전자통신동향분석 (Electronics and Telecommunications Trends)

한국전자통신연구원 (Electronics and Telecommunications Research Institute)
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지능형 Self-Organizing Network를 위한 설명 가능한 기계학습 연구 동향

Trend in eXplainable Machine Learning for Intelligent Self-organizing Networks

  • 권동승 (지능형스몰셀연구실) ;
  • 나지현 (지능형스몰셀연구실)
  • D.S. Kwon ;
  • J.H. Na
  • 발행 : 2023.12.01
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초록

As artificial intelligence has become commonplace in various fields, the transparency of AI in its development and implementation has become an important issue. In safety-critical areas, the eXplainable and/or understandable of artificial intelligence is being actively studied. On the other hand, machine learning have been applied to the intelligence of self-organizing network (SON), but transparency in this application has been neglected, despite the critical decision-makings in the operation of mobile communication systems. We describes concepts of eXplainable machine learning (ML), along with research trends, major issues, and research directions. After summarizing the ML research on SON, research directions are analyzed for explainable ML required in intelligent SON of beyond 5G and 6G communication.

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과제정보

이 논문은 2023년도 정부(과학기술정보통신부)의 재원으로 정보통신기획평가원의 지원을 받아 수행된 연구임[No. 2018-0-01659, 5G NR 기반 지능형 오픈 스몰셀 기술 개발].

참고문헌

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