• Journal of Communications and Networks
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• v.5 no.2
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• pp.157-166
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• 2003

This paper deals with the problem of channel identification for Single Input Multiple Output (SIMO) slow fading channels using clustering algorithms. Due to the intrinsic memory of the discrete-time model of the channel, over short observation periods, the received data vectors of the SIMO model are spread in clusters because of the AWGN noise. Each cluster is practically centered around the ideal channel output labels without noise and the noisy received vectors are distributed according to a multivariate Gaussian distribution. Starting from the Markov SIMO channel model, simultaneous maximum ikelihood estimation of the input vector and the channel coefficients reduce to one of obtaining the values of this pair that minimizes the sum of the Euclidean norms between the received and the estimated output vectors. Viterbi algorithm can be used for this purpose provided the trellis diagram of the Markov model can be labeled with the noiseless channel outputs. The problem of identification of the ideal channel outputs, which is the focus of this paper, is then equivalent to designing a Vector Quantizer (VQ) from a training set corresponding to the observed noisy channel outputs. The Linde-Buzo-Gray (LBG)-type clustering algorithms [1] could be used to obtain the noiseless channel output labels from the noisy received vectors. One problem with the use of such algorithms for blind time-varying channel identification is the codebook initialization. This paper looks at two critical issues with regards to the use of VQ for channel identification. The first has to deal with the applicability of this technique in general; we present theoretical results for the conditions under which the technique may be applicable. The second aims at overcoming the codebook initialization problem by proposing a novel approach which attempts to make the first phase of the channel estimation faster than the classical codebook initialization methods. Sample simulation results are provided confirming the effectiveness of the proposed initialization technique.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.43 no.8 s.350
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• pp.69-76
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• 2006

In this paper, we propose blind adaptation strategies for decision feedback equalizer (DFE) optimizing the operation mode between acquisitionand tracking modes based on adjustable soft decision devices. The proposed schemes select an optimal soft decision device to generate feedback samples for the DFE at a given noise to signal ratio, and apply corresponding adaptation rules which combine a blind infinite impulse response (IIR) filtering adaptation and the decision-directed least mean squared (DD-LMS) DFE adaptation. These adaptation approaches attempt to achieve not only smooth transition between acquisition and tracking of DFE but also mitigation of error propagation.

• Journal of The Institute of Information and Telecommunication Facilities Engineering
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• v.8 no.4
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• pp.201-206
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• 2009

The third generation mobile communications system requiring the reliable multimedia data transmission has provided with the reliable voice, data and video services over the variable propagation environment. However the broadband wireless multiple access technologies cause Inter Symbol Interference (ISI) or Multiple Access Interference (MAI) to degrade the performance of W-CDMA (Code Division Multiple Access) system. Constant Modulus Algorithm (CMA) which is frequently used as the adaptive blind equalizers to remove the interfering signal has ill-convergence phenomenon without proper initialization. In this paper, new blind equalization method based on conventional CMA is proposed to improve the channel efficiency, and through computer simulation this is tested over the time varying fading environment of mobile communication system. Consequently, new blind equalization method into concatenated Kalman filter with CMA is verified better than conventional CMA through adopting minimum mean square errors and eye-pattern obtained from algorithm are compared.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.3
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• pp.419-424
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• 2015

The Decision-directed (DD) algorithm is known to be not effective to initialize a blind equalizer in the channel conditions when the eye diagram of received signals is completely closed because it can not open the eye diagram enough. In this paper, we propose a new error to replace the error of the conventional DD algorithm. The new DD error is the conventional DD error scaled by the modulus of symbol decision, new DD algorithm using this error is effective to open the closed eye diagram in early stage of equalization unlike the conventional DD. The new DD algorithm appling the new error is showed excellent convergence characteristics as compared to the CMA widely used in blind initialization, particularly, is useful for equalization of signals having multimodulus. The performance of the new DD algorithm is verified through the simulation for the higher-order QAM signals.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.1
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• pp.29-35
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• 2006

The third generation mobile communications system requiring the reliable multimedia data transmission has provided with the reliable voice, data and video services over the variable propagation environment. However the broadband wireless multiple access technologies cause Inter Symbol Interference(ISI) or Multiple Access Interference(MAI) to degrade the performance of CDMA(Code Division Multiple Access) system. Constant Modulus Algorithm which is frequently used as the adaptive blind equalizers to remove the interfering signal has ill-convergence phenomenon without proper initialization. In this paper, new blind equalization method based on conventional CMA is proposed to improve the channel efficiency, and through computer simulation this is tested over the time varying fading environment of mobile communication system. consequently, new blind equalization method into concatenated Kalman filter with CMA is verified better than conventional CMA through adopting minimum mean square errors and eye-pattern obtained from algorithm are compared.

• Journal of The Institute of Information and Telecommunication Facilities Engineering
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• v.7 no.1
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• pp.15-22
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• 2007

The third generation mobile communications system requiring the reliable multimedia data transmission has provided with the reliable voice, data and video services over the variable propagation environment. However the broadband wireless multiple access technologies cause Inter Symbol Interference(ISI) or Multiple Access Interference(MAI) to degrade the performance of CDMA(Code Division Multiple Access) system. Constant Modulus Algorithm which is frequently used as the adaptive blind equalizers to remove the interfering signal has ill-convergence phenomenon without proper initialization. In this paper, new blind equalization method based on conventional CMA is proposed to improve the channel efficiency, and through computer simulation this is tested over the time varying fading environment of mobile communication system. consequently, new blind equalization method into concatenated Kalman filter with CMA is verified better than conventional CMA through adopting minimum mean square errors and eye- pattern obtained from algorithm are compared.

• The Journal of the Acoustical Society of Korea
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• v.39 no.2
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• pp.120-130
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• 2020

This paper solves the problem in underdetermined convolutive mixture by improving the disadvantages of the multichannel nonnegative matrix factorization technique widely used in blind source separation. In conventional researches based on Spatial Covariance Matrix (SCM), each element composed of values such as power gain of single channel and correlation tends to degrade the quality of the separated sources due to high variance. In this paper, level and frequency normalization is performed to effectively cluster the estimated sources. Therefore, we propose a novel SCM and an effective distance function for cluster pairs. In this paper, the proposed SCM is used for the initialization of the spatial model and used for hierarchical agglomerative clustering in the bottom-up approach. The proposed algorithm was experimented using the 'Signal Separation Evaluation Campaign 2008 development dataset'. As a result, the improvement in most of the performance indicators was confirmed by utilizing the 'Blind Source Separation Eval toolbox', an objective source separation quality verification tool, and especially the performance superiority of the typical SDR of 1 dB to 3.5 dB was verified.