• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.1
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• pp.83-88
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• 2017

This paper related with the performance evaluation of H-MMA (Hybrid-MMA) which is applying the adaptive modulus and adaptive step size concept to MMA adaptive equalization algorithm in order to reduce the intersymbol interference that is occurred in communication channel for digital code transmission. In the conventional MMA adaptive equalizer, the coefficient is updated by using the equalizer output and possible to compensation of amplitude and phase in 2nd dimensional QAM signal, the equalization performance were degraded due to fixed modulus and step size. For the overcomming the abovemensioned problem, it is possible to improving the equalization performance in the 2nd dimensional QAM signal by applying the adaptive modulus and adaptive step size propotional to equalizer output signal to the conventional MMA algorithm. The computer simulation was performed in the same channel for the compare the performance of MMA and proposed H-MMA which is proposed in this paper. As a result of simulation, the proposed H-MMA has slower convergence time in order to arriving the steady state than MMA. But after the steady state, H-MMA has more superior to the MMA in every performance index and the equalization noise was reduced.

• Proceedings of the IEEK Conference
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• 2004.06a
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• pp.265-268
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• 2004

In this paper. we propose an adaptive step-size algorithm for the adaptive interference canceller (AIC) in the space-time trellis coded DS-CDMA system. In the AIC, the performance of the blind LMS algorithms that updates the tap-weight vector of the AIC is heavily dependent on the choice of step-size. To improve the performance of the fixed step-size AIC (FS-AIC), the regular adaptive step-size algorithm is extended in complex domain and applied to the joint AIC and ML decoder scheme. Simulation results show that the joint adaptive step-size AIC (AS-AIC) and ML decoder scheme using the proposed algorithm has boner performance than not only the conventional ML decoder but also the joint FS-AIC and ML decoder scheme without much increase of the decoding delay and complexity.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2002.05a
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• pp.518-522
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• 2002

This paper proposes a new application of Fuzzy logic to Variable Step Size Least Mean Square (VS-LMS) adaptive beamforming algorithm in CDMA systems. The proposed algorithm adjusts the step size of the Least Mean Square (LMS) by using the application of Fuzzy logic in which the increase or decrease of step size depends on the fuzzy inference results of the Mean Square Error (MSE). Computer simulation results show that the proposed algorithm has a better capacity of tracking compared with the conventional LMS algorithms and other variable step size LMS algorithms.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.1
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• pp.109-114
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• 2016

This paper relates with the performance improvement of CCA (Compact Constellation Algorithm) equalization algorithm by adding the adaptive step size control in order to the minimization of intersymbol interference and additive noise effects that is occurs in the channel for digital radio transmissionl. In general, the fixed step size was used in order to adaptation in equalizer algorithm. But in proposed algorithm, the variable step size were adapted that is proposional to the nonlinear function of error signal for equalization. In order to show the improved equalizatation performance, the output signal constellation of equalizer, residual isi, maximum distortion, MSE and SER were used, then it were compared with the present CCA algorithm. As a result of computer simulation, the adaptive step size CCA has more better performance in the every performance index compared to the fixed step size CCA after in the steay state.

• The Journal of the Acoustical Society of Korea
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• v.33 no.5
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• pp.309-315
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• 2014

In this paper, a novel variable step-size filtered-x gradient adaptive lattice (NVSS-FxGAL) algorithm for active noise control system is proposed. The gradient adaptive lattice (GAL) algorithm is capable of controlling the narrow band noise effectively. The GAL algorithm can achieve both fast convergence rate and low steady-state level using the variable step-size. However, it suffers from the convergence performance for varying signal characteristic since the global variable step-size is equally applied to all lattice stages. Therefore, the proposed algorithm guarantees the stable and consistency convergence performance by using the local variable step-size for the suitable each lattice stage. Simulation results confirm that the proposed algorithm can obtain the fast convergence rate and low steady-state level compared to the conventional algorithms.

• Journal of Korea Multimedia Society
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• v.8 no.8
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• pp.1051-1056
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• 2005

Least mean square(LMS) algorithm is one of the most popular algorithm in adaptive signal processing because of the simplicity and the small computation. But the convergence speed of time domain adaptive algorithm is slow when the spread width of eigen values is wide. Moreover we have to choose the step size well for convergency in this paper, we use adaptive algorithm of wavelet transform. And we propose a new wavelet based adaptive algorithm of wavelet transform. And we propose a new wavelet based adaptive algorithm with variable step size, which Is linear to absolute value of error signal. We applied this algorithm to adaptive noise canceler. Simulation results are presented to compare the performance of the proposed algorithm with the usual algorithms.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.1
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• pp.104-110
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• 2009

In this paper, we suggest a new technique which employ the pipelined architecture for the implementation of the SAP adaptive filter using variable step size. According as SAP adaptive filter is sufficiently decomposed, a simplified SAP adaptive filter can be derived, and the weights of adaptive sub-filters can be updated by a simple formular without a matrix inversion. The convergence speed and the steady state error of the simplified SAP adaptive filter are improved by using variable step size. For practical implementation, the simplified SAP adaptive sub-filters are transformed by the pipeline technique.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.14 no.10
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• pp.1104-1111
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• 2003

The paper presents an algorithm for the compensation of gain and phase imbalances to exist between I-phase and Q-phase signal at direct conversion receiver. We propose a gain and phase imbalances blind equalization compensation algorithm by using variable step-size adaptive loop at direct conversion receiver. The blind equalization schemes have trade-off between convergence speed and jitter effect for the compensation of gain and phase imbalance. We propose the variable step-size adaptive loop method, which varies the loop coefficients according to errors, for recovering these problem. By using variable step-size adaptive loops, we propose to speed up the convergence process and reduce the jitter effect and simulation results show that the algorithm compensates signal loss and speeds up convergence time.

• Proceedings of the Korea Multimedia Society Conference
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• 2001.11a
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• pp.46-50
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• 2001

Adaptive signal processing is used to acoustic echo canceller. adaptive noise canceller and adaptive algorithm among adaptive algorithms is mainly used because the structure is simple and computa LMS algorithm has trade-off between the converge speed and the steady state error. In this paper, step-size of adaptive algorithm is varied with orthogonality Principles of optimal filter to get fasts though small steady state error. Time varying step-size is determined proportional to the maximum vector of LMS algorithm. As results of simulations, the adaptive algorithm with proposed time-v compared with conventional ones.

• The Journal of the Acoustical Society of Korea
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• v.28 no.8
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• pp.815-821
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• 2009

Information processing in variable and noisy environments is usually accomplished by means of adaptive filters. Among various adaptive algorithms, Least Mean Square (LMS) has become the most popular for its robustness, good tracking capabilities and simplicity, both in terms of computational load and easiness of implementation. In practical application of the LMS algorithm, the most important key parameter is the Step Size. As is well known, if the Step Size is large, the convergence rate of the algorithm will be rapid, but the steady state mean square error (MSE) will increase. On the other hand, if the Step Size is small, the steady state MSE will be small, but the convergence rate will be slow. Many researches have been proposed to alleviate this drawback by using a variable Step Size. In this paper, a new variable Step Size LMS(VSSLMS) called Categorized VSSLMS (CVSSLMS) is proposed. CVSSLMS updates the Step Size by categorizing the current status of the gradient, hence significantly improves the convergence rate. The performance of the proposed algorithm was verified from the view point of convergence rate, Excessive Mean Square Error(EMSE), and complexity through experiments.