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| Ç¥ÁØÁ¾·ù | Á¤º¸Åë½Å±â¼úº¸°í¼(TTAR) | ||||||||||||||||
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| Ç¥ÁعøÈ£ | TTAR-06.0305 | ±¸ Ç¥ÁعøÈ£ | |||||||||||||||
| Á¦°³Á¤ÀÏ | 2025-10-22 | ÃÑ ÆäÀÌÁö | 17 | ||||||||||||||
| ÇÑ±Û Ç¥Áظí | ¿ÀÇ·£ Áö´ÉÇü Á¦¾î¸¦ À§ÇÑ ´ë±Ô¸ð AI ¸ðµ¨ Àû¿ë ¹æ¾È (±â¼úº¸°í¼) | ||||||||||||||||
| ¿µ¹® Ç¥Áظí | Deployment of Large AI Models for RAN Intelligent Control in O-RAN Architecture (Technical Report) | ||||||||||||||||
| ÇÑ±Û ³»¿ë¿ä¾à | ÀÌ ±â¼úº¸°í¼´Â ¿ÀÇ·£(O-RAN) Ç¥ÁØ ±¸Á¶ ÇÏ¿¡¼ÀÇ ´ë±Ô¸ð ÀΰøÁö´É ¸ðµ¨(LAMs)À» Ȱ¿ëÇÑ Áö´ÉÇü ¹«¼± ³×Æ®¿öÅ© Á¦¾î ¹æ¾ÈÀ» Á¦½ÃÇÑ´Ù. O-RANÀº °èÃþÀû ±¸Á¶ÀÇ Non-RT RIC(Non-Real Time RAN Intelligent Controller)¿Í Near-RT RIC(Near-Real Time RAN Intelligent Controller)¸¦ ÅëÇØ ³×Æ®¿öÅ© Á¦¾î¸¦ ¼öÇàÇϸç, °¢ °èÃþÀº rApp°ú xAppÀ» ÅëÇØ »óÀ§ ³×Æ®¿öÅ© °ü¸® Á¤Ã¥ ¼ö¸³°ú Áؽǽð£ Á¦¾î¸¦ ´ã´çÇÑ´Ù.
º» º¸°í¼´Â O-RAN ALLIANCE Ç¥ÁØÀÇ Æ®·¡ÇÈ ½ºÆ¼¾î¸µ(Traffic Steering) À¯ÁîÄÉÀ̽ºÀÇ ¿öÅ©Ç÷ο츦 ¼Ò°³Çϰí ÇØ´ç RIC¿¡¼ LAMÀÌ µµÀ﵃ ¼ö ÀÖ´Â ¹æ¾ÈÀ» ¼Ò°³ÇÑ´Ù. ¾Æ¿ï·¯, LAMÀÇ Àû¿ë ½Ã Á¦¾î ·çÇÁ ³» ÀÀ´ä ½Ã°£ º¸ÀåÀ» À§ÇÑ ÅäÅ« ó¸® Áö¿¬ÀÇ Á¤·®È¿Í °°Àº ±â¼úÀû °í·Á»çÇ×µµ ÇÔ²² Á¦½ÃÇÑ´Ù. |
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| ¿µ¹® ³»¿ë¿ä¾à |
This technical report presents an intelligent radio network control approach based on large AI models (LAMs) within the framework of the standardized open radio access network (O-RAN) architecture. O-RAN enables hierarchical network control through the non-real-time RAN intelligent controller (Non-RT RIC) and the near-real-time RAN intelligent controller (Near-RT RIC). These layers are responsible for high-level policy management and near-real-time control via rApps and xApps, respectively.
This document introduces the traffic steering use case workflow as defined by the O-RAN ALLIANCE specifications and explores opportunities for integrating LAMs into the RIC architecture. In addition, it also addresses technical considerations such as quantifying token processing delays to ensure response time guarantees within the control loop. |
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| °ü·Ã IPR È®¾à¼ | Á¢¼öµÈ IPR È®¾à¼ ¾øÀ½ | ||||||||||||||||
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