| Paper Abstract and Keywords |
| Presentation |
2019-11-26 14:10
[Poster Presentation]
Issues for Application of Machine Learning to Prediction of Blockage of Millimeter Wave toward Advancement of 5G Mobile Communication System
Takahide Murakami, Satoshi Ito, Shoichiro Mihara, Hiroyuki Shinbo (KDDI Research) |
| Abstract |
(in Japanese) |
(See Japanese page) |
| (in English) |
In a period of spreading 5G mobile communication system and moving toward advanced system, communication services will become diversified. As a result, satisfaction of quality requirements from various types of communication services will be needed in environment with increased traffic from a large number of terminals. Utilizing millimeter wave (mmWave) will be expected to accommodate such requirements. In order to secure mobile link connectivity which is essential for accommodating communication quality in mmWave, prediction of sudden disconnection of mobile link due to blockage induced by people or moving objects is important. To utilize mmWave especially in outdoor environment where terminals are densely distributed, we are studying a method for avoiding sudden disconnection of mobile link with prediction of blockage applying machine learning by using information about video image obtained by stereo cameras in addition to characteristics of received radio signals. In this report, issues for applying the method in the supposed environment are described based on the existing study reports. |
| Keyword |
(in Japanese) |
(See Japanese page) |
| (in English) |
5G / millimeter wave (mmWave) communications / blockage prediction / machime learning / / / / |
| Reference Info. |
IEICE Tech. Rep. |
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| Conference Information |
| Committee |
RISING |
| Conference Date |
2019-11-26 - 2019-11-27 |
| Place (in Japanese) |
(See Japanese page) |
| Place (in English) |
Fukutake Learning Theater, Hongo Campus, Univ. Tokyo |
| Topics (in Japanese) |
(See Japanese page) |
| Topics (in English) |
Researches on Super-Intelligent Networking, etc. |
| Paper Information |
| Registration To |
RISING |
| Conference Code |
2019-11-RISING |
| Language |
Japanese |
| Title (in Japanese) |
(See Japanese page) |
| Sub Title (in Japanese) |
(See Japanese page) |
| Title (in English) |
Issues for Application of Machine Learning to Prediction of Blockage of Millimeter Wave toward Advancement of 5G Mobile Communication System |
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| Keyword(1) |
5G |
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millimeter wave (mmWave) communications |
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blockage prediction |
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machime learning |
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| 1st Author's Name |
Takahide Murakami |
| 1st Author's Affiliation |
KDDI Research, Inc. (KDDI Research) |
| 2nd Author's Name |
Satoshi Ito |
| 2nd Author's Affiliation |
KDDI Research, Inc. (KDDI Research) |
| 3rd Author's Name |
Shoichiro Mihara |
| 3rd Author's Affiliation |
KDDI Research, Inc. (KDDI Research) |
| 4th Author's Name |
Hiroyuki Shinbo |
| 4th Author's Affiliation |
KDDI Research, Inc. (KDDI Research) |
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| Speaker |
Author-1 |
| Date Time |
2019-11-26 14:10:00 |
| Presentation Time |
50 minutes |
| Registration for |
RISING |
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