Incheon National University develops advanced communication technology for faster, reliable 5G and 6G networks

As 5G and 6G networks expand, they promise a future of incredibly fast and reliable wireless connections. A key technology behind this is "millimeter-wave" (mmWave), which uses very high-frequency radio waves to transmit huge amounts of data. To make the most of mmWave, networks use large groups of antennas working together, called "massive Multiple-Input Multiple-Output (MIMO)”.

However, managing these complex antenna systems is challenging. They require precise information about the wireless environments between the base station (like a cell tower) and your device. This information is called "channel state information (CSI)”. The problem is that these signal conditions change rapidly, especially when moving—in a car, train, or even a drone. This rapid change, the "channel aging effect," can cause errors and disrupt your connection.

In this view, a team of researchers at Incheon National University led by Associate Professor Byungju have developed a new AI-powered solution. Their method, called “transformer-assisted parametric CSI feedback”, focuses on key aspects of the signal instead of sending all the detailed information. It concentrates on a few key pieces of information including angles, delays, and signal strength. By focusing on these key parameters, the system significantly reduces the amount of information that needs to be sent back to the base station. The paper was made available online on October 16, 2024, and published in Volume 23, Issue 12, December 2024 of the journal IEEE Transactions on Wireless Communications.

"To address the rapidly growing data demand in next-generation wireless networks, it is essential to leverage the abundant frequency resource in the mmWave bands. In mmWave systems, fast user movement makes this channel ageing a real problem," explains Prof. Byungju Lee.

The team leveraged artificial intelligence (AI), specifically a transformer model, to analyze and predict signal patterns. Unlike older techniques like CNNs, transformers can track both short- and long-term patterns in signal changes, making real-time adjustments even when users are moving quickly. A key aspect of their approach is prioritizing the most important information—angles and delays—when sending feedback to the base station. This is because these parameters have the biggest impact on the quality of the connection.

Tests showed that their method significantly reduced errors (over 3.5 dB lower error than conventional methods) and improved data reliability, as measured by bit error rate (BER). The solution was also tested in diverse scenarios, from pedestrians walking at 3 km/h to vehicles moving at 60 km/h, and even high-speed environments like highways. In all cases, the method outperformed traditional approaches. 

This breakthrough can provide uninterrupted internet to passengers on high-speed trains, enable seamless communication in remote areas via satellites, and enhance connectivity during disasters when traditional networks might fail. It is also poised to benefit emerging technologies like vehicle-to-everything (V2X) communications and maritime networks. “Our method ensures precise beamforming, which allows signals to connect seamlessly with devices, even when users are in motion,” says Prof. Lee.

This innovative method sets a new benchmark for wireless communication, ensuring the reliability and speed required for next-generation networks.

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Reference

Authors: Hyungyu Ju¹, Seokhyun Jeong¹, Seungnyun Kim², Byungju Lee³, Byonghyo Shim¹

Title of original paper: Transformer-Assisted Parametric CSI Feedback for mmWave Massive MIMO Systems

Journal: IEEE Transactions on Wireless Communications

DOI:       10.1109/TWC.2024.3476474

Affiliations:        

¹Institute of New Media and Communications, Seoul National University, Seoul, Republic of Korea

²Laboratory for Information and Decision Systems (LIDS), Massachusetts Institute of Technology, Cambridge, MA, USA

³Department of Information and Telecommunication Engineering, Incheon National University, Incheon, Republic of Korea
 

About Incheon National University

Incheon National University (INU) is a comprehensive, student-focused university. It was founded in 1979 and given university status in 1988. One of the largest universities in South Korea, it houses nearly 14,000 students and 500 faculty members. In 2010, INU merged with Incheon City College to expand capacity and open more curricula. With its commitment to academic excellence and an unrelenting devotion to innovative research, INU offers its students real-world internship experiences. INU not only focuses on studying and learning but also strives to provide a supportive environment for students to follow their passion, grow, and, as their slogan says, be INspired.

Website: https://www.inu.ac.kr/sites/inuengl/index.do?epTicket=LOG

About Associate Professor Byungju Lee 

Dr. Byungju Lee is currently an Associate Professor with the Department of Information and Telecommunication Engineering, Incheon National University, Incheon, South Korea. His research interests include the physical layer system design of the future wireless communications, such as integrated terrestrial and non-terrestrial networks and machine learning for wireless networks. Prof. Lee was awarded the 2020 Fred W. Ellersick Prize from the IEEE Communications Society co-recipient of the Bronze Prize in Samsung Best Paper Award Contest in 2018 and announced as a Qualcomm Fellowship Awardee in 2010.