• Journal of Advanced Navigation Technology
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• v.12 no.1
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• pp.22-27
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• 2008

This paper presents adaptive-MMOSPRED method for prediction of resource demands requested by multimedia calls, and shows the performance of the call admission control based on proposed resource prediction method in multimedia wireless networks. The proposed method determines (I-CDP) random variables of the standard normal distribution by using LMS algorithm that minimize errors of prediction in resource demands, while parameters in an existing method are constant all through the prediction time. Our simulation results show that prediction error in adaptive-MMOSPRED method is much smaller than in fixed-MMOSPRED method. Also we can see via simulation the CAC performance based on the proposed method improves the new call blocking performance compared with the existing method under the desired handoff dropping probability.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.2
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• pp.284-292
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• 2003

In this paper, we carried out the numerical examination of the initial value setting-up method to extend the range of optimal step parameter in a adaptive system which is controlled by LMS algorithm. For initial value setting-up methods, the general method which select the initial value randomly and the other method which applies the approximate value obtained from the direct method to initial value, were used. And then, we compared to the ranges of step parameter setting, the convergence speeds of mean-square-error, and the stabilities during the convergence process when the initial values were applied to the optimal directivity synthesis problem. According to the numerical simulation results, the initial value setting-up method by means of the direct method provides wider range for the step parameter, more efficient capability for convergence and stability, and more error correction ability than the general method.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.05a
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• pp.326-329
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• 2002

Engine noise is one of the major causes of the interior noise, and so has been studied in various ways in recent days. Recently Intake noise has been extensively studied to reduce the engine noise. Conventional method to reduce the noise is adding several resonators to the induction system. However this causes a reduction of engine output power and an increase of fuel consumption. In this study, the prototype of Active Intake Noise Control System is developed by using the Filtered-x LMS algorithm to reduce the Intake noise during acceleration. Intake noise is more excessively increased when the engine is rapidly accelerated. So, Normalized LMS algorithm is applied to improve the control performance under the rapid acceleration.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.3
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• pp.97-104
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• 2007

Adaptive echo canceller(AEC) has become an important component in speech communication systems, including mobile phones and speech recognition. In these applications, the acoustic echo path has a long impulse response. We propose a moving-averge least mean square(MVLMS) algorithm with a detection method for acoustic echo cancellation. Using, the result of the tests that used colored input models clearly shows that the MVLMS detection algorithm has convergence performance superior to the least mean square(LMS) detection algorithm alone. Although the computational complexity of the new MVLMS algorithm is only slightly greater than that of the standard LMS detection algorithm, the new algorithm confers a significant improvement in stability.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.26 no.12A
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• pp.1990-1999
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• 2001

This paper presents a dynamic simulation loop that gives tracking results of 2-color concentric annular ring (CAR) reticle seeker. Our simulation tool includes the target/flare model and a proportional navigation guidance (PNG) loop. The CAR reticle system performances and the flare effects are analyzed in various scenarios. When a flare is present in the field of view (FOV), the simulation results show that the reticle seeker cannot keep a precise target tracking. In this paper, we propose 2-color counter-countermeasure (CCM) using the least mean square (LMS) method to cope with a presence of IR flare. The proposed method makes a simultaneous process in two infrared (IR) wavelength bands: MWIR add SWIR. The simulation results have shown that our adaptive IRCCM algorithm can achieve an effective cancellation of the flare signal with a relatively high intensity.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2005.11a
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• pp.551-554
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• 2005

The method of the reduction of the automotive induction noise can be classified by the method of passive control and the method of active control. However, the passive control method has a demerit to reduce the effect of noise reduction at low frequency (below 500Hz) range and to be limited by a space of the engine room. Whereas, the active control method can overcome the demerit of passive control method. The algorithm of active control is mostly used the LMS (Least-Mean-Square) algorithm because the LMS algorithm can easily obtain the complex transfer function in real-time. Especially, When the Filtered-X LMS (FXLMS) algorithm is applied to an ANC system. However, the convergence performance of LMS algorithm goes bad when the FXLMS algorithm is applied to an active control of the induction noise under rapidly accelerated driving conditions. Thus Normalized FXLMS algorithm was developed to improve the control performance under the rapid acceleration. The advantage of Normalized FXLMS algorithm is that the step size is no longer constant. Instead, it varies with time. But there is one additional practical difficulty that can arise when a nonstationary input is used. If the input is zero for consecutive samples, then the step size becomes unbounded. So, in order to solve this problem. the Correlation FXLMS algorithm was developed. The Correlation FXLMS algorithm is realized by using an estimate of the cross correlation between the adaptation error and the filtered input signal to control the step size. In this paper, the performance of the Correlation FXLMS Is presented in comparison with that of the other FXLMS algorithms based on computer simulations.

• Transactions of the Korean Society of Automotive Engineers
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• v.11 no.6
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• pp.183-189
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• 2003

The study of the automotive noise reduction has been concentrated on the reduction of the automotive engine noise because the engine noise is the major cause of automotive noise. However, many studies of automotive engine noise led to the interest of the noise reduction of the exhaust and intake system. Recently, the active control method is used to reduce the noise of an automotive exhaust and intake system. It is mostly used the LMS(Least-Mean-Square) algorithm as an algorithm of active control because the LMS algorithm can easily obtain the complex transfer function in real-time. Especially, Filtered-X LMS (FXLMS) algorithm is applied to an Active Noise Control system. However, the convergence performance of LMS algorithm went bad when the FXLMS algorithm was applied to an active control of the induction noise under rapidly accelerated driving conditions. So, in order to solve this problem, the modified FXLMS algorithm is proposed. In this study, the improvement of the control performance using the modified FXLMS algorithm under rapidly and suddenly accelerated driving conditions was identified. Also, the performance of an active control using the LMS algorithm under rapidly accelerated driving conditions was evaluated through the theoretical derivation using a chirp signal to have similar characteristics with the induction noise signal.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.2 no.1
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• pp.71-77
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• 1998

In this Paper, the training principles and the control method of adaptive array antennas using the LMS and CMA algorithms for the $\pi$/4 QPSK signal is showed and the convergence characteristics, the adaptivity of directional pattern SINR and the replication of desired signal of adaptive arrays are compared and discussed each other. Computer simulation results showed that the SINR of LMS adaptive array was 13.8［dB］, and that of CMA was 12.8［dB］, and also the convergence characteristics of LMS was fast a little than that of CMA. The LMS adaptive array was also performed null point well for the interference signal direction than that of the CMA adaptive array.

• Proceedings of the IEEK Conference
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• 2000.09a
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• pp.553-556
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• 2000

This paper proposes an adaptive linearization method of Volterra nonlinear systems using DWT(Discrete Wavelet Transform)and an LMS-type predistorter. In particular, the proposed wavelet transform-domain lineatization method leads to diagonalization of the input vector auto-correlation matrix which yields improvement of the convergence rate of the corresponding transform-domain LMS algorithm. Furthermore, the adaptive Volterra predistorter followed by a corresponding weakly Volterra nonlinear system(here. a TWT amplifier model in a satellite communication system) is utilized to compensate for the distortion in the output. Also,12-PSK and 4-QAM are applied as the input to the nonlinear system to be tested. Some simulation results show that the proposed linearization approach has better performance than DCT-based or conventional normalized LMS algorithms do.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.10a
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• pp.591-592
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• 2010

The strong adjacent interference in the receiver channel may cause difficulties in recovering the signal and also it degrades the system performance very seriously. Therefore, in this paper, the cancellation method was investigated to minimize these interference effects. It was supposed that the strong transmission power was leaked into the receiver channel. the usual LMS algorithm was applied for cancellation. Weight coefficients for adaptation converged very fast within 10 micro seconds and it showed the cancellation capability of 50dB approximately.