Patent Trends on Machine Learning for Self-Organizing Network 


Vol. 46,  No. 12, pp. 2372-2382, Dec.  2021
10.7840/kics.2021.46.12.2372


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  Abstract

In order for 5G and B5G to become an infrastructure for the vertical industry, it is ultimately necessary to provide the optimal performance by the infrastructure itself while minimizing human intervention, so the application of Machine Learning (ML) technology to Self-Organizing Network(SON) is essential. Therefore, in this paper, the results of macroscopic and in-depth analysis of patent information of SON technology by ML are presented. According to the results of quantitative analysis of SON patent information, ML-applied SON patents account for 27% of all SON patents, and ML applications are biased in resource allocation and load balancing for self-optimization. In terms of patent competitiveness index, ML applied patents were about 1/2 of ML non-applied patents. Therefore, as the ML-applied SON patent is in its early stages globally, it is necessary to research and develop the ML-applied SON framework and self-optimization, composition, and healing technology.

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  Cite this article

[IEEE Style]

D. Kwon and J. Na, "Patent Trends on Machine Learning for Self-Organizing Network," The Journal of Korean Institute of Communications and Information Sciences, vol. 46, no. 12, pp. 2372-2382, 2021. DOI: 10.7840/kics.2021.46.12.2372.

[ACM Style]

Dong-Seung Kwon and Jee-Hyeon Na. 2021. Patent Trends on Machine Learning for Self-Organizing Network. The Journal of Korean Institute of Communications and Information Sciences, 46, 12, (2021), 2372-2382. DOI: 10.7840/kics.2021.46.12.2372.

[KICS Style]

Dong-Seung Kwon and Jee-Hyeon Na, "Patent Trends on Machine Learning for Self-Organizing Network," The Journal of Korean Institute of Communications and Information Sciences, vol. 46, no. 12, pp. 2372-2382, 12. 2021. (https://doi.org/10.7840/kics.2021.46.12.2372)

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pISSN : 1226 - 4717
eISSN : 2287 - 3880