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

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.3C
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• pp.157-162
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• 2011

For blind equalization of communication channels, concurrent equalization is useful to improve convergence characteristics. However, the concurrent equalization will result in limited performance enhancement by continuing concurrent adaptation with two algorithms after the equalizer converges to steady-state. In this paper, to improve the convergence characteristics and steady-state performance of the concurrent equalization, proposed is a new concurrent equalization technique with variable step-size parameter and weight-based tap coefficients update. The proposed concurrent vsCMA+DD equalization calculates weight factors using error signals of the variable step-size CMA (vsCMA) and DD (decision-directed) algorithm, and then updates the two equalizers based on the weights respectively. The proposed method, first, improves the error performance of the CMA by the vsCMA, and enhances the steady-state performance as well as the convergence speed further by the weight-based tap coefficients update. The performance improvement by the proposed scheme is verified through simulations.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.39 no.4
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• pp.173-179
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• 2002

This paper describes an equalizer using the DFE (Decision Feedback Equalizer) structure, CMA (Constant Modulus Algorithm) and LMS (Least Mean Square) algorithms. The DFE structure has better channel adaptive performance and lower BER than the transversal structure. The proposed equalizer can be used for 16/64 QAM modems. We employ high speed multipliers, square logics and many CSAs (Carry Save Adder) for high speed operations. We have developed floating-point models and fixed-point models using the COSSAP$\^$TM/ CAD tool and developed VHDL filter. The proposed equalizer shows low BER in multipath fading channel. We have performed models. From the simulation results, we employ a 12 tap feedback filter and a 8 tap feedforward logic synthesis using the SYNOPSYS$\^$TM/ CAD tool and the SAMSUNG 0.5$\mu\textrm{m}$ standard cell library (STD80) and verified function and timing simulations. The total number of gates is about 130,000.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.8
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• pp.3660-3665
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• 2012

For blind equalization, it is necessary to open an eye pattern quickly in the early stage of equalization, after that it is important to lower an error level of equalizer output signal. This paper discusses coarse error estimation using signal points specifically determined and fine error estimation using original signal constellation, and proposes two suggestions for how to take advantage of the two error estimation methods. The two error estimates, respectively, are effective to quickly open an eye pattern in the state of eye pattern closed, or to lower the level of an error in the steady-state after the eye pattern opening. Two blind equalization algorithms are proposed and their performances are compared, which select one of the two error estimates depending on the state of convergence of the equalizer, or combine two errors weightedly according to the relative reliabilities of the two error estimates, and calculate the new error.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.11
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• pp.2158-2165
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• 2007

In this paper, a Modified Fuzzy C-Means algorithm with Gaussian Weights(MFCM_GW) is presented for nonlinear blind channel equalization. The proposed algorithm searches the optimal channel output states of a nonlinear channel from the received symbols, based on the Bayesian likelihood fitness function and Gaussian weighted partition matrix instead of a conventional Euclidean distance measure. Next, the desired channel states of a nonlinear channel are constructed with the elements of estimated channel output states, and placed at the center of a Radial Basis Function(RBF) equalizer to reconstruct transmitted symbols. In the simulations, binary signals are generated at random with Gaussian noise. The performance of the proposed method is compared with those of a simplex genetic algorithm(GA), a hybrid genetic algorithm(GA merged with simulated annealing(SA): GASA), and a previously developed version of MFCM. It is shown that a relatively high accuracy and fast search speed has been achieved.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.24 no.1
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• pp.64-72
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• 2013

Blind equalization is a technique that equalizes the received signals without the training sequence. Because of the absence of training sequence, we can increase the bandwidth efficiency due to the blind equalization system. And we must use the blind equalization for removing the ISI in mobile satellite communication receiver. ISI occurs due to mobility of users in mobile satellite communications. Blind equalization is suitable for the mobile satellite communication channels. In this blind equalization, it's very important to improve BER performance to apply the mobile satellite communication system. In this paper, we propose the blind beamforming equalization system using the beamforming, MUSIC algorithm and coordinate change method. We were confirmed by the simulation that the proposed system improves the BER performance.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.3 no.3
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• pp.73-80
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• 2010

Complex-valued blind algorithms which are based on constant modulus error and Euclidian distance (ED) between two probability density functions show relatively poor performance in spite of the advantages of information theoretic learning since the inherent characteristics of the constant modulus error prevent the algorithm from coping with the symbol phase rotation caused by the complex channels. In this paper, we show that the symbol phase rotation problem can be avoided and the advantages of information theoretic learning can be preserved by introducing decision-directed mode to the blind algorithm whenever the equalizer output power lies in the neighborhood of multi-modulus levels. Simulation results through MSE convergence and constellation comparison for severely distorted complex channels show significantly enhanced performance of symbol-point concentration and no phase rotation problems caused by the complex channel models.

• The Journal of the Acoustical Society of Korea
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• v.16 no.3
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• pp.38-44
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• 1997

In this study, wer derived LMF-Sato, LMSF-Sato complex blind equalization algorithms for complex data. And then, the convergence rates, the convergence characteristics at the steady state and the stability of the proposed LMF and LMSF blind equalization algorithms are compared with those of LMS-Sato blind equalization algorithm. In simulations with 16-QAM data, LMF-Sato and LMSF-Sato algorithms showed better performance comparing with LMS-Sato algorithm generally. When the initial estimation errors of the weights of the equalizer are large, LMF-Sato algorithm showed ill characteristic in stability. However, LMSF-Sato algorithm has good covergence characteristics and preserves robustness.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.3C
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• pp.279-285
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• 2003

In this paper we propose a blind decision feedback equalizer (DFE) that is characterized by the fact that it does not require channel estimation. Because the output of the optimized multistep prediction error filter (PEF) can be represented as a product of the channel partial impulse response and the transmitted sequence, a backward multistep PEF can be used as the blind DFE feedforward filter (FFF). The corresponding feedback filter (FBF) is obtained from the symbol -rate partial channel impulse response. The proposed algorithm has several advantages over existing blind channel estimation techniques, including stable performance without the necessity of exact channel order estimation.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.8
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• pp.1037-1045
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• 1999

We propose two new classes of robust blind equalization algorithms against abrupt changes of channel conditions, which we call a triple-mode algorithm(TMA) and an automatic switch-over algorithm(ASA). The conventional DMGSA exhibits slow convergence rates due to the incorrect equalizer tap-updating process under the severe channel conditions. In order to speed up the convergence process, the TMA operates in triple-mode that is based on the dual-mode of the DMGSA incorporated with the tap-updating control modes of the SGA as well as the MSGA. Without resorting to the decision region for selecting the operation mode in the TMA, the ASA automatically switches the blind mode to the smoother conventional decision-directed mode. The ASA uses the error functional that is the weighted sum of the Generalized Sato error and the decision-directed error, where the weights correspond to the channel conditions. Test results on 16-QAM and 8-VSB datas confirm that the TMA and the ASA perform well under the sudden changes of channel conditions.