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High-speed visible light communication system using space division processing

공간 분할 처리를 이용한 고속 가시광통신 시스템

  • Park, Jun Hyung (Department of Electronic Engineering, Semyung University) ;
  • Lee, Kyu Jin (Department of Electronic Engineering, Semyung University)
  • 박준형 (세명대학교 전자공학과) ;
  • 이규진 (세명대학교 전자공학과)
  • Received : 2018.10.22
  • Accepted : 2018.12.20
  • Published : 2018.12.31

Abstract

There are various 'wireless communication technologies' around us. Wireless mobile communication has evolved through various stages, and its utilization is also diverse. However, due to the development of wireless communication technology, the demand for frequency resources is much higher than the supply, so frequency shortage is serious. Recently, 'visible light communication' has been attracting attention as an emerging communication technology that can solve the frequency shortage. 'Visible light communication' is a communication method based on serial data transmission / reception, and there is a difficulty in transmitting / receiving parallel data because the transmitter and the receiver are arbitrarily present. In this paper, we have studied parallel data processing of visible light communication. We could solve the problem by analyzing parallel data using image processing. Through this study, communication performance can be verified through I / O data comparison by implementing parallel data analysis method. It is expected that diversity in parallel data analysis will be presented through the results.

우리 주변에는 다양한 '무선 통신 기술'이 존재한다. 하지만 무선 통신 기술의 발달로 인해 주파수 자원을 필요로 하는 기술이 늘어나면서 주파수 부족 현상이 심각하게 대두되었다. 최근 이러한 문제를 해결할 수 있는 대안으로 떠오르는 통신기술로 '가시광 통신'이 주목받고 있다. '가시광 통신'은 직렬데이터 송수신을 기반으로 하는 통신 방법으로 발신부의 한계 및 포토다이오드를 이용하는 수신단의 문제 때문에 병렬데이터 송수신에 어려움이 있다. 본 논문에서는 이러한 가시광 통신의 병렬데이터 처리에 대하여 연구했다. 가시광 통신 시스템에 영상처리를 적용한 병렬데이터 분석을 통해 병렬데이터 분석 방법을 구현하였다. 제안 시스템에서 입출력 데이터 매칭 비교를 통해 병렬 통신 성능을 확인할 수 있었으며 병렬데이터 분석에 다양성을 제시할 것으로 기대된다.

Keywords

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Fig. 1. Visible light communication principle

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Fig. 2. HPF & LPF Mask

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Fig. 3. System Concept

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Fig. 4. System Flow Chart

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Fig. 5. Grayscale & Template Matching

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Fig. 6. HPF, LPF & Template Matching

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Fig. 7. Matching results by Center value(9.1-9.4)

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Fig. 8. Matching results by Center value(9.7, 9.8)

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Fig. 9. Template Matching complete

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Fig. 10. Matching Time & Detect Data

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