• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.5C
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• pp.317-325
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• 2011

For OFDM (Orthogonal Frequency Division Multiplexing) systems, 2-D MMSE (2-Dimensional Minimum Mean Square Error) channel estimation provides optimal performance in frequency/time selective fading channel environment. However, the 2-D MMSE channel estimation has high computational complexity due to the large matrix size, because the 2-D MMSE channel estimation considers time as well as frequency axis for channel estimation. To reduce the computational complexity, we propose a modified 2-D MMSE channel estimator which is based on 1-D MMSE channel estimation with weighted sum. Furthermore, we consider RMS delay spread and Doppler frequency estimation for 2-D MMSE channel estimation. We show that the proposed method can significantly reduce computational complexity as well as that it can perform close to 2-D MMSE channel estimation.

• Journal of Advanced Navigation Technology
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• v.15 no.5
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• pp.735-741
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• 2011

In this paper, we have analyzed the effect of SNR estimation error on the BER performance of MMSE-DFE in high-speed binary CDMA system. Since MMSE equalization algorithm requires the SNR value of input signal, it should be estimated using CAZAC sequence in preamble. However, when AWGN and ISI exist simultaneously, it is impossible to estimate the exact SNR value of input signal and thereby equalizer's performance may be deteriorated. The simulation results can be used as a guideline for selection of SNR estimation algorithm for MMSE-DFE design.

• ETRI Journal
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• v.40 no.2
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• pp.218-226
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• 2018

Multiuser detection (MUD) and channel estimation techniques in space-division multiple-access aided orthogonal frequency-division multiplexing systems recently has received intensive interest in receiver design technologies. The maximum likelihood (ML) MUD that provides optimal performance has the cost of a dramatically increased computational complexity. The minimum mean-squared error (MMSE) MUD exhibits poor performance, although it achieves lower computational complexity. With almost the same complexity, an MMSE with successive interference cancellation (SIC) scheme achieves a better bit error rate performance than a linear MMSE multiuser detector. In this paper, hybrid ML-MMSE with SIC adaptive multiuser detection based on the joint channel estimation method is suggested for signal detection. The simulation results show that the proposed method achieves good performance close to the optimal ML performance at low SNR values and a low computational complexity at high SNR values.

• Journal of Communications and Networks
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• v.16 no.4
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• pp.447-457
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• 2014

In this paper, we investigate the frequency domain channel estimation for multiple-input multiple-output (MIMO) single-carrier frequency-division multiple-access (SC-FDMA) systems. In MIMO SC-FDMA, code-division multiplexed (CDM) pilots such as cyclic-shifted Zadoff-Chu sequences have been adopted for channel estimation. However, most frequency domain channel estimation schemes were developed based on frequency-division multiplexing of pilots. We first develop a channel estimation error model by using CDM pilots, and then analyze the mean-square error (MSE) of various minimum MSE (MMSE) frequency domain channel estimation techniques. We show that the cascaded one-dimensional robust MMSE (C1D-RMMSE) technique is complexity-efficient, but it suffers from performance degradation due to the channel correlation mismatch when compared to the two-dimensional MMSE (2D-MMSE) technique. To improve the performance of C1D-RMMSE, we design a robust iterative channel estimation (RITCE) with a frequency replacement (FR) algorithm. After deriving the MSE of iterative channel estimation, we optimize the FR algorithm in terms of the MSE. Then, a low-complexity adaptation method is proposed for practical MIMO SC-FDMA systems, wherein FR is performed according to the reliability of the data estimates. Simulation results show that the proposed RITCE technique effectively improves the performance of C1D-RMMSE, thus providing a better performance-complexity tradeoff than 2D-MMSE.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39A no.6
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• pp.333-342
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• 2014

The pilot assisted channel frequency response (CFR) estimation schemes for an OFDM-based system with virtual subcarriers are analyzed under the assumption that pilot symbols are located according to a comb-type pattern in the OFDM block. In particular, as the minimum mean square error (MMSE) based scheme aiming to directly predict the channel impulse response and the MMSE based scheme aiming to suppress the leakage have not been clearly compared, by proving that the mean square errors (MSEs) of the latter scheme is always larger than that of the former scheme, this paper shows that the former scheme is superior to the latter scheme. Moreover, the impact of the number of pilots on the performances of the MMSE and least-square based channel estimation schemes are investigated. The performance analyses of the presented schemes are confirmed by computer simulation.

• ETRI Journal
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• v.38 no.3
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• pp.510-517
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• 2016

Recent developments in the field of separation of mixed signals into music/voice components have attracted the attention of many researchers. Recently, iterative kernel back-fitting, also known as kernel additive modeling, was proposed to achieve good results for music/voice separation. To obtain minimum mean square error (MMSE) estimates of short-time Fourier transforms of sources, generalized spatial Wiener filtering (GW) is typically used. In this paper, we propose an advanced music/voice separation method that utilizes a generalized weighted ${\beta}$-order MMSE estimation (WbE) based on iterative kernel back-fitting (KBF). In the proposed method, WbE is used for the step of mixed music signal separation, while KBF permits kernel spectrogram model fitting at each iteration. Experimental results show that the proposed method achieves better separation performance than GW and existing Bayesian estimators.

• International Journal of Contents
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• v.15 no.4
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• pp.27-35
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• 2019

In this paper, we propose an advanced Minimum Mean Square Error (MMSE) channel estimation method for IEEE 802.11p/Wireless Access in Vehicular Environments (WAVE) systems. To improve the performance of MMSE method, we apply the Weighted Sum using Update Matrix (WSUM) scheme to the step of calculating the instantaneously estimated channel and then, a time domain selectively averaging method is applied after the WSUM scheme. Based on that, the accuracy of instantaneously estimated channel increases and then, the accuracy of auto covariance matrix also increases. Consequently, we can achieve the performance gain over the conventional MMSE method. Through simulations based on the IEEE 802.11p standard, it is confirmed that the proposed scheme can outperform the existing channel estimation schemes.

• Journal of Satellite, Information and Communications
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• v.7 no.1
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• pp.53-58
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• 2012

In this paper, we evaluate and analyze representative estimation methods for the sparse channel. In order to evaluate error performance of matching pursuit(MP) and minimum mean square error(MMSE) algorithm, lower bound of MMSE is determined by Cramer-Rao bound and compared with upper bound of MP. Based on analysis of those bounds, mean square error of MP which is effective in the estimation of sparse channel can be larger than that of MMSE according to the number of estimated tap and signal-to-noise ratio. Simulation results show that the performances of both algorithm are reversed on the sparse channel with Rayleigh fading according to signal-to-noise ratio.

• The Journal of the Korea Contents Association
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• v.9 no.5
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• pp.84-90
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• 2009

In this paper, the new channel estimation was proposed that have the low complexity and high performance using Fuzzy inference method uses recently from various field for estimation about uncertainty in channel estimation of OFDM. Proposed method is channel estimation performance improve, calculation and interpolation for statistics character of channel using the pilot before LS channel estimation by Fuzzy inference method. Simulation result in QPSK proposed channel estimation method shows the enhancement of 5.5dB compared to the LS channel estimation and the deterioration of 1.3dB compared to the MMSE channel estimation in mean square error point $10^{-3}$. symbol error rate shows similarity performance the MMSE $10^{-1.96}$, proposed channel estimation $10^{-1.93}$ and enhancement of $10^{-0.35}$ compared to the LS channel estimation in signal to noise ratio point 20dB.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.9A
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• pp.1265-1275
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• 1999

An adaptive MMSE detector can be used to cancel the MAI in CDMA system. But standard adaptive MMSE detector cannot be used in real mobile environment due to fast fading channel. Furthermore multipath reception make it more difficult to converge to optimum weight values. In this paper we discuss and model the multipath fading environment in Forward-link Synchronous CDMA channels and propose adaptive MMSE RAKE detector structure which can be applied in the mobile station. A proposed adaptive MMSE detector requires estimation of received signal delay and complex channel coefficients such as amplitude and phase variation. These burden can be solved by utilizing the common pilot channel. The pilot channel may have higher power than the traffic channel, which give more exact channel estimation. Moreover RAKE structure gives more accurate and stable result which can be used as reliable reference signal in multipath fading channel environment. With this structure, conventional adaptive algorithm such as LMS or NLMS can be applied in adaptive MMSE detector.