• Journal of the Korean Institute of Telematics and Electronics S
• /
• v.35S no.10
• /
• pp.135-143
• /
• 1998

Several equalizers are applied to the DVD-ROM(Digital Versatile Disc-Read Only Memory) system. Because imperfect writing process may cause nonlinear distortion in the reply signal, neural equalizers which have strong nonlinear mapping capability are applied to the system to compensate the nonlinear distortion. Experimental results to verify that the combination of decision-feedback type equalizers and modulation code is formidable are also given. The experimental results shwo that the SNR gain of the neural equalizers over the conventional equalizers becomes much as the nonlinearity in the channel increases. Furthermore, the decision-feedback type equalizers outperform the equalizers which have no decision-feedback in eliminating ISI(Intersymbol Interference) of random data sequence but there is no performance gain of the decision-feedback type equalizers over the equalizers without decision-feedback when these are applied to compensate the ISI of modulation-encoded data sequence.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.22 no.11
• /
• pp.2459-2469
• /
• 1997

In this paper, the multi-stage radius-directed algorithm is applied to fractionally spaced equalizers which are insensitive to the sampling timing-phase. these equalizers exhibit good convergence characeristics when compared to fractionally spaced blind equalizers using conventional blind algorithms. Also, multi-model fractionally spaced blind equalizers, which use multiple symbol spaced blind equalizers that operate independently, converge faster than conventional fractionally spaced blind equalizers.

• Proceedings of the IEEK Conference
• /
• 1999.06a
• /
• pp.468-473
• /
• 1999

Neural networks for adaptive channel equalizers have been resorted to recently in digital communication systems. In this paper, the characteristics and the application areas and etc. for neural networks as adaptive channel equalizers are examined through simple examples.

• Journal of the Optical Society of Korea
• /
• v.15 no.3
• /
• pp.232-236
• /
• 2011

We analyze the linear equalizers used in optically amplified on-off-keyed (OOK) systems to combat chromatic dispersion (CD) and polarization mode dispersion (PMD), and we derive the mathematical minimum mean squared error (MMSE) performance of these equalizers. Currently, the MMSE linear equalizer for optical OOK systems is obtained by simulations using adaptive approaches such as least mean squared (LMS) or constant modulus algorithm (CMA), but no theoretical studies on the optimal solutions for these equalizers have been performed. We model the optical OOK systems as square-law nonlinear channels and compute the MMSE equalizer coefficients directly from the estimated optical channel, signal power, and optical noise variance. The accuracy of the calculated MMSE equalizer coefficients and MMSE performance has been verified by simulations using adaptive algorithms.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.24 no.6A
• /
• pp.881-887
• /
• 1999

In this paper, were introduce two types of equalizers, called equalizer-a and equalizer-b, applying to wireless communications having unknown channel characteristics. The equalizer-a, which has the single sample detector with equalizer system, is developed while the equalizer-b has the partition detectors with the same system used in equalizer-a. The methodologiy we adopt for designing the equalizers is that the sample space is partitioned into finite number of regions by using quantiles, which are estimated by robbins-monro stochastic approximation (RMSA) algorithm, and the coefficients of equalizers are calculated based on nonlinear minimum mean, square error (MMSE) algorithm. Through the computer simulation, the equalizers show much better performance in equiprobably partitioned sample subspaces of observations than the single sample detector and the detector, which has the conventional equalizer, in unquantized observation space under various noise environments.

• Proceedings of the IEEK Conference
• /
• 2002.06a
• /
• pp.61-64
• /
• 2002

In this paper, various equalizers are considered to improve the performance of Home Phoneline Networking Alliance (HomePNA) 2.0 system under dispersive channel with intersymbol interference. We evaluate and compare the performances of Recursive Least Squares (RLS) and Least Mean Squares (LMS) adaptation algorithms. Computer simulations show that the equalizers utilizing tile RLS algorithm outperforms the LMS algorithm, especially for the system of high symbol rate and complex constellation.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.19 no.5
• /
• pp.939-951
• /
• 1994

In adaptive equalizers based on least mean squares (LMS) algorithms, the convergence rate is determined by the convariance matrix of an input signal. When the eigenvalue spread of the convariance matrix is close to unity, the convergence rate is quite fast. In this paper, for fast convergence of LMS-based adaptive equalizers we propose a modified reference signal pertinent to the statistical channel. From the theoretical analysis and computer simulation, it is shown that the proposed modification method is quite effective for fast convergence of LMS-based adaptive equalizers.

• ETRI Journal
• /
• v.31 no.2
• /
• pp.162-172
• /
• 2009

A linear-prediction-based blind equalization algorithm for single-input single-output (SISO) finite impulse response/infinite impulse response (FIR/IIR) channels is proposed. The new algorithm is based on second-order statistics, and it does not require channel order estimation. By oversampling the channel output, the SISO channel model is converted to a special single-input multiple-output (SIMO) model. Two forward linear predictors with consecutive prediction delays are applied to the subchannel outputs of the SIMO model. It is demonstrated that the partial parameters of the SIMO model can be estimated from the difference between the prediction errors when the length of the predictors is sufficiently large. The sufficient filter length for achieving the optimal prediction is also derived. Based on the estimated parameters, both batch and adaptive minimum-mean-square-error equalizers are developed. The performance of the proposed equalizers is evaluated by computer simulations and compared with existing algorithms.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.35 no.5C
• /
• pp.432-438
• /
• 2010

In this paper we study the effect of bit-to-symbol mappings on the convergence behavior of turbo equalizers employing low-density parity-check (LDPC) codes over high order modulations. We analyze the effective SNR of the outputs from linear minimum mean-squared error (MMSE) equalizers and the convergence property of LDPC decoding for different symbol mappings. Numerical results show that the bit-reliability (BR) mapping provides better performance than random mapping in LDPC-coded turbo equalizers over high order modulations. We also verify the effect of symbol mappings through the noise threshold and error performance.

• Journal of the Korean Institute of Telematics and Electronics B
• /
• v.33B no.6
• /
• pp.164-175
• /
• 1996

In this thesis, to cope with severe intersymbol interference and nonlinear distotions of the digital magnetic recording channel a neural decision feedback equalizer (NDFE) and an adaptive neural equalizer (NE) are applied. The digital magnetic recording channels with various recording densities and different types of the nonlinear distortions are considered. The computer simulation shows that as the nonlinear distortion is increased, the neural equalizers (NdFE, NE) have advantages of approximately 2-4 dB in signal to noise ratio (SNR) over the onventional eualizers to reach sme bit error rate and, a sthe recording density is increased, 1~5 dB of SNR improvement are also gained. Especially the NdFE gives a superior performance over the other equalizers when there is a severe nonlinear distortion in the digital magnetic channel.