paris-Saclay-CNRS demonstrated that a specific PM, called a space-time-coding metasurface, can simultaneously support both sensing and communication. Their study, published in Nature Communications, introduces two integrated sensing and communication (ISAC) schemes leveraging this technology.

    “As we enter the 6G era, networks must do more than just transmit data—they must interact with and adapt to their environment,” said senior author Tie Jun Cui. Motivated by this vision, the team developed a PM that enables high-speed communication while sensing its surroundings in real time.

    Space-Time-Coding Metasurface: A Programmable Solution for Dynamic Signal Control

    Experimental setup for measurements on a moving transmitting antenna. Credit: Adapted from Chen et al., Nature Communications 16, 1836 (2025), under CC BY-NC-ND 4.0.

    At the heart of their system is a space-time-coding metasurface, a programmable surface that actively manipulates reflected signals. Unlike conventional mirrors that simply bounce back light, this surface adjusts electromagnetic wave propagation using embedded diodes that switch on and off dynamically. Notably, it supports both the original signal frequency and additional harmonics, allowing precise control.

    This dual functionality enables stable connectivity while tracking movement, detecting objects, and responding to environmental changes. To test its capabilities, the researchers built a microwave-frequency prototype (10.3 GHz), which successfully demonstrated real-time sensing and communication.

    “Our prototype adapts to moving users, stabilizes connections, and accurately detects obstacles,” Cui explained. “This approach could simplify mobile networks, reduce costs, optimize spectrum use, and improve sustainability.”

    Their breakthrough paves the way for future smart environments, with applications in smart cities, home security, industrial robotics, and autonomous vehicles. Moving forward, the team aims to integrate artificial intelligence for real-time decision-making and enhance security to ensure reliable and protected operation. Ultimately, they envision intelligent spaces that seamlessly adapt to user needs, making homes and cities more connected, responsive, and efficient.

    Read Original Article: TechXplore

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  • The World´s First 6G Technology From Japan

    The World´s First 6G Technology From Japan

    Credit: Canvas

    The network is capable of transmitting five HD movies per second and has the potential to revolutionize telecommunications, offering applications ranging from ultra-HD streaming to real-time communication.

    Telecommunications Companies


    Japanese telecommunications companies, including DOCOMO, NTT Corporation, NEC Corporation and Fujitsu, have announced the development of a 6G wireless device that promises to be 20 times faster than the 5G network.

    According to the Engineering Today website, this new device reaches an “impressive speed” of 100 gigabits per second (Gbps) and can operate at distances of up to 100 meters.

    Furthermore, it continues, the great innovation of 6G lies in the use of the so-called “sub-terahertz” bands, which vary between 100 and 300 gigahertz (GHz), considerably higher than those used in 5G, which normally do not exceed 40 GHz.

    “With the ability to transmit five HD movies per second, 6G has the potential to revolutionize telecommunications, offering applications ranging from ultra-HD streaming to real-time communication in autonomous vehicles, satisfying a growing demand for faster data and connectivity” .

    The companies announcing the world’s first 6G reveal that the challenge now is to develop new devices that work efficiently in these higher bands, as they require completely different technologies from those used today.

    According to the website, each of the companies involved has brought its expertise to overcome the technical challenges and advance the development of 6G. For example, DOCOMO worked on developing wireless systems for the 100 GHz band, managing to transmit data at 100 Gbps for up to 100 meters; NTT focused on the 300 GHz band, creating a device capable of simulating performance over the same distance; NEC developed a complex active phased array antenna with more than 100 elements, essential for operation in the 100 GHz band; Fujitsu innovated in compound semiconductor technologies, increasing efficiency and signal amplification capacity at the high frequencies involved.

    Announcement Contradicts China’s Prediction

    According to a report published on June 23, 22, by the Techtudo website, China Mobile, the world’s largest telephone operator, released a technical study that suggested the architecture and design of the 6G network.

    China’s forecasts pointed to gains of up to a hundred times compared to the current 5G, as well as greater reliability, with the implementation of the 6G network. However, the Japanese companies’ forecasts are the opposite.

    By 2022, according to the news report, China would be leading the race to develop the 6G network, even with huge investments from companies in South Korea, the United States and Japan

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