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V2V 환경에서 적응적 채널 추정 기법에 대한 성능 분석

Performance Analysis of Adaptive Channel Estimation Scheme in V2V Environments

  • 이지혜 (전남대학교 전자컴퓨터공학과) ;
  • 문상미 (전남대학교 전자컴퓨터공학과) ;
  • 권순호 (전남대학교 전자컴퓨터공학과) ;
  • 추명훈 (전남대학교 전자컴퓨터공학과) ;
  • 배사라 (전남대학교 전자컴퓨터공학과) ;
  • 김한종 (한국기술교육대학 정보기술공학부) ;
  • 김철성 (전남대학교 전자컴퓨터공학과) ;
  • 김대진 (전남대학교 전자컴퓨터공학과) ;
  • 황인태 (전남대학교 전자컴퓨터공학과)
  • Lee, Jihye (School of Electronics & Computer Engineering Chonnam National University) ;
  • Moon, Sangmi (School of Electronics & Computer Engineering Chonnam National University) ;
  • Kwon, Soonho (School of Electronics & Computer Engineering Chonnam National University) ;
  • Chu, Myeonghun (School of Electronics & Computer Engineering Chonnam National University) ;
  • Bae, Sara (School of Electronics & Computer Engineering Chonnam National University) ;
  • Kim, Hanjong (School of Electrical, Electronics & Communication Engineering, Korea University of Technology and Education) ;
  • Kim, Cheolsung (School of Electronics & Computer Engineering Chonnam National University) ;
  • Kim, Daejin (School of Electronics & Computer Engineering Chonnam National University) ;
  • Hwang, Intae (School of Electronics & Computer Engineering Chonnam National University)
  • 투고 : 2017.03.20
  • 심사 : 2017.07.28
  • 발행 : 2017.08.25

초록

차량통신은 도로 위 차량들 간의 효율적인 조정을 가능하게 할 수 있을 뿐만 아니라, 더 나아가 미래 차량의 어플리케이션으로 차량 안전, 인포테인먼트 그리고 자율 주행까지도 다룰 수 있다. 3GPP(3rd Generation Partnership Project)에서는 LTE(Long Term Evolution) 기반 차량 통신에 대한 표준화 연구가 활발히 진행되고 있다. 차량 통신은 안전과 밀접한 관련이 있기 때문에, 낮은 지연과 높은 신뢰성을 필요로 한다. 하지만 차량의 빠른 이동성으로 인해 V2V(Vehicle-to-Vehicle) 환경은 채널 왜곡이 매우 심하며, 높은 신뢰성의 차량 통신을 위해서 채널 추정이 매우 중요한 요소임을 알 수 있다. 이를 위해 본 논문에서는 LTE 기반 V2V 환경에서 채널 추정 기법을 제안한다. LTE 기반 업링크 시스템에서 채널 추정은 파일럿 심볼인 DMRS(DeModulation Reference Signal)를 이용한다. 기존 채널 추정 기법으로는 LS(Least Square), DDCE(Decision Directed Channel Estimation), STA(Spectral Temporal Averaging), 그리고 Smoothing이 있다. 본 논문에서는 기존의 채널 추정 기법들과 달리 파일럿 심볼에서 QS(Quadratic Smoothing)를 이용해 보다도 정확한 채널을 추정하며, 데이터 심볼에서 적응적으로 채널을 추정하는 ASCE(Adaptive Smoothing Channel Estimation) 기법을 제안한다. 모의실험 결과, 제안한 ASCE 기법이 NMSE(Normalized Mean Square Error)와 BER(Bit Error Rate) 측면에서 전체적으로 성능이 향상 된 것을 볼 수 있다.

Vehicle communication can facilitate efficient coordination among vehicles on the road and enable future vehicular applications such as vehicle safety enhancement, infotainment, or even autonomous driving. In the $3^{rd}$ Generation Partnership Project (3GPP), many studies focus on long term evolution (LTE)-based vehicle communication. Because vehicle speed is high enough to cause severe channel distortion in vehicle-to-vehicle (V2V) environments. We can utilize channel estimation methods to approach a reliable vehicle communication systems. Conventional channel estimation schemes can be categorized as least-squares (LS), decision-directed channel estimation (DDCE), spectral temporal averaging (STA), and smoothing methods. In this study, we propose a smart channel estimation scheme in LTE-based V2V environments. The channel estimation scheme, based on an LTE uplink system, uses a demodulation reference signal (DMRS) as the pilot symbol. Unlike conventional channel estimation schemes, we propose an adaptive smoothing channel estimation scheme (ASCE) using quadratic smoothing (QS) of the pilot symbols, which estimates a channel with greater accuracy and adaptively estimates channels in data symbols. In simulation results, the proposed ASCE scheme shows improved overall performance in terms of the normalized mean square error (NMSE) and bit error rate (BER) relative to conventional schemes.

키워드

참고문헌

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