• 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 the Korean Institute of Telematics and Electronics C
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• v.36C no.6
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• pp.44-51
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• 1999

The HMM-Net is a neural network architecture that implements the computation of output probabilities of a hidden Markov model (HMM). The architecture is developed for the purpose of combining the discriminant power of neural networks with the time-domain modeling capability of HMMs. Criteria of maximum likehood(ML) and minimization of mean squared error(MMSE) are used for learning HMM-Net classifiers. The criterion MMSE is better than ML when initial learning condition is well established. However Ml is more useful one when the condition is incomplete[3]. Therefore we propose an efficient learning method of HMM-Net classifiers using a hybrid criterion(ML/MMSE). In the method, we begin a learning with ML in order to get a stable start-point. After then, we continue the learning with MMSE to search an optimal or near-optimal solution. Experimental results for the isolated numeric digits from /0/ to /9/, a training and testing time-series pattern set, show that the performance of the proposed method is better than the others in the respects of learning and recognition rates.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.11C
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• pp.1098-1110
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• 2003

In this paper, we propose a homomorphic wavelet-based MMSE filter with edge detection to restore images degraded by speckle noise. In the proposed method, a noisy image is first transformed into logarithmic domain. Each pixel in the transformed image is then classified into flat and edge regions by applying DIP operator to the image restored by homomorphic directional MMSE filter. Each pixel in flat region is restored by homomorphic wavelet-based MMSE filter. Each pixel in edge region is restored by the weighted sum of the output of homomorphic wavelet-based MMSE filtering and that of homomorphic directional MMSE filtering. The restored image in spatial domain is finally obtained by applying the exponential function to the restored image in logarithmic domain. Experimental results show that the restored images by the proposed method have ISNR improvement of 3.3-4.0 ㏈ and ${\beta}$, a measurement parameter on edge preservation, improvement of 0.0103-0.0126 and superior subjective image quality over those by conventional methods.

• Journal of Satellite, Information and Communications
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• v.10 no.1
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• pp.22-28
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• 2015

In this paper, we propose a new computationally efficient joint iterative multi-input multi-output (MIMO) detection scheme using a soft interference cancellation and minimum mean squared-error (SIC-MMSE) method. The critical computational burden of the SIC-MMSE scheme lies in the multiple inverse operations of the complex matrices. We find a new way which requires only a single matrix inversion by utilizing the Taylor series expansion of the matrix, and thus the computational complexity can be reduced. The computational complexity reduction increases as the number of antennas is increased. The simulation results show that our method produces almost the same performances as the conventional SIC-MMSE with reduced computational complexity.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.8
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• pp.83-93
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• 2013

By comparing Wiener's MMSE on stochastic signal transmission with Shannon's mutual information first proved by C.E. Shannon in terms of information theory, connections between two approaches were investigated. What Wiener wanted to see in signal transmission in noisy channel is to try to capture fundamental limits for signal quality in signal estimation. On the other hands, Shannon was interested in finding fundamental limits of signal quantity that maximize the uncertainty in mutual information using the entropy concept in noisy channel. First concern of this paper is to show that in deriving limits of Shannon's point to point fundamental channel capacity, Shannon's mutual information obtained by exploiting MMSE combiner and Wiener filter's MMSE are interelated by integro-differential equantion. Then, At the meeting point of Wiener's MMSE and Shannon's mutual information the upper bound of spectral efficiency and the lower bound of energy efficiency were computed. Choosing a proper lattice-type code of a mod-${\Lambda}$AWGN channel model and MMSE estimation of ${\alpha}$ confirmed to lead to the fundamental Shannon capacity limits.

• 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.39B no.12
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• pp.864-869
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• 2014

In this paper, we propose an OFDM system with a pre-equalizer which pre-distorting a transmission signal to compensate for the degradation of the system by the intersymbol interference and multi-path fading at the high-speed multimedia communications. We model an OFDM system by using C language, a simulation was performed. As a result, there was a performance of BER is about 7dB at $10^{-3}$, improved to $10^{-4}$ on the MMSE property also $10^{-3}$.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.4C
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• pp.414-423
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• 2009

This paper considers a linear precoding scheme that achieves near optimal sum rate. While the minimum mean square error (MMSE) precoding provides the better MSE performance at all signal-to-noise ratio (SNR) than the zero forcing (ZF) precoding, its sum rate shows superior performance to ZF precoding at low SNR but inferior performance to ZF precoding at high SNR, From this observation, we first propose a near optimal linear precoding scheme in terms of sum rate. The resulting precoding scheme regularizes ZF precoding to maximize the sum rate, resulting in better sum rate performance than both ZF precoding and MMSE precoding at all SNR ranges. To find regularization parameters, we propose a simple algorithm such that locally maximal sum rate is achieved. As a low complexity alternative, we also propose a simple power re-allocation scheme in the conventional regularized channel inversion scheme. Finally, the proposed scheme is tested under the presence of channel estimation error. By simulation, we show that the proposed scheme can maintain the performance gain in the presence of channel estimation error and is robust to the channel estimation error.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.9C
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• pp.743-748
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• 2008

This paper makes a research on the equivalent Wiener-Hopf equation which can obtain the coefficient of TDL filter on orthogonal input signal in terms of mean square error. Using this result, we can present the coefficient and error of TDL filter directly without inverse orthogonalization process on orthogonal input signal. We make a theoretical analysis on MMSE and show an Wiener-Hopf solution and the proposed equivalent one in mathematical example simultaneously.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.6C
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• pp.476-482
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• 2012

In this paper, we analyze and compare several co-channel interference mitigation algorithms for WBAN application in 2.4 GHz ISM frequency bands. ML (Maximum Likelihood), OC (Optimal Combining) and MMSE (Minimum Mean Square Error) has been considered for the possible techniques for interference cancellation in view of the trade off between the performance and the complexity of implementation. Based on the channel model of IEEE 802.15.6 standard, simulation results show that ML and OC attains the lower BER performance than that of MMSE if we assume the perfect channel estimation. But, ML and OC have the additional requirement of implementation for his own and other users's channel estimation process, hence, besides the BER performance, the complexity of implementation and the sensitivity to channel estimation error should be considered since it requires the simple and small sized equipment for WBAN system application. In addition, the gap of detection BER performance between ML, OC and MMSE is much decreased under the imperfect channel estimation if we adopt real channel estimation process, therefore, in order to apply to WBAN system, the trade off between the BER performance and complexity of implemetation should be seriously considered to decide the best co-channel interference cancellation for WBAN system application.