• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.17 no.3
• /
• pp.87-92
• /
• 2017

This paper compares the equalization algorithm of CR-MMA (Constellation Reduction-Multi Modulus Algorithm) and RMMA (Region based Multi Modulus Algorithm) for the compensation of channel's distortion in nonconstant modulus signal. In order to obtain the error signal for adaptive equalization, every signal points are reduced to the constant modulus signal in CR-MMA and every signal points are separated into the 4 regions, then the reductions are performed based on this region in RMMA. These two algorithm based on the reduction principle such as in order to updating the tap coefficient in the adaptive equalization, it has different equalization performance. The computer simulation was performed in order to compare the each equalization performance in this paper. As a result of computer simulation, RMMA has more good performance in the residual isi, maximum distortion and SER performance than CR-MMA, but not in convergence speed.

• Journal of the Korean Institute of Telematics and Electronics B
• /
• v.33B no.1
• /
• pp.133-143
• /
• 1996

The constant modulus algorithm (CMA), one of the widely used blind equalization algorithms, equalizes channels using the second-order statistic of equalizer outputs. The performance of the CMA for multi-level signals such as the quadrature amplitude modulation (QAM) signal degrades because the CMA maps all signal power onto a single modulus. in this paper, to improve the equalization performance of a QAM system, we propose a shell partitioning method based on error magnitude. We assume the probability distribution of an equalizer output as Gaussian, and obtain decision boundaries by maximum likelihood estimation based on the fact that the distribution of the equalizer output power is noncentral $x^2$. The proposed CMA constructs a multi-moduli equlization system based on the fact that each shell separated by decision boundaries employs a single modulus. Computer simulation results for 32-QAM and 64-QAM show the effectiveness of the proposed algorithm.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.13 no.5
• /
• pp.2332-2337
• /
• 2012

In this paper, a blind decision feedback algorithm is proposed based on the ideas that the derivative of information potential for constant modulus errors stays relatively undisturbed even when large output differences are induced by severe channel distortions and this property can prevent the error propagation that is one of the main problems in decision feedback structures. From the simulation results of the steady state MSE, the proposed blind equalizer algorithm with decision feedback has yielded about 3 dB performance enhancement in the channel model without spectrum nulls and above 9 dB in severe channel characteristics with spectrum nulls.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.19 no.2
• /
• pp.85-90
• /
• 2019

This paper related with the M-CMA adaptive equalization algorithm which is possible to improve the residual isi and robustness performance compare to the current MMA algorithm that is reduce the intersymbol interference occurs in channel when transmitting the QAM signal. The current MMA algorithm depend on the cost function and error function using fixed signal dispersion constant, but the M-CMA algorithm depend on the new proposed cost function and error function using multiple dispersion constant. By this, it is possible to having robustness of the CMA and simultaneous compensation of amplitude and phase of MMA. The computer simulation was performed in the same channel and noise environment for compare the proposed M-CMA and current MMA algorithm. The equalizer output signal constellation, residual isi, MD, MSE learning courves and SER, represents the robustness were used for performance index. As a result of simulation, the M-CMA has more superior to the MMA in robustness and other performance index.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.9 no.1
• /
• pp.152-159
• /
• 2005

For high-speed data communication in band-limited channels, main of the bit error are fading and ISI(Inter-Symbol Interference). The common way of dealing with ISI is using equalization in the receiver. In this thesis, channel adaptive equalizer which uses Fuzzy Stochastic Gradient(FSG) and Constant Modulus Algorithm(CMA) is nonlinear equalizer, or Blind equalizer, that works directly on the signals with no training sequences required. This equalizer employs Takagi-Sugeno's fuzzy model that uses the FSG algorithm, to automatically regulate the step size of the descent gradient vector, combining fast convergence rate and low mean square error(MSE), and the CMA which is a special case of Godard's algorithm, to having multiple dispersion constants($R_p$).

• The Journal of the Korea institute of electronic communication sciences
• /
• v.11 no.5
• /
• pp.459-464
• /
• 2016

The mobile communication service is widely used and the repeaters is rapidly increasing because of the extending service areas. we propose a new Signed CMA(: Constant Modulus Algorithm) algorithm for ICS(: Interference Cancellation System) as a larger service area of mobile communication service. The proposed Signed CMA algorithm improved performances by adjusting step size values. We showed that the proposed algorithm could improve the Mean Square Error(: MSE) performance of Signed CMA. MATLAB(: Matrix Laboratory) is employed to analyze the proposed algorithm and to compare it with the experimental results. At the convergence of 1000 iteration state, the MSE(: Mean Square Error) performance of the proposed Signed CMA algorithm with step size of 0.0065 is about 5 dB better than the conventional CMA algorithm.

• Journal of the Institute of Electronics Engineers of Korea TE
• /
• v.39 no.2
• /
• pp.17-28
• /
• 2002

Recently, the study on non-linear equalization, self-recovering equalization using the neural Network structure or Fuzzy logic, is lively in progress. In this thesis, if the value of error difference is large, coefficient adaptation rate is bigger, and if being small, it is smaller. We proposed the new FSG(Fuzzy Stochastic Gradient)/CMA algorithm combining TS(Tagaki-Sugeno) fuzzy model having fast convergence rate and low mean square error(MSE) and CMA(Constant Modulus Algorithm) which is prone to ISI and insensitive to phase alteration. As a simulation result of the designed channel adaptive equalizer using the proposed FSG/CMA algorithm, it is shown that SNR is improved about 3.5dB comparing to the conventional algorithm. 

• Proceedings of the IEEK Conference
• /
• 1999.11a
• /
• pp.43-46
• /
• 1999

Blind equalizers recover the transmitted data using signal's statistical characteristics only. Because of its computational simplicity and fast convergence rate, CMA is widely used in practice. Blind equalizers, however, converge much slowly than conventional equalizers which use the training signals. In order to improve the convergence rate, many modified blind equalization algorithms have been proposed. Among those, Normalized CMA (NCMA) was applied to increase the convergence rate by using the large step size. Unfortunately it can only be applied for the constant modulus signal constellation scheme. this paper, we propose the Selective NCMA (SNCMA) that improve the convergence rate of blind equalization algorithms by using NCMA for non-constant modulus signalling method such as QAM constellation. We achieved fast start-up convergence rate and reduced steady-state residual error.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.25 no.10B
• /
• pp.1760-1768
• /
• 2000

Blind Equalization Method without training sequences is proposed for channel efficiency in mobile communication system for asynchronous multi-user DS-CDMA. the risk of mis-convergence of weak-power users is increased because of small regions of convergence in case of near-far effect in CMA(Constant Modulus Algorithm) which is the simplest has high performance and widely implemented. In despite the problem a equalization using Newton method has higher performance than a conventional method in squared error and eye-pattern.

• The Journal of the Acoustical Society of Korea
• /
• v.28 no.7
• /
• pp.640-645
• /
• 2009

CMA (Constant Modulus Algorithm) is one of the famous algorithms in blind channel equalization. Generally, CMA converges slowly and the speed of convergence is dependent on a step-size in the CMA procedure. Many researches have tried to speed up the convergence speed by applying a variable step-size to CMA. In this paper, we propose a new CMA algorithm with improved convergence performance. The improvement comes from an orthogonal projection of an average error gradient. We show the improvement in simulation results.