• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.10 no.1
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• pp.121-127
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• 2010

This paper relates with the improved CMA blind adaptive equalization algorithm which uses the constellation matching method that improve the inverse modelling efficiency of a communication channel compared to the present CMA blind adaptive equalizer. The amplitude distortion can be compensated in the present CMA blind adaptive equalizer which is used for the reduction of intersymbol interference by distortion that generate such as a band limited wireless mobile channel, but in the improved adaptive alogorithm operates with the minimize the amplitude phase distortion in the output of equalizer by applying the cost function that is composition of additional signal constellation matching error terms. In order to evaluation of the inverse modeling efficiency of improved algorithm, the residual intersymbol interference and recovered signal constellation were compared by computer simulation. As a result of comparion of computer simulation, the improved algorithm has a good stability in the residual intersymbol interference in the steady state, but it has a slow convergence rate in the adaptation state in initial state.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.7
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• pp.1364-1373
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• 1994

In this thesis, an algorithm for fast convergence to the steady state and for achieving an improved MSE in blind adaptive equalizers is proposed. The conventional radius-directed algorithm can be transformed into an algorithm that provides effective blind convergence in the aspect of the MSE as the convergence speed. This can be achieved through altering the stop and go algorithm. The performance of the new algorithm is analyzed and compared with the two conventional algorithms, such as the CMA and the stop and go algorithm. The experimental results show the superiority of the new algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.4C
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• pp.384-391
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• 2003

Blind channel identification and equalization attempt to identify the communication channel and to remove the inter-symbol interference caused by a communication channel without using any known trainning sequences. In this paper, we propose a blind adaptive channel identification and equalization algorithm with phase offset compensation for single-input multiple-output (SIMO) channel. It is based on the one-step forward multichannel linear prediction error method and can be implemented by an RLS algorithm. Phase offset problem, we use a blind adaptive algorithm called the constant modulus derotator (CMD) algorithm based on condtant modulus algorithm (CMA). Moreover, unlike many known subspace (SS) methods or cross relation (CR) methods, our proposed algorithms do not require channel order estimation. Therefore, our algorithms are robust to channel order mismatch.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.9C
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• pp.876-881
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• 2006

In this paper, we propose a complex-valued IIR filter for digital VSB signals based on CMA in order to efficiently mitigate multipath distortions, especially the leakage from the quadrature component. The proposed equalizer overcomes the drawback of the conventional real-valued IIR equalizers that it attempts to equalize Hilbert transform of quadrature component. We demonstrate via simulation that the proposed complex IIR filter successfully mitigates the leakages from the quadrature component, while the conventional real IIR filter requires a longer IIR filter to achieve the same performance. We present cost function analysis for a simple two-tap case showing that the proposed IIR equalizer with CMA for VSB signals has a global minimum at the desired location.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.2
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• pp.111-116
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• 2018

This paper compare the adaptive equalization performance of RMMA (Region-based MMA) and SCA (Square Contour Algorithm) in order to minimize the intersymbol interference that is occurred in communication channel when transmit the multilevel QAM signal. The RMMA used for improving the performance by translate to 4-level constant modulus and stability in current MMA algorithm, and the SCA used for the improving the performacne by combines the current CMA and RCA algorithm. These algorithms are aimed to improving the equalization peformance by applying the differenct principle each other in multilevel QAM signal, its different performance were compared by computer simulation in the same channel environment. For this, the output signal constellation of equalizer, residual isi, maximum distortion were applied in performance index. As a result, RMMA have more fairly good in every performance index such as signal point clustering capabilities and convergence speed compared to SCA. It is confired that the equalization noise due to misadjumstment was reduced in RMMA than SCA.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.6
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• pp.176-185
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• 1996

In this paper, we present the modified CMA (constant modulus algorithm) and LMS (least mean square) algorithms for digiCipher system with reduced hardware cost, in which the pipelined architecture is employed. They yield the performance comparable to that using floating-point operations. We show the effecstiveness of the proposed architecture through the implementation results using VHDL.

• Proceedings of the KIEE Conference
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• 1999.07g
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• pp.3135-3137
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• 1999

We propose two robust blind equalization algorithms based on multi-stage clustering blind equalization algorithm, which are called a complex classification update algorithm(CCUA) and an error compensation algorithm(ECA). The first algorithm is a tap-updating algorithm which each computes classified real and imaginary parts in order to reduce computations and the complexity of implementation as a stage increase. The second one is a algorithm which can achieve faster convergence speed because error of equalizer input make always fixed. Test results confirm that the proposed algorithms with faster convergence and lower complexity outperforms both constant modulus algorithm (CMA) and conventional multi-stage blind clustering algorithm(MSA) in reducing the SER as well as the MSE at the equalizer output.

• Proceedings of the KIEE Conference
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• 1999.07g
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• pp.3138-3140
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• 1999

We propose a robust blind equalization algorithm based on dual-mode algorithm which incorporates a stop-and-go technique. The constant modulus algorithm(CMA) exhibits very slow convergence when applied to QAM signals and generates phase error. We show that convergence properties of the dual-mode MCMA can be significantly improved by simply adding a stop-and-go technique. To speed up the convergence rate, the TMA-MCMA operates in triple mode that is based on the dual-mode of the MCMA incorporated with the tap-updating control modes of the SGA.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.5
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• pp.1274-1282
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• 1996

This paper deals with an inverse modeling of nonminimum phase communication channel utilizing the HOS (High Order Statistics) of the received signal. After the communication channel is separated into the minimum phase and maximum phase components, the inverse modeling is performed independently. The performance superiority is confirmed by monte-carlo computer simulation in comparison with the traditional CMA (Constant Modulus Algorithm) method. By utilizing the proposed algorithm employing the HOS of the received signal, the inverse frequency characteristics of the channel can be obtained withoug transmitted signal in digital communication. This algorithm is required in preprocessing or postprocessing in order to remove the channel effect, and effective in the self adaptive equalizer which can minimize the bit error rate or symbol error rate in the recovry of received signal.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.1
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• pp.19-26
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• 2013

This paper deals with the performance comparison of blind adaptive equalization algorithm, the MMA and S-MMA, that is used for compensation of the amplitude and phase distortion simultaneously which occurs in the time dispersive channel. The present CMA algorithm is possible to compensates the amplitude only, but not in phase, so it needs to the another additional circuit for compensating the phase. In order to overcoming the abovemensioned shorthand, the improved cost function is applied to the MMA algorithm. In MMA algorithm, the error is consists of the dispersion constant only, but in S-MMA, the error is consists of the dispersion constant considering the output of decision device (sliced symbol) in order to updating the tap coefficients. By using the two kind error signal, the adaptive equalization algorithm has different performance. In this paper, we compare to the adaptive equalization algorithm performance by using the recovered constellation, residual isi, MD (Maximum Distortion) and SER as a index when the transmitting signal is 16 and 64-QAM and then passing through the same communication channel. As a result of simulation, the S-MMA can improving the Roburstness in SER performance compared to the MMA in the high order QAM signal.