SK Telecom and Samsung have partnered to bring AI-driven enhancements to 5G networks, with a focus on boosting the performance of individual base stations. Engineers from both companies spent nearly a year developing an advanced, deep-learning AI system that automatically recommends the best settings for various base station environments.
“This is a meaningful achievement that has confirmed that the potential performance of individual base stations can be maximized by incorporating AI,” said Ryu Tak-ki, head of SK Telecom’s infrastructure technology division.
Named the AI-RAN Parameter Recommender, this system has already been tested on SK Telecom’s commercial network. The goal is to address the natural fluctuations in wireless conditions caused by different base station locations and surrounding infrastructure. These factors often lead to inconsistent 5G service quality across areas, even when using the same type of equipment.
To tackle these challenges, SK Telecom developed a deep learning model that analyzes how wireless network data interacts with AI-driven settings. This setup allows the AI to predict changes in wireless conditions and automatically adjust parameters to improve user experience. Samsung brought in its own Network Parameter Optimization AI Model to further refine these adjustments, making the system more responsive to shifts in the wireless environment.
With these combined efforts, the AI system can now predict different wireless conditions and autonomously optimize settings at each base station, improving 5G quality and adaptability across locations. “AI is a key technology for innovation in various industrial fields, and it is also playing a decisive role in the evolution to next-generation networks,” said Choi Sung-hyun, head of the advanced development team in Samsung Electronics’ network business division. “Samsung Electronics will continue to take the lead in developing intelligent and automated technologies for AI-based next-generation networks.”
Beyond this project, SK Telecom is investing in further AI-driven developments for its network, such as systems that automatically adjust base station power and future beamforming capabilities, which aim signals more precisely for stronger, more reliable connections.
“We will accelerate the evolution into an AI-Native Network that provides differentiated customer experiences through the convergence of telecommunications and AI technologies,” Ryu added.
