TLDRs;
- Samsung and SK Telecom begin joint development of AI-powered 6G network technologies.
- Partnership focuses on AI-RAN systems to improve speed, reliability, and spectrum efficiency.
- Alliance-approved AI channel estimation could boost cell-edge performance by over 30%.
- New innovations may enter 5G-Advanced networks before full 6G rollout.
Samsung Electronics and SK Telecom have entered a major new partnership aimed at accelerating the development of 6G networks powered by artificial intelligence.
As per a Tuesday announcement, the two South Korean technology leaders signed a fresh memorandum of understanding (MOU) outlining a multi-year plan to jointly design, test, and refine next-generation radio access network (RAN) technologies built around advanced AI systems.
The deal marks one of the most coordinated commercial pushes yet toward AI-driven 6G, positioning Korea at the center of the global race to build more intelligent, ultra-efficient mobile networks. With global data usage surging and telecom operators seeking more adaptable infrastructure, the timing reflects an industry-wide shift toward AI-native network architectures.
AI-RAN at the Core of the Partnership
Central to the collaboration is the development of AI-based channel estimation, an emerging technique that uses machine learning models to interpret wireless signals with far greater precision than today’s rules-based systems.
Traditional channel estimation often struggles in low-signal environments, especially at the edges of a cell tower’s coverage. Early lab simulations suggest that AI-driven methods could boost throughput by as much as 30% in these challenging zones.
The companies will also explore distributed multiple-input multiple-output (MIMO) transmission, a method that uses large numbers of antennas to maintain fast data speeds across variable environments. This will be paired with AI-guided RAN schedulers designed to allocate network resources more efficiently in real time, especially in high-demand urban zones.
Beyond incremental improvements, both teams plan to experiment with entirely new RAN designs optimized for AI-first operation. This includes overhauling existing network architectures to support far heavier AI workloads, from inference at the edge to in-network learning.
Industry Backing Strengthens Momentum
Samsung and SK Telecom’s proposed AI channel estimation framework was recently accepted as an official work item within the AI-RAN Alliance, a fast-growing industry consortium dedicated to advancing the use of AI in telecom networks.
The approval helps establish clear milestones, technical benchmarks, and development guidelines, giving the technology a formal pathway toward commercial adoption.
Within 3GPP, the global standards body overseeing mobile communication protocols, the work aligns with Release 18–19 initiatives that aim to bring machine learning deeper into 5G-Advanced and eventually 6G systems. Experts suggest that some AI-RAN features may enter operator networks even before 6G arrives, offering real-world validation and accelerating rollout timelines.
Opportunities for Broader Industry Players
The collaboration also opens the door for a wide ecosystem of hardware and software vendors. As operators like SK Telecom and SoftBank push AI-driven RAN technologies into field testing, suppliers of edge accelerators, model-training tools, networking silicon, and test equipment are finding new opportunities to collaborate.
GPU-based platforms offer strong performance but consume significant power, while CPU-based solutions with custom silicon promise better efficiency and flexibility, creating multiple pathways for innovation. Semiconductor makers, including those already integrating AI/ML accelerators into telecom chipsets, may play an increasingly critical role in bringing these new 6G capabilities to life.
The rapid expansion of the AI-RAN Alliance, growing from just 11 members to more than 80 in a year, highlights the rising commercial interest across the sector. Open-source tooling is also leveling the playing field, allowing third-party developers to build new models for functions such as beamforming, interference mitigation, and channel optimization.
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