• Title/Summary/Keyword: DDCE(Decision Directed Channel Estimation)

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Channel Estimation Method Using the Correlation in the High-Speed Wireless Transmissions (고속 무선 전송에서 상관관계를 이용한 채널 추정방식)

  • Lee Joo-Hyoung;Kim Joo-Kyoung;Kim Jae-Moung
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.4 no.1 s.6
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    • pp.63-71
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    • 2005
  • This paper proposes the channel estimation method robust to severe frequency selective fading channels in O%M system using wide bandwidth for the high data rate transmission. DDCE, which uses data between the high correlated symbols, is usually used for channel estimation in the slow fading channels. DDCE can get high gains in the non-selective channels. As the bandwidth of system gets wider, it becomes more severe frequency selective fading environments so that the reliability of data becomes lower and error flow is occurred. FE method, this paper proposed, uses the relation between sub-carriers of OFDM in frequency selective fading channels so FE method gets some gains by adapting the power value at a target frequency to the mean value of channel estimated values of adjacent sub-carriers. Because FE uses only preamble unlike DDCE using data, it is independent of data rate related to the reliability of data and the number of multipath. Consequently, FE can obtain considerable gains in the wideband systems where the errorflow of DDCE is occurred, and FE is applicable to frequency selective fading environments.

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Joint Symbol Detection and Channel Estimation Methods for an OFDM System in Fading Channels (페이딩 채널환경에서 OFDM 시스템에 대한 심볼 검출 및 채널 추정 기법)

  • Cho, Jin-Woong;Kang, Cheol-Ho
    • Journal of the Institute of Electronics Engineers of Korea TC
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    • v.38 no.3
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    • pp.9-18
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    • 2001
  • In this paper, we present the joint symbol detection and channel estimation for an orthogonal frequency division multiplexing (OFDM) system in fading channels. The proposed methods are based on decision-directed channel estimation (DDCE) method and their symbol detection is achieved by using Viterbi algorithm. This Viterbi decision-directed channel estimation (VDDCE) method tracks time-varying channels and detects a maximum likelihood symbol sequence. Recursive Viterbi decision-directed channel estimation (RVDDCE) method based on VDDCE method is proposed to shorten the detecting depth. In this method, channel estimate and Viterbi processing are recursively performed every interval of training symbol. Also, average chann'el estimation (ACE) technique to reduce the effect of additive white Gaussian noise (AWGN) is applied VDDCE method and RVDDCE method. These proposed methods arc demonstrated by computer simulation.

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Performance Analysis of Adaptive Channel Estimation Scheme in V2V Environments (V2V 환경에서 적응적 채널 추정 기법에 대한 성능 분석)

  • Lee, Jihye;Moon, Sangmi;Kwon, Soonho;Chu, Myeonghun;Bae, Sara;Kim, Hanjong;Kim, Cheolsung;Kim, Daejin;Hwang, Intae
    • Journal of the Institute of Electronics and Information Engineers
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    • v.54 no.8
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    • pp.26-33
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    • 2017
  • 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.

Novel LTE based Channel Estimation Scheme for V2V Environment (LTE 기반 V2V 환경에서 새로운 채널 추정 기법)

  • Chu, Myeonghun;Moon, Sangmi;Kwon, Soonho;Lee, Jihye;Bae, Sara;Kim, Hanjong;Kim, Cheolsung;Kim, Daejin;Hwang, Intae
    • Journal of the Institute of Electronics and Information Engineers
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    • v.54 no.3
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    • pp.3-9
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    • 2017
  • Recently, in 3rd Generation Partnership Project(3GPP), there is a study of the Long Term Evolution(LTE) based vehicle communication which has been actively conducted to provide a transport efficiency, telematics and infortainment. Because the vehicle communication is closely related to the safety, it requires a reliable communication. Because vehicle speed is very fast, unlike the movement of the user, radio channel is rapidly changed and generate a number of problems such as transmission quality degradation. Therefore, we have to continuously updates the channel estimates. There are five types of conventional channel estimation scheme. Least Square(LS) is obtained by pilot symbol which is known to transmitter and receiver. Decision Directed Channel Estimation(DDCE) scheme uses the data signal for channel estimation. Constructed Data Pilot(CDP) scheme uses the correlation characteristic between adjacent two data symbols. Spectral Temporal Averaging(STA) scheme uses the frequency-time domain average of the channel. Smoothing scheme reduces the peak error value of data decision. In this paper, we propose the novel channel estimation scheme in LTE based Vehicle-to-Vehicle(V2V) environment. In our Hybrid Reliable Channel Estimation(HRCE) scheme, DDCE and Smoothing schemes are combined and finally the Linear Minimum Mean Square Error(LMMSE) scheme is applied to minimize the channel estimation error. Therefore it is possible to detect the reliable data. In simulation results, overall performance can be improved in terms of Normalized Mean Square Error(NMSE) and Bit Error Rate(BER).