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논문 기본 정보
- 자료유형
- 학위논문
- 저자정보
- 지도교수
- 정지원
- 발행연도
- 2020
- 저작권
- 한국해양대학교 논문은 저작권에 의해 보호받습니다.
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초록· 키워드
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In UWOC (Underwater Wireless Optical Communication) systems, scattering and absorption occur due to water molecules and suspended particles, resulting in weak signals at the receiver end. In this thesis, a LDPC (Low-Density Parity-Check) code, which is a kind of error-correcting code, was employed in order to compensate for performance loss, and its performance was improved only when the input values of the decoder were soft decision types.
However, no algorithm has yet been reported that applies a soft decision technique for the M-ary PPM (Pulse Position Modulation) and QAM (Quadrature Amplitude Modulation) schemes in the case of UWOC. Therefore, we developed a SVG (Soft Value Generator) algorithm in order to use a turbo equalizer, which improves the performance over all of the iterations in the case of the M-ary PPM and QAM schemes.
Through simulations, it was confirmed that the proposed method performs better than the conventional hard decision algorithm. Also it evaluated that the performance of the proposed method through four water tank experiments, in which M-ary PPM and QAM data were employed to perform experiments by varying the turbidity and transmission rates in a water tank. In addition, the experiment was conducted to compare performance with changes in water temperature, and to compare green laser with red laser. And an experiment was done to compare when the water was mixed with when it was unmixed. This again showed that the performance of the proposed algorithm is superior to that of the conventional algorithm.
However, no algorithm has yet been reported that applies a soft decision technique for the M-ary PPM (Pulse Position Modulation) and QAM (Quadrature Amplitude Modulation) schemes in the case of UWOC. Therefore, we developed a SVG (Soft Value Generator) algorithm in order to use a turbo equalizer, which improves the performance over all of the iterations in the case of the M-ary PPM and QAM schemes.
Through simulations, it was confirmed that the proposed method performs better than the conventional hard decision algorithm. Also it evaluated that the performance of the proposed method through four water tank experiments, in which M-ary PPM and QAM data were employed to perform experiments by varying the turbidity and transmission rates in a water tank. In addition, the experiment was conducted to compare performance with changes in water temperature, and to compare green laser with red laser. And an experiment was done to compare when the water was mixed with when it was unmixed. This again showed that the performance of the proposed algorithm is superior to that of the conventional algorithm.
목차
제 1 장 서론----1제 2 장 수중 레이저 통신 모델----32.1 수중 레이저 통신 송수신 모델----32.2 수중 레이저 통신에서 고려되는 채널 부호화 기법----42.3 수중 레이저 통신에서 고려되는 변조 기법----62.4 수중 레이저 통신 채널 환경----8제 3 장 제안한 LDPC 부호화된 터보 등화 기법----103.1 제안한 터보 등화 기법 모델----103.2 SVG 알고리즘----113.2.1 M진 PPM 변조 기법에서 SVG 알고리즘----113.2.2 M진 QAM 변조 기법에서 SVG 알고리즘----14제 4 장 시뮬레이션 및 실험 성능 분석----174.1 시뮬레이션 성능 분석----174.2 수조 실험 결과----204.2.1 수조 실험 환경----214.2.2 2018년 8월 실험 결과 분석----244.2.3 2018년 10월 실험 결과 분석----304.2.4 2019년 6월 실험 결과 분석----364.2.5 2019년 9월 실험 결과 분석----39제 5 장 결 론----48감사의 글----50참고문헌----51
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