• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2002.11a
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• pp.27-30
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• 2002

본 논문은 8VSB 방식의 디지털 지상파 TV 시스템에서 수신 채널 등화기의 수렴속도와 MSE(Mean Square Error) 성능을 개선하기 위하여 DCT HLMS DFE(Discrete Cosine Transform Hierarchical Least Mean Square)를 제안한다. 즉, 다중경로 수신 환경에서 수신 신호의 왜곡 및 지연에 따른 입력 데이터에 대한 고유값 확산을 감소하기 위하여 DCT와 전력추정 알고리즘을 사용하고 또한, LMS(Least Mean Square) DFE를 계층적 구조의 서브필터로 변형함으로써 수신 데이터상관 행렬의 고유값 범위를 줄인다. 전산모의 실험 결과 제안한 DCT HLMS DFE는 ATTC(Advanced Television Test Center)가 제시한 디지털 지상파 TV 방송 채널 중 A 채널 하에서 기존의 LMS DFE 보다 수렴속도와 MSE 성능이 개선됨을 알 수 있다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2010.11a
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• pp.219-222
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• 2010

OFDM시스템의 대안으로, SC-FDE시스템은 주파수 선택적 페이딩 환경에서 구현상의 복잡도가 크지 않으면서 낮은 PAPR로 다중 경로 지연에 의한 영향을 완화시키기 위한 기술로 연구되어 왔다. SC-FDE시스템에서 보호 구간으로 PN신호를 훈련 심볼(Training Sequence)로 둠으로써 CP에 비해 빠른 동기화와 채널 추정에 사용될 수 있는 장점이 있으며, 채널 추정을 위해 Correlation과 LMS기법을 동시에 적용함으로써 에러가 최소가 되기까지 수렴 시간을 줄일 수 있다. 본 논문에서는 PN시퀀스를 기반으로 추정한 채널 값으로, ISI를 효과적으로 제거할 수 있는 MMSE-FDE 등화 기법을 제안한다. SFN 채널 환경과 같이 스펙트럼 널이 강한 다중 경로 페이딩환경에서 ISI를 선 제거 하는 ISI cancellation 기법을 통해 정확한 SNR추정을 할 수 있고, 이를 통해 MMSE-FDE 등화 성능을 향상 시킬 수 있다.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.39 no.1
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• pp.35-47
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• 2002

This paper proposes a self organizing RBF neural network equalizer for the equalization of digital communications. It is the most important for the equalizer using the RBF neural network to estimate the RBF centers correctly and quickly, which are the desired channel states. However, the previous RBF equalizers are not used in the actual communication system because of some drawbacks that the number of channel states has to be known in advance and many centers are necessary. Self organizing neural network equalizer proposed in this paper can implement the equalization without prior information regarding the number of channel states because it selects RBF centers among the signals that are transmitted to the equalizer by the new addition and removal criteria. Furthermore, the proposed equalizer has a merit that is able to make a equalization with fewer centers than those of prior one by the course of the training using LMS and clustering algorithm. In the linear, nonlinear and standard telephone channel, the proposed equalizer is compared with the optimal Bayesian equalizer for the BER performance, the symbol decision boundary and the number of centers. As a result of the comparison, we can confirm that the proposed equalizer has almost similar performance with the Bavesian enualizer.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.26 no.6B
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• pp.776-783
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• 2001

통신 채널에서 블라인드 채널 등화는 훈련신호나 채널의 사전 정보가 필요하지 않기 때문에 전송 효율을 높일 수 있는 매우 중요한 문제이다. 선형 예측 오차 방법은 블라인드 등화기의 차수 추정 오차에 대하여 강인하며 적응 알고리듬을 이용하여 효율적으로 구현할 수 있는 장점이 있다. 시스템 지연은 등화기의 성능에 많은 영향을 끼치지만 기존의 one-step 선형 예측은 등화기의 임의의 시스템 지연에 대해서는 구현할 수 없는 단점이 있다. 순방향 선형 예측과 역방향 선형 예측은 각각 시스템 지연이 0과 최대인 블라인드 등화와 관련이 있다. 그러나 Multistep 예측은 임의의 시스템 지연을 갖는 블라인드 등화기를 구현할 수 있는 장점이 있다. 본 논문에서는 최적의 시스템 지연을 구한 후 RLS 알고리듬과 LMS 알고리듬을 이용한 multistep 선형 예측을 이용한 블라인드 채널 등화기를 제안하였다. 그리고 기존의 알고리듬들과 본 논문에서 제안한 알고리듬의 성능을 모의실험을 통하여 기존의 알고리듬들과 비교·평가하였다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.2
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• pp.237-245
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• 2012

This paper describes an acoustic echo canceller with double-talk by the blind signal separation. The acoustic echo canceller is deteriorated or diverged in the double-talk period. So we use the blind signal separation to estimate the near-end speech signal and to eliminate the estimated signal from the residual signal. The blind signal separation extracts the near-end signal with dual microphones by the iterative computations using the 2nd order statistical character. Because the mixture model of blind signal separation is multi-channel in the closed reverberation environment, we used the copied coefficients of echo canceller without computing the separation coefficients. By this method, the acoustic echo canceller operates irrespective of double-talking. We verified performances of the proposed acoustic echo canceller by simulations. The results show that the acoustic echo canceller with this algorithm detects the double-talk periods thoroughly, and then operates stably in the normal state without the divergence of coefficients after ending the double-talking. And it shows the ERLE of averagely 20dB higher than the normal LMS algorithm.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.44 no.1
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• pp.138-145
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• 2007

Wireless transmission system using the multipath channel is affected ISI due to the delay spread. So we use a decision feedback equalizer which consist of decision part and feedback filter for remove the ISI effectively. In this paper, we propose a improved adaptive decision feedback equalizer to mitigate ISI effectively. The proposed adaptive decision feedback equalizer is construct by using soft decision device and hierarchical feedback filter based on MMSE sub-optimal equalizer using the LMS algorithm. Soft decision device mitigate the error propagation in feedback filter by incorrectly detected decision symbol and feedback filter which is divided two step independently mitigate the ISI by using a adaptive algorithm. As a result this structure shows better performance than conventional decision feedback equalizer by mitigating the error propagation in filter cause incorrectly detecting symbol. and we get the MSE more rapidly by using larger step-size due to reduce the number of feedback filter tap. In computer simulation, we compare the bit error rate performance of proposed decision feedback equalizer with conventional one on the S-V channel model for UWB system.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1469-1472
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• 1997

For system state estimation, existing LMS type esimators widely used. For example Kalman filter is one of them. In this paper, a state estimator is derived for the H$_{\infty}$ norm of the estimation error spectrum matrix to be minimized. For the solution of this problem classical NP interpolation problem is used. Also, by deriving the duality between the filter problem and the well-known H$_{\infty}$ control problem, another solution is obtained. The computer simuation results show that H$_{\infty}$ estimator has less estimation error and so this is better than the existing Kalman filter estimator.or.

• The Journal of the Acoustical Society of Korea
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• v.18 no.7
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• pp.45-55
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• 1999

In this paper, we used the WLMS(Wavelet domain Least Mean Square) adaptive filter based on the wavelet transform to cancel grain noise. Usually, grain noise occurs in changes of the crystalline structure of metals in high temperature environment. It makes the detection of flaw difficult. The WLMS adaptive filtering algorithm establishes the faster convergence rate by orthogonalizaing the input vector of adaptive filter as compared with that of LMS adaptive filtering algorithm in time domain. We implemented the WLMS adaptive filter by using the delayed version of the primary input vector as the reference input vector and then implemented the CA-CFAR(Cell Averaging- Constant False Alarm Rate) threshold estimator. CA-CFAR threshold estimator enables to detect the flaw and back echo signals automatically. Here, we used the output signals of adaptive filter as its input signal. To Cow the statistical characteristic of ultrasonic signals corrupted by grain noise, we performed run test. The results showed that ultrasonic signals are nonstationary signal, that is, signals whose statistical properties vary with time. The performance of each filter is appreciated by the signal-to-noise ratio. After LMS adaptive filtering in time domain, SNR improves to about 2-3㏈ but after WLMS adaptive filtering in wavelet domain, SNR improves to about 4-6㏈.

• Proceedings of the IEEK Conference
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• 2007.07a
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• pp.119-120
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• 2007

The operation of Interference cancellation algorithm for wireless repeater cancellation depends on either existing correlation properties between desired signal and reference signal or not At the time, due to the correlation properties at the ICS system, adaptive algorithms without considering system delay do not function properly. Thus, this system should be oscillated. In this paper, to solve these problems, we use the delayed least mean square algorithm. For the best performance of ICS, the system delays must be estimated. To efficiently estimate the delay of ICS, we use relations between bandwidth and correlation properties of the received signal.

• The Journal of the Acoustical Society of Korea
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• v.7 no.4
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• pp.31-53
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• 1988

In this work we study extensively the structures and performance characteristics of the block least mean-square (BLMS) adaptive digital filters (ADF's) that can be realized efficiently using the fast Fourier transform (FFT). The weights of a BLMS ADF realized using the FFT can be adjusted either in the time domain or in the frequency domain, leading to the time-domain BLMS(TBLMS) algorithm or the frequency-domain BLMS (FBLMS) algorithm, respectively. In Part Ⅰof the paper, we first present new results on the overlap-add realization and the number-theoretic transform realization of the FBLMS ADF's. Then, we study how we can incorporate the concept of different frequency-weighting on the error signals and the self-orthogonalization of weight adjustment in the FBLMS ADF's , and also in the TBLMS ADF's. As a result, we show that the TBLMS ADF can also be made to have the same fast convergence speed as that of the self-orthogonalizing FBLMS ADF. Next, based on the properties of the sectioning operations in weight adjustment, we discuss unconstrained FBLMS algorithms that can reduce two FFT operations both for the overlap-save and overlap-add realizations. Finally, we investigate by computer simulation the effects of different parameter values and different algorithms on the convergence behaviors of the FBLMS and TBLMS ADF's. In Part Ⅱ of the paper, we will analyze the convergence characteristics of the TBLMS and FBLMS ADF's.