Analysis and Identification of Root Cause of 5G Radio Quality Deterioration Using Machine Learning

Author:

NISHIKAWA Yoshiaki1,MARUYAMA Shohei1,ONISHI Takeo1,TAKAHASHI Eiji1

Affiliation:

1. NEC

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Networks and Communications,Software

Reference16 articles.

1. [1] Ministry of Economy, Trade and Industry, “Industrial Technology Vision 2020 Compiled,” May 2020. https://www.meti.go.jp/english/press/2020/pdf/0529_008a.pdf

2. [2] 5G ACIA, “Key 5G Use Cases and Requirements,” White Paper, May 2020. https://5g-acia.org/wp-content/uploads/5G-ACIA_WP_Key-5G-Use-Cases-and-Requirements_SinglePages.pdf

3. [3] 3GPP, “Service requirements for cyber-physical control applications in vertical domains,” TS 22.104, V17.4.0, Oct. 2020.

4. [4] L. Breiman, “Random Forests,” Machine Learning 45, pp5-32, Oct. 2001. 10.1023/a:1010933404324

5. [5] S. Hochreiter and J. Schmidhuber, “Long short-term memory,” Neural Computation, vol.9, no.8, pp.1735-1780, Nov. 1997. 10.1162/neco.1997.9.8.1735

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