In modern telecommunications networks, resources are incredibly valuable. To meet the demands of burgeoning network traffic and the diverse requirements of various services, it is essential to manage and optimize these resources effectively. Our lab is developing advanced mathematical optimization techniques and algorithms to solve these challenges, aiming to maximize network performance and minimize costs.
Artificial intelligence (AI) holds significant potential to enhance the efficiency of wireless networks. Our lab is exploring the application of machine learning models to various aspects, including processing wireless signals, predicting network traffic, and detecting failures. Through this research, we aim to realize automation and optimization of wireless systems, improving both their reliability and efficiency.
Open RAN technology focuses on standardizing and ensuring interoperability among different components of telecommunications networks. By adopting Open RAN, networks can become more flexible and cost-effective, as equipment from various vendors becomes compatible. Our lab is pursuing international collaborations to implement and apply Open RAN technologies.
The telecommunications industry is undergoing a significant transformation, driven by the need for greater agility and scalability. To address the surging network traffic and the varied demands of modern services, adopting cutting-edge solutions is imperative. Our lab is at the forefront of developing Cloud Native Radio Access Network (RAN) technologies. These innovations harness the power of cloud-native principles to enhance flexibility, optimize resource utilization, and reduce operational costs. Through these advanced techniques, we aim to maximize network performance, ensure reliability, and facilitate rapid deployment of new services.