"No strain even with baseball stadium crowds"…KT and Samsung Electronics improve base station load by up to 34% using AI

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KT, in partnership with Samsung Electronics, has successfully verified next-generation AI-based wireless network optimization technology at a baseball stadium where large crowds gather. The technology is highly regarded for dramatically enhancing network stability by automatically dispersing data traffic that had been concentrated on specific base stations to surrounding areas.

On the 2nd, KT announced that it completed on-site verification of its "autonomous wireless network operation technology" utilizing a virtual network platform called "AI Cell Twin" at Suwon KT Wiz Park.

The verification was conducted over approximately three months starting from last July at a baseball stadium hosting actual home games. Baseball stadiums, where data traffic fluctuates sharply depending on spectator entry and exit times or game situations, are considered the most challenging environment for testing network optimization technology.

The results of the verification were powerful. As traffic that had been excessively concentrated on specific base stations was smoothly dispersed to surrounding base stations, traffic imbalance between base stations improved by up to 34%, and load per base station decreased by up to 16%. The predictions made by AI Cell Twin in the virtual space also showed high accuracy, perfectly matching actual wireless network data.

The "autonomous wireless network operation technology" introduced this time differs from conventional simple automation technologies. In the past, base stations were controlled based on pre-set criteria or single metrics alone, but this new technology allows AI to comprehensively analyze real-time user distribution, mobile usage patterns, network congestion levels, and customer-perceived quality to independently find the optimal operation plan.

The "AI Cell Twin," which played a key role in this process, is a "network digital twin platform" that replicates the actual wireless network environment in a virtual space. By arbitrarily setting and pre-testing various traffic change scenarios within the virtual environment, it enabled advanced verification to safely apply the optimal solutions derived by AI to the actual base station network in advance.

The two companies plan to continue demonstration work during this autumn baseball season while expanding the scope of technology application beyond large complex facilities like baseball stadiums to various high-density traffic environments such as urban areas and large-scale festival sites.

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*This content was translated by AI.View Original