• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.4
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• pp.83-89
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• 2013

An adaptive blind equalization is a technique using to minimize the Inter-symbol Interference occurred on a communication channel in the transmission of the high speed digital data. In this paper, we propose a blind equalization more improving performance of the conventional MSAGF-MMA adaptive blind equalization algorithm by applying a multiple step size. This algorithm apply a LMS algorithm with a several step size according to each region divided by absolute values of decision-directed error to MSAGF-MMA. By computer simulation, it is confirmed that the proposed algorithm has a performance highly enhanced in terms of a convergence speed, a residual ISI and a residual error and an ensemble averaged MSE in a steady status compared with MMA and MSAGF-MMA.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.7
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• pp.1287-1294
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• 2006

In many current wireless packet data system, the short-burst transmissions are used, and training overhead is very significant for such short burst formats. So, the availability of the short training sequence and the fast converging algorithm is essential in the adaptive equalizer. In this paper, the new equalizer algorithm is proposed to improve the performance of a MTLMS (multiple-training least mean square) based DFE (decision feedback equalizer)using the short training sequence. In the proposed method, the output of the DFE is fed back to the LMS (least mean square) based adaptive DEF loop iteratively and used as an extended training sequence. Instead of the block operation using ML (maximum likelihood) estimator, the low-complexity adaptive LMS operation is used for overall processing. Simulation results show that the perfonnance of the proposed equalizer is improved with a linear computational increase as the iterations parameter in creases and can give the more robustness to the time-varying fading.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.5
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• pp.1061-1066
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• 2014

Transmission characteristics of the sound propagation is very complicate and sparse in shallow water. To increase the performance of underwater acoustic communication system, lots of channel estimation technique has been proposed. In this paper, we proposed the channel estimation based on LMS(Least Mean Square) algorithm which has faster convergence speed than conventional sparse-aware LMS algorithms. The proposed method combines $L_p$-norm LMS with soft decision process. Simulation was performed by using the sound velocity profile which acquired in real sea trial. As a result, we confirmed that the proposed method shows the improved performance and faster convergence speed than conventional methods.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.18 no.1
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• pp.154-160
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• 2004

In this paper, implementation of active noise curtains using multiple channel adaptive filters is presented. The same numbers of single channel LMS algorithms as control loudspeakers is used instead of a multi-channel LMS algorithm to reduce the computational burden of adaptive filter algorithms. In general, a multi-channel LMS algorithm is usually used in active noise control system. but this algorithm has much more computational complexity. The single channel control techniques have less amount of DSP calculation, compared to multiple channel control techniques. A stabilizing procedure for adaptive IIR filters is also proposed to improve the stability of recursive LMS algorithms. Both experimental results of two control techniques using TMS320VC33 digital signal processor show the similar noise reduction, but the single channel control techniques are more efficient in practical active noise curtain applications

• The Journal of the Acoustical Society of Korea
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• v.15 no.1
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• pp.46-53
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• 1996

Adaptive LMS algorithm has been used in many application areas due to its low complexity. In this paper input signal is transformed into the subbands with arbitrary bandwidth. In each subbands the dynamic range can be reduced, so that the independent filtering in each subbands has faster convergence rate than the full band system. The DCT transform domain LMS adaptive filtering has the whitening effect of input signal at each bands. This leads the convergence rate to very high speed owing to the decrease of eigen value spread Finally, the filtered signals in each subbands are synthesized for the output signal to have full frequency components. In this procedure wavelet filter bank guarantees the perfect reconstruction of signal without any interspectra interference. In simulation for the case of speech signal added additive white gaussian noise, the suggested algorithm shows better performance than that of conventional NLMS algorithm at high SNR.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.7
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• pp.1321-1327
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• 2009

In this paper, as the mobile communication service is widely used and the demand for wireless repeaters is rapidly increasing because of the easiness of extending service areas. But a wireless repeater has a problem the oscillation due to feedback signal. We proposed a new hybrid interference canceller using the adaptive filter with CMA(Constant Modulus Algorithm)-Grouped LMS(Least Mean Square) algorithm in the adaptive interference canceller. The proposed interference canceller has better channel adaptive performance and a lower MSE(Mean Square Error) than conventional structure because it uses the cancellation method of Grouped LMS algorithm. The proposed detector uses the LMS algorithms with two different step size to reduce mean square error and to obtain fast convergence. This structure reduces the number of iterations for the same MSE performance and hardware complexity compared to conventional nonlinear interference canceller.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.9 no.4
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• pp.11-22
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• 1999

Least-mean-square(LMS) adaptive filters have proven to be extremely useful in a number of signal processing tasks. However LMS adaptive filter suffer from a slow rate of convergence for a given steady-state mean square error as compared to the behavior of recursive least squares adaptive filter. In this paper an efficient signal interference control technique is introduced to improve the convergence speed of LMS algorithm with tap weighted vectors updating which were controled by reusing data which was abandoned data in the Adaptive transversal filter in the scheme with data recycling buffers. The computer simulation show that the character of convergence and the value of MSE of proposed algorithm are faster and lower than the existing LMS according to increasing the step-size parameter $\mu$ in the experimentally computed. learning curve. Also we find that convergence speed of proposed algorithm is increased by (B+1) time proportional to B which B is the number of recycled data buffer without complexity of computation. Adaptive transversal filter with proposed data recycling buffer algorithm could efficiently reject ISI of channel and increase speed of convergence in avoidance burden of computational complexity in reality when it was experimented having the same condition of LMS algorithm.

• Journal of IKEEE
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• v.17 no.2
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• pp.145-150
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• 2013

In the paper, we propose a new CSS(Complex Signed-Signed) CMA(Constant Modulus Algorithm) algorithm for ICS(Interference Cancellation System). When the repeater get the feedback signal, the CSS CMA algorithm is proposed at the ICS repeater using DSP(Digital Signal Processing) for the removal of interfering signals from the feedback paths. The proposed CSS CMA algorithm improved performances and hardware complexity by adjusting step size values. the steady state MSE(Mean Square Error) performance of the proposed CSS CMA algorithm with step size of 0.00043 is about 4dB better than the conventional CMA algorithm. And the proposed Complex Signed Signed CMA algorithm requires 1950 ~ 2150 less iterations than the LMS(Least Mean Square) and Signed LMS(Normalized Least Mean Square) algorithms at MSE of -25dB.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.15 no.5
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• pp.34-40
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• 2001

In this paper, a narrowband active noise control system to reduce the noise in thermal power plants is proposed. The narrowband active noise control system contains rectangular wave generator and has a multi channel feed forward adaptive algorithms which uses the adjoint LMS algorithm. Although the effectiveness have been proven in the filtered-X LMS broadband active noise control system, this algorithm has much more computational complexity than that of narrowband active noise control system. The proposed active control system that uses the adjoint LMS algorithm, compared to the previous broadband active noise control system, not only is more effective in controlling narrowband noise but also has a more stable structure. Adaptive filter contains the FIR structure and IIR structure for primary and secondary path models. The simulation proves the effectiveness of the proposed algorithm.

• Proceedings of the KAIS Fall Conference
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• 2008.11a
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• pp.164-166
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• 2008

소음은 현대 사회에서 쉽게 접하게 되는 환경 오염원이다. 능동소음제어(Active Noise Control)는 발생된 소음을 제거하기 위해 구현이 간단한 LMS 알고리즘을 많이 사용하고 있다. 그러나 LMS 알고리즘은 수렴 속도와 소음신호의 변화속도에 따라 발산의 위험을 가지고 있다. 본 논문에서는 이러한 LMS의 문제점을 보완하기 위해 경험 모드 분석법을 이용한 feedback FXLMS(Filtered-X Least Mean Square) 알고리즘을 제안하였다. 소음제거 시스템의 출력단에서 검출된 잔차소음을 경험 모드 분석법(Empirical Mode Decomposition)을 이용하여 IMF 신호들로 분해하고, 분해된 각 신호를 FXLMS 알고리즘을 이용하여 수렴시킨 후, 결과들을 다시 결합하여 소음 제거에 이용하였다. 각각의 IMF 신호를 FXLMS 알고리즘으로 수렴시킬 때 수렴속도에 변화를 주어 소음제거의 효율성을 높였다. 제안한 알고리즘을 Matlab을 이용하여 시뮬레이션하였고 기존의 FXLMS알고리즘보다 향상된 수렴속도 및 안정성을 가짐을 입증하였다.