• Journal of information and communication convergence engineering
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• 제8권2호
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• pp.136-139
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• 2010

We derived Stop-and-go normalized DD, dual-mode normalized Sato, dual-mode NCMA blind equalization algorithm for complex data in this research. And then, the convergence characteristics of the proposed SG-NDD, dual-mode NSato blind equalization algorithms are compared with those of SG-DD, dual-mode Sato algorithms. In general, the normalized blind equalization algorithms have better convergence characteristics than the conventional algorithms.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2001년도 추계종합학술대회
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• pp.315-318
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• 2001

기준신호를 필요로 하지 않는 블라인드 방식의 새로운 LMS 및 MMSE 알고리즘을 제안한다. 디지털 신호의 Finite Constellation 특성을 이용하여 Projection 방식으로 본 알고리즘을 구현했다. 제안 알고리즘의 성능을 증명하기 위해서, AWGN 채널과 다중경로 Rayleigh Fading 채널상황에서 시뮬레이션을 수행하였다.

• 한국통신학회논문지
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• 제27권8A호
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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.

• 한국컴퓨터산업학회논문지
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• 제2권4호
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• pp.537-546
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• 2001

DSSS(Direct-Sequence Spread-Spectrum) CDMA 시스템에서 MAI(Multiple Access Interference)와 원근 문제를 해결할 수 있는 단일-사용자 검파에 적합한 알고리즘으로 Griffiths’알고리즘과 LCCMA(Linearly Constrained Constant Modulus Algorithm)에 제안되었으며 MMSE 검파기에 적합한 다중-사용자 알고리즘인 MOE 알고리즘 또한 제안되었다. 본 논문은 training sequence의 요구 없이 시스템의 성능을 향상시킬 수 있는 이 세 가지 Blind 적합 알고리즘을 가지고 간섭 사용자의 수나 원하는 사용자의 데이터 업데이트율에 따라 각각의 알고리즘별 성능을 비교 분석하였다. 시뮬레이션 결과 간섭 사용자수와 원하는 사용자의 업데이트율의 변화에 따라 모두 LCCMA 알고리즘이 뛰어난 성능을 보았다. Blind 적용은 하나의 training sequence의 필요성을 없앰으로써 더욱 융통성 있는 네트웍디자인을 가능케 했다.

• Journal of Communications and Networks
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• 제12권5호
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• pp.459-465
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• 2010

A new blind equalization algorithm that is based on maximizing the probability that the constant modulus errors concentrate near zero is proposed. The cost function of the proposed algorithm is to maximize the probability that the equalizer output power is equal to the constant modulus of the transmitted symbols. Two blind information-theoretic learning (ITL) algorithms based on constant modulus error signals are also introduced: One for minimizing the Euclidean probability density function distance and the other for minimizing the constant modulus error entropy. The relations between the algorithms and their characteristics are investigated, and their performance is compared and analyzed through simulations in multi-path channel environments. The proposed algorithm has a lower computational complexity and a faster convergence speed than the other ITL algorithms that are based on a constant modulus error. The error samples of the proposed blind algorithm exhibit more concentrated density functions and superior error rate performance in severe multi-path channel environments when compared with the other algorithms.

• ETRI Journal
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• 제34권1호
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• pp.130-133
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• 2012

Recently, several noise-robust adaptive multichannel LMS algorithms have been proposed based on the spectral flatness of the estimated channel coefficients in the presence of additive noise. In this work, we propose a general form for the algorithms that integrates the existing algorithms into a common framework. Computer simulation results are presented and demonstrate that a new proposed algorithm gives better performance compared to existing algorithms in noisy environments.

• 한국통신학회논문지
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• 제38A권1호
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• pp.26-32
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• 2013

출력 샘플과 수신단에서 랜덤한 순서로 발생된 심볼의 정보 포텐셜을 기반으로 한 블라인드 알고리즘은, 바이어스된 충격성 잡음이 채널에 더해질 때, 정보 포텐셜을 바탕으로 한 비용함수에 바이어스된 신호를 처리할 변수가 포함되어 있지 않아 성능저하를 겪게 된다. 이러한 바이어스된 충격성 잡음에 대한 강건성을 목표로, 이 논문에서는 수정된 정보 포텐셜을 제안하고, 이 제안된 정보 포텐셜에 기반하여 증강된 필터 구조와 랜덤 심볼을 사용한 새로운 블라인드 알고리즘을 도출하였다. 다중 경로 채널의 블라인드 등화에 대한 시뮬레이션 결과로부터, 제안된 정보 포텐셜에 기반한 블라인드 알고리즘이 바이어스된 강한 충격성 잡음 환경에서 탁월한 수렴 성능을 나타냈다.

• 전기학회논문지
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• 제59권2호
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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.

• 한국통신학회논문지
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• 제28권4C호
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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.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2000년도 ITC-CSCC -2
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• pp.753-756
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• 2000

In this paper we present and compare two different spatio-temporal decorrelation learning algorithms for updating the weights of a linear feedforward network with FIR synapses (MIMO FIR filter). Both standard gradient and the natural gradient are employed to derive the spatio-temporal decorrelation algorithms. These two algorithms are applied to multichannel blind deconvolution task and their performance is compared. The rigorous derivation of algorithms and computer simulation results are presented.