• 제목/요약/키워드: basis expansion model (BEM)

검색결과 5건 처리시간 0.023초

고속 시변 채널 OFDM을 위한 저복잡도 LS 채널 예측의 성능 개선 (Performance Improvement of Low Complexity LS Channel Estimation for OFDM in Fast Time Varying Channels)

  • 임동민
    • 대한전자공학회논문지TC
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    • 제49권8호
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    • pp.25-32
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    • 2012
  • 본 논문에서는 고속 시변 채널 OFDM을 위한 저복잡도 LS(Least Squares) 채널 예측의 성능 개선 방안을 제안한다. 저복잡도 LS 채널 예측을 위해 사용하는 CE-BEM(Complex Exponential-Basis Expansion Model) 채널 모델의 경우 채널 모델 자체의 문제점으로 인하여 채널 예측 성능 저하가 발생한다. 본 논문에서는 우선 시간 영역 윈도우를 이용하여 데이터 심볼에 의한 ICI(Interchannel Interference)의 영향을 제거한다. LS 채널 예측 결과에서 샘플을 취하여 윈도우의 영향을 제거한 후 특성이 채널 변화의 표현에 적합한 DPSS(Discrete Prolate Spheroidal Sequences)를 기저함수(basis function)로 하는 보간 (interpolation) 방식으로 채널 응답을 복원하여 CE-BEM의 문제점을 해결한다. 컴퓨터 모의실험을 통한 성능 확인 결과 제안된 채널 예측 방식은 기존의 방식과 비교하여 특히 고속 시변 채널에서 우수한 성능 개선 효과를 보여주며, 선택된 기저함수의 형태뿐만 아니라 기저함수의 개수의 설정이 성능을 크게 좌우하는 또 다른 요소임을 확인하였다.

고속 시변 채널 OFDM을 위한 파일럿 심볼을 이용한 저복잡도 LS 채널 예측 (Pilot Symbol Assisted Low Complexity LS Channel Estimation for OFDM in Fast Time Varying Channels)

  • 임동민
    • 대한전자공학회논문지TC
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    • 제48권11호
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    • pp.17-21
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    • 2011
  • 본 논문에서는 고속 시변 채널 OFDM을 위한 파일럿 심볼을 이용하는 저복잡도 LS(Least Square) 채널 예측 방식을 제안한다. 제안된 방식은 기존의 BEM(Basis Expansion Model) 채널 모델 LS 예측 방식과 비교하여 동일한 성능에서 저장공간 및 계산량이 줄어드는 저복잡도 특성을 나타낸다.

Novel Adaptive Distributed Compressed Sensing Algorithm for Estimating Channels in Doubly-Selective Fading OFDM Systems

  • Song, Yuming;He, Xueyun;Gui, Guan;Liang, Yan
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제13권5호
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    • pp.2400-2413
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    • 2019
  • Doubly-selective (DS) fading channel is often occurred in many orthogonal frequency division multiplexing (OFDM) communication systems, such as high-speed rail communication systems and underwater acoustic (UWA) wireless networks. It is challenging to provide an accurate and fast estimation over the doubly-selective channel, due to the strong Doppler shift. This paper addresses the doubly selective channel estimation problem based on complex exponential basis expansion model (CE-BEM) in OFDM systems from the perspective of distributed compressive sensing (DCS). We propose a novel DCS-based improved sparsity adaptive matching pursuit (DCS-IMSAMP) algorithm. The advantage of the proposed algorithm is that it can exploit the joint channel sparsity information using dynamic threshold, variable step size and tailoring mechanism. Simulation results show that the proposed algorithm achieves 5dB performance gain with faster operation speed, in comparison with traditional DCS-based sparsity adaptive matching pursuit (DCS-SAMP) algorithm.

Low Pilot Ratio Channel Estimation for OFDM Systems Based on GCE-BEM

  • Wang, Lidong;Lim, Dong-Min
    • Journal of electromagnetic engineering and science
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    • 제7권4호
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    • pp.195-200
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    • 2007
  • Doubly-selective channel estimator for orthogonal frequency division multiplexing(OFDM) systems is proposed in this paper. Based on the generalized complex exponential basis expansion model(GCE-BEM), we describe the time-variant channel with time-invariant coefficients over multiple OFDM blocks. The time variation of the channel destroys the orthogonality between subcarriers, and the resulting channel matrix in the frequency domain is no longer diagonal, but the main interference comes from the near subcarriers. Based on this, we propose a channel estimator with low pilot ratio. We first develop a least-square(LS) estimator under the assumption that only the maximum Doppler frequency and the channel order are known at the receiver, and then verify that the correlation matrix of inter-channel interference(ICI) is a scaled identity matrix based on which we derive an optimal pilot insertion scheme for the LS estimator in the sense of minimum mean square error. The proposed estimator has the advantages of low pilot ratio and robustness against inter-carrier interference.

Joint Kalman Channel Estimation and Turbo Equalization for MIMO OFDM Systems over Fast Fading Channels

  • Chang, Yu-Kuan;Ueng, Fang-Biau;Shen, Ye-Shun;Liao, Chih-Yuan
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제13권11호
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    • pp.5394-5409
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    • 2019
  • The paper investigates a novel detector receiver with Kalman channel information estimator and iterative channel response equalization for MIMO (multi-input multi-output) OFDM (orthogonal frequency division multiplexing) communication systems in fast multipath fading environments. The performances of the existing linear equalizers (LE) are not good enough over most fast fading multipath channels. The existing adaptive equalizer with decision feedback structure (ADFE) can improve the performance of LE. But error-propagation effect seriously degrades the system performance of the ADFE, especially when operated in fast multipath fading environments. By considering the Kalman channel impulse response estimation for the fast fading multipath channels based on CE-BEM (complex exponential basis expansion) model, the paper proposes the iterative receiver with soft decision feedback equalization (SDFE) structure in the fast multipath fading environments. The proposed SDFE detector receiver combats the error-propagation effect for fast multipath fading channels and outperform the existing LE and ADFE. We demonstrate several simulations to confirm the ability of the proposed iterative receiver over the existing receivers.