Samsung is positioning itself at the center of the 6G revolution with AI-powered radio access networks that promise to slash energy costs while delivering personalized connectivity. In an exclusive interview, Charlie Zhang, Senior VP of Samsung's 6G Research Team, reveals how the company's AI-RAN technology is already proving its worth through real-world demonstrations at MWC 2025, setting the stage for next-generation network dominance.
Samsung just dropped a major signal about the future of wireless networks. The company's 6G research chief, Charlie Zhang, is revealing how artificial intelligence isn't just enhancing current networks - it's completely rewriting the playbook for next-generation communications.
The Korean tech giant has been quietly building its 6G arsenal since 2020, and now the results are starting to show. At MWC 2025, Samsung demonstrated its AI-RAN technology improving resource utilization even in the noisiest, most interference-heavy environments - proving this isn't just theoretical research anymore.
"End users now prioritize reliable connectivity and longer battery life over raw performance metrics such as data rates and latency," Zhang told Samsung Newsroom. "The focus has shifted beyond technical specifications to overall user experience."
This shift in thinking reflects a broader industry awakening. While competitors chase headline-grabbing speed numbers, Samsung's betting on something more fundamental: networks that actually work better for real people in real situations. The company's "AI-Native & Sustainable Communication" white paper, published in February 2025, outlines four core directions that go far beyond traditional performance metrics.
The technical breakthrough centers on AI-RAN - artificial intelligence embedded directly into radio access networks, the core infrastructure that connects our devices to the broader internet. Traditional RAN systems rely on dedicated hardware that's expensive to maintain and slow to adapt. Samsung's approach flips this model entirely.
"With AI-based channel estimation, we can accurately predict and estimate dynamic channel characteristics that are corrupted by noise and interference," Zhang explained in the interview. "This higher accuracy leads to more efficient resource utilization and overall network performance gains."
