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시간지연 인공신경망을 이용한 수동소자 상호변조 왜곡 추정
장범희(Beomhee Jang),김현채(Hyunchae Kim),임성빈(Sungbin Im),김종훈(Chonghoon Kim) 대한전자공학회 2018 전자공학회논문지 Vol.55 No.12
수동소자 상호변조 왜곡은 무선 통신 환경에서 수동소자의 비선형성으로 인하여 발생하는 간섭신호이고, 수신기의 잡음수준을 높여 통신의 품질저하를 초래한다. 본 논문은 FDD (Frequency Division Duplex) 무선 통신 시스템에서 LTE 시스템과 Wibro 시스템 공용화 시 순방향 신호에 의하여 발생하는 3차 PIMD (Passive Interomodulation Distortion) 추정에 대한 방법을 제안한다. 두 시스템 각각의 송신신호와 실제 측정한 수동소자 상호변조 왜곡신호를 이용하여 인공신경망 알고리즘의 한 종류인 FTDNN (Focused Time Delay Neural Network) 모델에 학습 및 테스트를 수행하였다. 그 결과, FTDNN 구조가 수동소자 상호변조 왜곡의 비선형성을 학습하는데 적합함을 확인하였고, 간섭제거 알고리즘에 사용될 수 있다는 가능성을 확인하였다. 본 연구에서 제안한 수동소자 상호변조 왜곡 추정방식은 시스템의 출력단에 연동하여 동작 할 수 있으므로 유지보수가 간편하고 장소적인 한계를 극복 할 수 있다는 장점이 있다. Passive intermodulation distortion is an interference signal generated due to non-linearity of a passive element in a wireless communication environment and raises the noise level of a receiver, resulting in a deterioration of communication quality. This paper proposes a method for estimating the 3rd PIM (Third Passive Intermodulation) caused by the forward signal in the FDD (Frequency Division Duplex) wireless communication system when the LTE system and the Wibro system are shared. Learning and testing were performed on a FTDNN (Focused Time Delay Neural Network) model, which is a kind of artificial neural network algorithm, using the transmitted signals of both systems and the actually measured passive intermodulation distortion signals. As a result, it is confirmed that FTDNN structure is suitable for learning non-linearity of passive intermodulation distortion, and it is confirmed that it can be used for interference cancellation algorithm. The passive distortion estimation method proposed in this study can operate in conjunction with the output stage of the system, so it is easy to maintain and can overcome limitations of the place.
Improved particle fusing geometric relation between particles in FastSLAM
Kim, Inkyu,Kwak, Nosan,Lee, Heoncheol,Lee, Beomhee Cambridge University Press 2009 Robotica Vol.27 No.6
<B>SUMMARY</B><P>FastSLAM is a framework for simultaneous localization and mapping using a Rao-Blackwellized particle filter (RBPF). But, FastSLAM is known to degenerate over time due to the loss of particle diversity, mainly caused by the particle depletion problem in resampling phase. In this work, improved particle filter using geometric relation between particles is proposed to restrain particle depletion and to reduce estimation errors and error variances. It uses a KD tree (<I>k</I>-dimensional tree) to derive geometric relation among particles and filters particles with importance weight conditions for resampling. Compared to the original particle filter used in FastSLAM, this technique showed less estimation error with lower error standard deviation in computer simulations.</P>
Kim, Hoonbae,Yeo, Donghyun,Won, Beomhee,Yu, SeGi,Jung, Donggeun American Scientific Publishers 2016 Journal of Nanoscience and Nanotechnology Vol.16 No.5
<P>Flexible organic solar cells (OSCs) were fabricated on an indium-tin-oxide (ITO)/poly(ethylene terephthalate) (PET) substrate and were subjected to bending tests with various bending radii. We observed that the photovoltaic properties of the OSCs precipitously deteriorated at a bending radius <= 0.75 cm. In order to investigate the effects of the bending test, the changes in the surface morphology and the sheet resistance of the ITO-coated PET samples were investigated, and the photovoltaic properties of bent and unbent OSCs were evaluated. Thereafter, equivalent circuits for the OSCs were assumed and the change in their parameters, such as resistance and capacitance, was observed.</P>