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Machine Learning-Based Signal Prediction Method for Power Line Communication Systems  

Sun, Young Ghyu (광운대학교 유비쿼터스 통신 연구실)
Sim, Issac (광운대학교 유비쿼터스 통신 연구실)
Hong, Seung Gwan (광운대학교 유비쿼터스 통신 연구실)
Kim, Jin Young (광운대학교 유비쿼터스 통신 연구실)
Publication Information
Journal of Satellite, Information and Communications / v.12, no.3, 2017 , pp. 74-79 More about this Journal
Abstract
In this paper, we propose a system model that predicts the original signal transmitted from the transmitter using the received signal in the power line communication system based on the multi - layer perceptron which is one of the machine learning algorithms. Power line communication system using communication system using power network has more noise than communication system using general communication line. It causes a problem that the performance of the power line communication system is degraded. In order to solve this problem, the communication system model proposed in this paper minimizes the influence of noise through original signal prediction and mitigates the performance degradation of the power line communication system. In this paper, we prove that the original signal is predicted by applying the proposed communication system model to the white noise environment.
Keywords
Machine learning; artificial neural network; power line communication system; additive white Gaussian noise channel; multi-layer perceptron;
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