| Title |
A Machine Learning-based Error Correction and Filtering System for Multicast Visible Light Communications |
| Authors |
엄상인(Sangin Eom) ; 고준수(Junsu Ko) ; 심규성(Kyusung Shim) ; 안병구(Beongku An) |
| DOI |
https://doi.org/10.5573/ieie.2021.58.3.3 |
| Keywords |
Machine learning; multicast; visible light communication; text error correction |
| Abstract |
In this paper, we propose a machine learning-based text data error correction and filtering system for supporting multicast visible light communication (MVLC) efficiently. The main feature and contribution of this paper can be summarized as follows. First, the proposed system can support the MVLC efficiently. Second, when the received text data message includes an error in MVLC, the proposed system can efficiently correct the received errors using machine learning without extra packet transmission and data information. Third, the proposed system can efficiently support the text data filtering using machine learning for MVLC. From the performance evaluation, we can see that the proposed system can judge by oneself the errors of the received text data while the malicious error text data can be corrected and filtered efficiently in MVLC. |