| Title |
Two-way LED-to-LED Visible Light Communication SystemUsing Machine Learning |
| Authors |
최일원(Ilwon Choi) ; 김기훈(Kihun Kim) ; 박수빈(Soovin Park) ; 이윤기(Yungi Lee) ; 심규성(Kyusung Shim) ; 안병구(Beongku An) |
| DOI |
https://doi.org/10.5573/ieie.2019.56.3.33 |
| Keywords |
Visible Light Communication(VLC) ; Two-way LED-to-LED communication ; Machine learning |
| Abstract |
In this paper, we propose a two-way LED-to-LED Visible Light Communication(VLC) system using machine learning. The main features and contributions of the proposed system are as follows. First, using machine learning, the proposed system can reduce and improve the data error rate of the randomly varying wireless VLC channel conditions. Second, the proposed system can increase the data reception rate in LED-to-LED bidirectional system by channel correction and improvement using the machine learning. Third, the proposed system can store the phenomenon that occurs during data transmission through channel learning in the database, and the changes of the channeling data can be confirmed through the stored data in the database. It compensates and stabilizes the data channeling state of VLC, which is sensitive to external environment factors. This can effectively improves the data communication state of the VLC. From the performance of the proposed system, we can see the proposed system can compensate and improve the disadvantages of the VLC using light that is so sensitive to the external environment effects. Also, we can confirm the proposed system can improve the rate of transmission and reception when the transmission distance is increased. |