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AI Model Developed to Enhance Efficiency of Mobile Networks

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TL;DR

    • AI-driven model slashes telecom network resource usage by up to 76%.

    • Dynamic adaptation to demand boosts network efficiency and sustainability.

    • AI innovation extends beyond telecom, shaping a more efficient future.

Researchers at the University of Surrey have developed a new artificial intelligence (AI) model that could significantly improve the efficiency of the UK’s telecommunications network. This innovative model has the potential to save up to 76% in network resources compared to existing Open Radio Access Network (O-RAN) systems while also contributing to the environmental sustainability of mobile networks by reducing energy consumption. In a recent study published in the IEEE Transactions on Network Service Management, the Surrey researchers unveiled their groundbreaking approach to optimizing bandwidth allocation using mathematical modeling and AI.

Enhancing network efficiency with AI

Esmaeil Amiri, who led the research at the University of Surrey, explained the significance of their model by stating, “Our model shows that by using AI, telecommunications providers could use their bandwidth far more efficiently, with only a small additional computational cost.” The researchers achieved this remarkable improvement in bandwidth capacity with minimal computational overhead compared to other O-RAN systems. This breakthrough could lead to substantial cost savings for telecommunications companies and pave the way for more efficient and eco-friendly mobile networks.

Dynamic adaptation to changing demand

One of the key advantages of the AI-based solution developed by the Surrey team is its ability to dynamically adapt to changes in network demand. Unlike traditional approaches that require extensive reconfiguration of the network, this solution can efficiently allocate computing power in response to fluctuating demand. Professor Ning Wang, a co-author of the study and Professor in Networks at the University of Surrey, noted, “This solution can dynamically adapt to changes in demand, yet with significantly reduced necessity of reconfiguring the network. This could make our communications networks more robust and more efficient.”

Broad applications beyond telecommunications

While the primary focus of this research is on enhancing telecommunications networks, the underlying AI model holds promise for a wide range of applications. Professor Wang emphasized that this innovative solution could be adapted to various scenarios, such as optimizing battery usage for drones or reducing latency in remote surgical procedures. The flexibility of the model opens the door to a multitude of possibilities for improving efficiency and performance in diverse fields.

Transforming telecom operations with O-RANs

Open Radio Access Networks (O-RANs) have revolutionized the operations of telecom providers by enabling the flexible allocation of computing power across their networks. This dynamic adjustment of resources allows telecom companies to respond swiftly to changing demand without the need for extensive hardware reconfiguration. However, existing O-RAN technology still faces challenges when it comes to rapidly adapting to network demand fluctuations.

A potential path to greater efficiency

The University of Surrey researchers believe that their findings could empower telecom providers to further enhance the efficiency of their networks. By implementing the AI-based solution, these providers could not only bolster the resilience of their systems but also reduce energy consumption, contributing to a more sustainable future. The potential benefits extend beyond telecommunications, impacting various industries where resource optimization is critical.

Moving toward implementation

The proposed AI-based scheme is poised to undergo further testing and development in the HiperRAN Project. In collaboration with industry partners, the Surrey team aims to bring this technology closer to being ready for widespread adoption. Dr. Mohammad Shojafar, another co-author of the study and Senior Lecturer at the University of Surrey, stated, “This solution aims to design intelligent, robust applications for traffic demands on Open RAN, a prominent next-generation telecom network. This research could be implemented easily, helping shape the next generation of telecommunications networks.”

the University of Surrey’s AI-driven approach to optimizing network efficiency offers a promising solution for the telecommunications industry and beyond. With the potential to save significant resources and reduce energy consumption, this innovation could lead to more resilient and sustainable networks, transforming the way we connect and communicate in the future. As the HiperRAN Project advances, we may soon witness the practical implementation of this groundbreaking technology, ushering in a new era of telecommunications.

Disclaimer. The information provided is not trading advice. Cryptopolitan.com holds no liability for any investments made based on the information provided on this page. We strongly recommend independent research and/or consultation with a qualified professional before making any investment decisions.

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John Palmer

John Palmer is an enthusiastic crypto writer with an interest in Bitcoin, Blockchain, and technical analysis. With a focus on daily market analysis, his research helps traders and investors alike. His particular interest in digital wallets and blockchain aids his audience.

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