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The AI-native RAN: A Framework for Telecoms Operators and Vendors

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  • AI ³×ÀÌÆ¼ºê RANÀ̶õ ¹«¾ùÀ̸ç, ±× äÅÃÀÇ ¿øµ¿·ÂÀº ¹«¾ùÀΰ¡?
  • AI ³×ÀÌÆ¼ºê RANÀÇ ÁÖ¿ä ¿ä¼Ò
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  • ¾î¶² º¥´õ ¹× ±âŸ ÀÌÇØ°ü°èÀÚµéÀÌ Ç÷§Æû°ú »ýŰ踦 Çü¼ºÇϰí ÀÖÀ¸¸ç, À̵éÀÌ ¹èÆ÷¸¦ °¡¼ÓÈ­ÇÏ´Â µ¥ µµ¿òÀÌ µÇ´Â°¡?
  • ÀÓº£µðµå AI·Î Áö¿øÇÒ ¼ö Àְųª Áö¿øÇØ¾ß ÇÏ´Â RAN ±â´ÉÀº ¹«¾ùÀΰ¡?
  • AI ó¸® ±â´ÉÀº ³×Æ®¿öÅ©ÀÇ ¾îµð¿¡ ¹èÄ¡µÇ¸ç, ¾ÆÅ°ÅØÃ³ÀÇ ÁÖ¿ä °áÁ¤ »çÇ×Àº ¹«¾ùÀΰ¡?
ksm 25.02.17

"The AI-native RAN could transform the economics of mobile networks but challenging decisions must be made now."

AI is beginning to be introduced to the RAN to increase automation and intelligence, but the industry has set out an ambitious vision of an AI-native RAN in which AI can be embedded into every element of the mobile network. This has the potential to transform the challenging economics of 5G, enable new services and improve customer experiences. However, the solutions and ecosystem are nascent, which makes it challenging for telecoms operators to plan their strategies.

This report sets out the main drivers and challenges in the AI-native platform, based on new operator surveys. It creates a taxonomy of the AI-native RAN and maps this against the main active players, including vendors and operators. The framework enables stakeholders to understand their place in the emerging market and identify alliances.

Questions answered:

  • What is the AI-native RAN and what are the drivers for its adoption?
  • What are the main elements of an AI-native RAN? Who is leading the development of these elements and when will they be commercially available?
  • Which vendors and other stakeholders are forming platforms or ecosystems and will these help to accelerate deployability?
  • Which RAN functions can or should be supported with embedded AI?
  • Where would the AI processing capability be located in the network and what are the main architectural decisions?

Who should read this report:

  • Heads of strategy and technology within vendor companies in the RAN equipment, RAN software, AI platforms, AI models and data, and semiconductors sectors.
  • CTO office and heads of network or data strategy within operators, especially those that aim to establish a roadmap for RAN AI and for virtualised RAN within the next few years.
  • CEOs and CTOs within start-up companies that are focused on RAN AI.
  • Leaders of standards groups or industry alliances that are working on RAN AI.
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