Samsung and Japanese telecommunications operator KDDI have successfully completed an AI-powered network optimization trial on KDDI’s active commercial 5G standalone (SA) network in Japan, per Samsung’s official announcement of the trial completion Samsung’s official trial announcement. The trial tested Samsung’s AI-driven network optimization tool on live carrier infrastructure, rather than a lab or simulated test environment. It validated real-world performance for 5G SA deployments across KDDI’s active service areas in Japan.
What did the Samsung-KDDI AI 5G trial test?
The trial evaluated the AI solution’s performance across three core 5G SA network optimization use cases: real-time coverage adjustment, traffic load balancing across individual cell sites, and dynamic quality of service (QoS) prioritization for end-user devices, per the official Samsung announcement. For example, the real-time coverage adjustment function automatically tunes cell site transmit power to account for shifting environmental conditions, while the dynamic QoS feature prioritizes latency-sensitive traffic such as enterprise private 5G connections during congestion events. The solution automated routine optimization tasks that typically require manual configuration by network engineering teams.
During testing, the tool reduced network optimization time by up to 40% compared to traditional manual processes. The test also confirmed the solution’s compatibility with KDDI’s existing 5G SA core and radio access network (RAN) hardware, with no major infrastructure upgrades required for initial deployment Samsung’s trial performance and compatibility details.
What performance gains did the AI tool deliver?
During the live trial, the AI solution dynamically adjusted network parameters in response to real-time traffic patterns across KDDI’s full 5G SA coverage area in Japan. This dynamic adjustment reduced peak-hour network congestion by 15% and improved overall network capacity for end users during high-traffic periods Samsung’s trial performance metrics.
The successful validation on active commercial infrastructure provides a tested reference for other carriers seeking to deploy AI-powered optimization tools on their own 5G SA networks, with minimal disruption to existing services. Per the official announcement, the trial results confirm the solution is ready for limited commercial deployment scenarios. No full nationwide rollout on KDDI’s network has been announced as part of the trial results Samsung’s commercial deployment guidance.
Why is AI-driven 5G network management valuable for carriers?
5G standalone networks are built to support high-bandwidth, low-latency use cases, including fixed wireless access, enterprise private 5G networks, and mobile edge computing (MEC) deployments. All of these use cases require consistent, adaptive network performance to meet agreed service level agreements (SLAs) for end users, as outlined in Samsung’s trial context documentation Samsung’s 5G SA use case overview.
Traditional manual network optimization is resource-intensive for carriers: teams must adjust parameters for thousands of individual cell sites to account for shifting user demand, physical obstructions, and environmental factors that impact signal performance, per Samsung’s industry context notes Samsung’s manual optimization context.
AI-powered optimization tools like Samsung’s solution aim to reduce this operational overhead by automating parameter adjustments across the entire network in real time, with minimal human oversight. This automation lowers carrier operational expenditure (opex) over time, reducing the cost of maintaining large-scale 5G networks Samsung’s AI optimization value proposition.
