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

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.46 no.2
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• pp.64-70
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• 2009

A 6-Gbps feed-forward equalizer having a 6.2-dB gain at 3GHz is designed in 0.13-um CMOS technology and the equalizer helps error-free data recovery over a 7-m SATA cable with 14.7dB loss. Based on a differentially-connected varactor, the proposed equalizer uses only a one-fourth varactor size of a conventional equalizer, which enables the equalizer's integration in a pad-frame, high operating frequency, and low power dissipation of 3.6mW.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.42 no.8 s.338
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• pp.17-24
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• 2005

This paper proposes a Decision Feedback Equalizer (DFT) with an error feedback filter for blind channel equalization. The proposed equalizer uses Least Mean Square(LMS) Algorithm and Multi-Modulus Algorithm (MMA), and has been designed for 64/256 QAM constellations. The existing MMA equalizer uses either two transversal filters or feedforward and feedback filers, while the proposed equalizer uses feedforward, feedback and error feedback filters to improve the channel adaptive performance and to reduce the number of taps. The proposed equalizer has been simulated using the $SPW^{TM}$ tool and it shows performance improvement. It has been modeled by VHDL and logic synthesis has been performed using the $0.25\;\mu m$ Faraday CMOS standard cell library. The total number of gates is about 190,000 gates. The proposed equalizer operates at 15 MHz. In addition, FPGA vertification has been performed using FPGA emulation board.

• Proceedings of the IEEK Conference
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• 2001.09a
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• pp.869-872
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• 2001

Blind identification and equalization of communication channel is important because it does not need training sequence, nor does it require a priori channel information. So, we can increase the bandwidth efficiency. The linear prediction error method is perhaps the most attractive in practice due to the insensitive to blind channel estimator and equalizer length mismatch as well as for its simple adaptive algorithms. In this paper, we propose method for fractionally spaced blind equalizer with arbitrary delay using one-step forward prediction error filter from second-order statistics of the received signals for SIMO channel. Our algorithm utilizes the forward prediction error as training sequences for data estimation and desired signal for channel estimation.

• Journal of information and communication convergence engineering
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• v.5 no.1
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• pp.35-41
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• 2007

In this paper, a modified Fuzzy C-Means (MFCM) algorithm is presented for nonlinear blind channel equalization. The proposed MFCM searches the optimal channel output states of a nonlinear channel, based on the Bayesian likelihood fitness function instead of a conventional Euclidean distance measure. In its searching procedure, all of the possible desired channel states are constructed with the elements of estimated channel output states. The desired state with the maximum Bayesian fitness is selected 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 that of a hybrid genetic algorithm (GA merged with simulated annealing (SA): GASA), and the relatively high accuracy and fast searching speed are achieved.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.42 no.5 s.335
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• pp.13-22
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• 2005

IEEE 802.11a is a standard for the high-speed wireless local area network (WLAN), supporting from 6 up to 54 Mbps in a 5 GHz band. We propose a channel equalization algerian and a sampling clock recovery algorithm by utilizing the Viterbi decoder output of the IEEE 802.11a WLAN standard. The proposed channel equalizer adaptively compensates channel variations. The proposed system uses re-encoded Viterbi decoder outputs as reference symbols for the adaptation of the channel equalizer. It also extracts sampling phase information with the Viterbi decoder outputs for fine adjustment of the sampling clock. The proposed sampling clock recovery and equalizer are more robust to noise and frequency selective fading environments than conventional systems using only four pilot samples.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.4C
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• pp.447-453
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• 2007

In the multipath fading channel, OFDM(Orthogonal Frequency Division Multiplexing)system possess the characteristics of ISI/ICIwith prefix, but a weak point of circuit complexity and PAPR problem. SC-FDE(Single Carrier with Frequency Domain Equalization) performance is similar to OFDM system, but equalizer is complex in frequency domain. In this paper, simple proportional equalizer offer for SC-FDE system, it useful method in the $2GHz{\sim}\;10GHz$ channel model such as indoor, outdoor, SUI. It prove using MATLAB simulation, speed faster then OFDM system, reduce terminal complexity in same test condition.

• Journal of Digital Contents Society
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• v.12 no.3
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• pp.355-360
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• 2011

In this paper, the performance of OFDM (Orthogonal Frequency Division Multiplexing) was assessed by using computer simulations performed using Matlab. We analyzed channel estimation algorithm for adaptive modulation techniques and effect of system using designed simulator in Multimedia wireless communication multipath fading channel environment. Also, we analyzed performance of adaptive OFDM systems that apply adaptive equalizer using guided result through BER. In result, in case of adaptive modulation OFDM systems that modulation mode changes according to channel state, we knew that adaptive modulation OFDM systems have gains of about 7dB performance than general system (BER=$10^{-1}$). Thus we know that adaptive OFDM propose systems is required for efficient transmission in the high speed Multimedia wireless communication channel environment.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.32A no.8
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• pp.11-18
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• 1995

This paper proposes a nonlinear adaptive equalizer which is based on fuzzy rules and fuzzy inference of several affine mapping for the received channel data. The proposed nolonlinear adaptive equalizers with the significantly lower computational complexity. Also it can be applied to the on-line adaptation environments owing to its fast convergence characteristics and the lower computational load. When using the decision feedback vectors, this equaalizer can be easily realized in the form of the DFE structure with out the requirement for the perfect channel knowledge as in the case of the fuzzy adaptive filter.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.26 no.8B
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• pp.1078-1084
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• 2001

In this paper, fuzzy-ARTMAP neural network is applied for compensating the nonlinearity of satellite communication channel. The fuzzy-ARTMAP is made of using fuzzy logic and ART neural network. By a match tracking process with vigilance parameter, fuzzy ARTMAP neural network achieves a minimax learning rule that minimizes predictive error and maximizes generalization. Thus, the system automatically learns a minimal number of recognition categories, or hidden units, to meet accuracy criteria. Simulation studies are performed over satellite nonlinear channels. The performance of proposed fuzzy-ARTMAP equalizer is compared with MLP-basis equalizers.