• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.9
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• pp.2218-2230
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• 2012

In this paper, we propose an efficient channel delay estimation method for orthogonal frequency-division multiplexing (OFDM) systems, especially over doubly-selective fading channels which are selective in both the symbol time domain and subcarrier frequency domain. For the doubly-selective fading channels in single frequency network (SFN), long and strong echoes exist and thus the conventional discrete Fourier Transform (DFT) based channel delay estimation system often fails to produce the exact channel delay profile. Based on the analysis of the discrete-time frequency response of the channel impulse response (CIR) coefficients in the DFT-based channel delay estimation system, we develop a method to effectively extract the true CIR from the aliased signals by employing a simple narrow-band low-pass filter (NB-LPF). The performance of the proposed system is verified using the COST207 TU6 SFN channel model.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.7A
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• pp.628-638
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• 2005

The analysis of maximum diversity order and coding gain for multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) systems over time-and frequency-selective (or doubly-selective) channels is addressed in this paper. A novel channel time-space correlation function is developed given the spatially correlated doubly-selective Rayleigh fading channel model. Based on this channel-model assumption, the upper-bound of pairwise error probability (PEP) for MIMO-OFDM systems is derived under the maximum likelihood (ML) detection. For a certain space-frequency code, we quantify the maximum diversity order and deduce the expression of coding gain. In this wort the impact of channel time selectivity is especially studied and a new definition of time diversity is illustrated correspondingly

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.5
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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.

• Journal of electromagnetic engineering and science
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• v.6 no.4
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• pp.203-208
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• 2006

Channel estimation and data detection for OFDM systems over time- and frequency-selective channels are investigated. Relying on the complex exponential basis expansion channel model, a pilot-embedded channel estimation scheme with low computational complexity and spectral efficiency is proposed. A periodic pilot sequence is superimposed at a low power on information bearing sequence at the transmitter before modulation and transmission. The channel state information(CSI) can be estimated using the first-order statistics of the received data. In order to enhance the performance of channel estimation, we recover the transmitted data which can be exploited to estimate CSI iteratively. Simulation results show that the proposed method is suitable for doubly-selective channel estimation for the OFDM systems and the performance of the proposed method can be better than that of the Wiener filter method under some conditions. Through simulations, we also analyze the factors which can affect the system performances.

• Journal of electromagnetic engineering and science
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• v.7 no.4
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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.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.2
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• pp.583-599
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• 2015

We apply the Bayesian matching pursuit (BMP) algorithm to the estimation of time-frequency selective channels in orthogonal frequency division multiplexing (OFDM) systems. By exploiting prior statistics and sparse characteristics of propagation channels, the Bayesian method provides a more accurate and efficient detection of the channel status information (CSI) than do conventional sparse channel estimation methods that are based on compressive sensing (CS) technologies. Using a reasonable approximation of the system model and a skillfully designed pilot arrangement, the proposed estimation scheme is able to address the Doppler-induced inter-carrier interference (ICI) with a relatively low complexity. Moreover, to further reduce the computational cost of the channel estimation, we make some modifications to the BMP algorithm. The modified algorithm can make good use of the group-sparse structure of doubly selective channels and thus reconstruct the CSI more efficiently than does the original BMP algorithm, which treats the sparse signals in the conventional manner and ignores the specific structure of their sparsity patterns. Numerical results demonstrate that the proposed Bayesian estimation has a good performance over rapidly time-varying channels.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.21 no.6
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• pp.635-641
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• 2010

Time-varying channel characteristics in OFDM systems over doubly selective channels cause inter-carrier interferences(ICI) in the frequency domain. Time domain windowing gives rise to restriction on the bandwidth of the frequency domain channel matrix and makes it possible to approximate the OFDM system as a simplified linear input-output model. When successive interference cancellation based on linear MMSE estimation is employed for channel equalization in OFDM systems, symbol detection ordering produces considerable effects on overall system performances. In this paper, we show the reduction of the residual ICI by time domain windowing and the resultant performance improvements, and investigate the effects of SINR- and CSEP-based symbol detection ordering on the performance of successive interference cancellation.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.18 no.12
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• pp.1408-1418
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• 2007

In this paper, we analyze the performance of pilot symbol assisted channel estimation and equalization schemes for OFDM systems over frequency-selective time-varying channels and propose methods to improve the system performance. In the least square(LS) and linear minimum mean square error(MMSE) channel estimation, time domain windowing is introduced for banding the frequency domain channel matrix. The linear MMSE and decision feedback equalization schemes are employed with the pilot symbols for channel estimation taken into account in the equalization process. To reduce computational complexity, the band LU matrix factorization algorithm is introduced in solving the linear systems involved in the equalization, and the performances are compared with the known previous results by computer simulations. When time domain windowing is employed in the decision feedback equalization, the matrix related with the decision feedback process is shown to be unhanded and the resultant performance degradation is analyzed.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.21 no.1
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• pp.76-82
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• 2010

In this paper, we analyze the performance of the block linear MMSE equalization for OFDM systems in doubly selective channels by computer simulations. The block linear MMSE equalization shows somewhat unusual BER characteristics in that the BER curve drops at first as SNR increases but then rises up as SNR increases further beyond some point. In this paper, we investigate the BER characteristics of the block linear MMSE equalization by analyzing the condition number of the coefficient matrix in the linear system involved in the equalization process, and propose a new method to avoid the BER performance degradation at high SNR.

• Journal of Communications and Networks
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• v.12 no.4
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• pp.317-329
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• 2010

In recent years, many sparse estimation methods, also known as compressed sensing, have been developed. However, most of these methods presume that the measurement matrix is completely known. We develop a new blind maximum likelihood method-the expectation-sparse-maximization (ESpaM) algorithm-for models where the measurement matrix is the product of one unknown and one known matrix. This method is a variant of the expectation-maximization algorithm to deal with the resulting problem that the maximization step is no longer unique. The ESpaM algorithm is justified theoretically. We present as well numerical results for two concrete examples of blind channel identification in digital communications, a doubly-selective channel model and linear time invariant sparse channel model.