How to improve the efficiency of 5G to benefit next-generation wireless networks
Wireless systems are enabling increasingly complex functions in industrial, business, healthcare and personal settings, requiring stronger coverage and signal quality for better performance.
Many countries have already deployed 5G networks, but these networks continue to present several shortcomings. Modern 5G operates in millimeter-wave, a range of electromagnetic frequencies which offers large bandwidth and high frequency. However, the high frequency also makes signals more susceptible to penetration loss and path loss, resulting in reduced communication coverage.
Several researchers including Dr. Jiguang He, a team member in the Digital Research Center at the Technology Innovation Institute (TII) who focuses on wireless communications, are already working on next-generation wireless systems, which are promising to be faster and more reliable.
They have recently come out with a new paper, Hashing Beam Training for Near-Field Communications, which explains ways to enhance the quality and reliability of high-frequency wireless communications by optimizing how devices align their antennas to send and receive signals.
Solutions to 5G shortcomings
5G’s shortcomings can be addressed by increasing beamforming?the technique used to focus a beam, or signal path, in a specific direction to enhance a connection’s speed and reliability. This can already be done thanks to the development of a technology called massive multiple-input multiple-output (MIMO), which is a large-scale antenna array using multiple transmitters and receivers that can transfer more data at the same time.?
Millimeter wave MIMO communication has shown great promise for 5G. However, the widespread deployment of millimeter wave MIMO systems has been hindered by high costs, implementation complexity, significant power consumption, and limited coverage.?
To simplify implementation and improve efficiency, beam training, which is a process where devices test different directions and shapes of beams to find the best signal, must be enhanced. Beam training is critical for future 6G systems operating at higher frequencies.?
It’s possible to enhance beam training by introducing the use of hashing functions to design multi-arm beams, which are systematically traversed during beam training. In essence, hashing functions work like sophisticated sorting algorithms that help streamline the process of beam selection.?
What’s interesting is that this approach reduced the beam training overhead while maintaining performance. By enhancing beam training efficiency while reducing its complexity, Dr. He and his peers have demonstrated that we can save time for data transfer, thereby improving network throughput.
The research encountered positive feedback from the research community and received the Best Paper Award at IEEE International Conference on Communications 2024. Such a recognition is a momentous achievement for many reasons.?
Practical implications
Millimeter wave MIMO systems can be viable for large-scale deployment, especially in densely populated urban areas. This new research is paving the way for future advanced and efficient wireless communication networks and it’s a promising development for the deployment and commercialization of next-generation wireless systems such as Beyond 5G and 6G MIMO.
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This breakthrough is essential for high-definition video streaming on a personal mobile phone, which will become smoother. It will enable autonomous driving, industrial Internet of Things, and telemedicine, which all require extremely high data rates and ultra-low latency connectivity.?
These techniques will one day also be applied in areas like autonomous systems and industrial automation, where efficient communication is crucial. These projects promise to deliver innovative solutions with significant societal and industrial impact.
These practical implications strongly resonate with the works of? TII, and the work of Dr. He and his peers will significantly contribute to the enhancement of the global competitiveness of the United Arab Emirates in advanced technology sectors.
UAE’s competitiveness in telecommunications
This new research on enhancing beam training efficiency in B5G and 6G systems aligns with TII’s goal of fostering innovation and promoting a robust research and development environment. It also fosters technological innovation and competitiveness in the telecommunications sector.
This is only the beginning. In the short term, TII’s DSRC aims to integrate this technique into its reconfigurable intelligent surface (RIS) platform to validate its effectiveness in practical applications.?
TII is working with several leading universities, such as Zhejiang University and Khalifa University, and research institutions to explore new applications of these methods in advanced communication systems.?
Going forward, the hope is that these findings will serve as the basis for further research focusing on beam training that will continue to enhance its efficiency and performance and contribute to next-generation wireless networks as we transition toward 6G and beyond. For example, future work focused on further enhancing the efficiency and accuracy of beam training could integrate it with advanced technology such as AI and machine learning.
Ultimately, Dr. He’s work will have a tangible impact on the advancement of wireless communication technologies and contribute to TII’s overarching vision of positioning the UAE as a global leader in innovation and technology.
Check out Dr. Jiguang He’s research paper:?
Hashing Beam Training for Near-Field Communications, also by Yuan Xu ,?Li Wei ,?Chongwen Huang ,?Chen Zhu ,?Zhaohui Yang ,?Jun Yang ,?Jiguang He ,?Zhaoyang Zhang ,?Mérouane Debbah
Telecom Director at Technology Innovation Institute-TII
4 个月Well done !! and more will come.
R&D Director in BaseBIt (AI & Privacy Computing)
4 个月Thanks for sharing
5G L1 Integration engineer at Nokia and Researcher PHD Student (5G, 6G, URLLC, MTC, IoT)
4 个月congratulations
AI/ML | Advertising Systems | Recommender Systems | Speech Processing | Distributed Systems | Time Series Analysis | Chatbot | NLP | CV
4 个月Congrats Jiguang He