• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.2
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• pp.476-483
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• 2010

If the data are pre-whitened, then gradient adaptive algorithms which are simpler than higher order statistics algorithms can be used in adaptive blind signal estimation. In this paper, we propose a blind subband affine projection algorithm for multiple-input multiple-output adaptive equalization in the blind environments. All of the adaptive filters in subband affine projection equalization are decomposed to polyphase components, and the coefficients of the decomposed adaptive sub-filters are updated by defining the multiple cost functions. An infinite impulse response filter bank is designed for the data pre-whitening. Pre-whitening procedure through subband filtering can speed up the convergence rate of the algorithm without additional computation. Simulation results are presented showing the proposed algorithm's convergence rate, blind equalization and blind signal separation performances.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1962-1965
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• 2004

In this paper, the new algorithm for blind adaptive decorrelating parallel interference canceller detector in direct-sequence code division multiple access (DS-CDMA) synchronous communication systems is proposed. The goal of this paper is to improve the performance of the blind adaptive decorrelating parallel interference cancellation detector (BAD/PIC). The proposed blind adaptive decorrelating detector is using optimum step-size technique bootstrap algorithm as an initial stage of PIC, which does not require a training sequence. Therefore, this algorithm has a superior view of utilizing bandwidth and reduces the complexity of computation of inversion cross-correlation matrix. The computer simulation results show that the bit error rate performance of the proposed algorithm for the new structure of detector is better than that of the other detectors such as matched filters, the conventional PIC, and the blind adaptive decorrelating PIC detector.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.4C
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• pp.384-391
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• 2003

Blind channel identification and equalization attempt to identify the communication channel and to remove the inter-symbol interference caused by a communication channel without using any known trainning sequences. In this paper, we propose a blind adaptive channel identification and equalization algorithm with phase offset compensation for single-input multiple-output (SIMO) channel. It is based on the one-step forward multichannel linear prediction error method and can be implemented by an RLS algorithm. Phase offset problem, we use a blind adaptive algorithm called the constant modulus derotator (CMD) algorithm based on condtant modulus algorithm (CMA). Moreover, unlike many known subspace (SS) methods or cross relation (CR) methods, our proposed algorithms do not require channel order estimation. Therefore, our algorithms are robust to channel order mismatch.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.3B
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• pp.220-225
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• 2002

MUD(Multiuser detection) technology which locates desired signal and removes interference signal from multiple access signals increases system capacity and decreases multiple access effect. In this paper, we develop a blind adaptive multiuser detector for synchronous CDMA with a noise-whitened filter. To improve the symbol error probability performance, DFBD (Decision-Feedback Blind Adaptive Multiuser Detector) is proposed and compared with BD(Blind Adaptive Multiuser Detector). The proposed DFBD is slightly improved.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.3B
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• pp.259-266
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• 2002

In the CDMA system, the Multiple access interference(MAI) causes system performance and capacity degradation. One of the MAI cancel method is a feedback detector that orthogonal decision-feedback detector(ODFD) and Deocrrelating decision-feedback detector(DDFD) have been studied by now. In this paper, we propose a blind adaptive ODFD(BA-ODFD) with blind equalizer combined ODFD, Also we simulate the operation of BA-ODFD in AWGN channel and Rayleigh (tiding channel. and compare blind adaptive ODFD with blind adaptive DDFD.

• Proceedings of the IEEK Conference
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• 2001.06a
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• pp.69-72
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• 2001

Blind equalization of transmission channel is important in communication areas and signal processing applications because it does not need training sequence, nor does it require a priori channel information. Recently, Tong et al. proposed solutions for this problem exploit the diversity induced by antenna array or time oversampling, leading to the second order statistics techniques, fur example, subspace method, prediction error method, and so on. The linear prediction error method is perhaps the most attractive in practice due to the insensitive to blind equalizer length mismatch as well as for its simple adaptive filter implementation. Unfortunately, the previous one-step prediction error method is known to be limited in arbitrary delay. In this paper, we induce the optimal delay, and propose the adaptive blind equalizer with multi-step linear prediction using RLS-type algorithm. Simulation results are presented to demonstrate the proposed algorithm and to compare it with existing algorithms.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.8A
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• pp.753-762
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• 2002

Blind equalization of transmission channel is important in communication areas and signal processing applications because it does not need training sequences, nor dose it require a priori channel information. In this paper, an adaptive blind MMSE channel equalization technique based on second-order statistics in investigated. We present an adaptive blind MMSE channel equalization using multichannel linear prediction error method for estimating cross-correlation vector. They can be implemented as RLS or LMS algorithms to recursively update the cross-correlation vector. Once cross-correlation vector is available, it can be used for MMSE channel equalization. Unlike many known subspace methods, our proposed algorithms do not require channel order estimation. Therefore, our algorithms are robust to channel order mismatch. Performance of our algorithms and comparisons with existing algorithms are shown for real measured digital microwave channel.

• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.47-50
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• 1999

Adaptive channel equalization accomplished without resorting to a training sequence is known as blind equalization. The Constant Modulus Algorithm(CMA) and Modified CMA(MCMA) are widely referenced algorithms for blind equalization of a QAM system. This paper proposes a hybrid scheme of CMA and MCMA with Carrier Recovery that is robust for high level QAM with low steady state tracking error.

• ETRI Journal
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• v.42 no.1
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• pp.26-35
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• 2020

Herein, we consider uplink multiuser massive multiple-input multiple-output systems when multiple users transmit information symbols to a base station (BS) by applying simple space-time block coding (STBC). At the BS receiver, two detection filters for each user are used to detect the STBC information symbols. One of these filters is for odd-indexed symbols and the other for even-indexed symbols. Using constrained output variance metric minimization, we first derive a special relation between the closed-form optimal solutions for the two detection filters. Then, using the derived special relation, we propose a new blind adaptive algorithm for implementing the minimum output variance-based optimal filters. In the proposed adaptive algorithm, filter weight vectors are updated only in the region satisfying the special relation. Through a theoretical analysis of the convergence speed and a computer simulation, we demonstrate that the proposed scheme exhibits faster convergence speed and lower steady-state bit error rate than the conventional scheme.

• Proceedings of the IEEK Conference
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• 2001.06a
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• pp.317-320
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• 2001

Blind adaptive channel identification of communication channels is a problem of important current theoretical and practical concerns. Recently proposed solutions for this problem exploit the diversity induced by antenna array or time oversampling leading to the so-called, second order statistics techniques. And adaptive blind channel identification techniques based on a off-line least-squares approach have been proposed. In this paper, a new approach is proposed that is based on eigenvalue decomposition. And the eigenvector corresponding to the minimum eigenvalue of the covariance matrix of the received signals contains the channel impulse response. And we present a adaptive algorithm to solve this problem. The performance of the proposed technique is evaluated over real measured channel and is compared to existing algorithms.