• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.11
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• pp.2451-2458
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• 1997

Adaptive channel equalization complished without resorting to a training sequence is known as blind equalization. In this paper, in order to increase the speed of the convergence and to reduce the steady-state mean squared error simulatneously, we propose the multi-stage DD(decision-direct) algorithm derived from the combination of the Sato algorithm and the decision-directed algorithm. In the starting stage, the multi-stage DD algorithm is identical to the Sato algorithm which guarantees the convergence of the equalizer. As the blind equalizer converges, the number of the level of the quantizers is increased gradally, so that the proposed algorithm operates identical to the decision-directed algorithm which leads to the low error power after the convergence. Therefore, the multi-stage DD algorithm obtains fast convergence rate and low steady state mean squared error.

• Journal of Digital Contents Society
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• v.5 no.4
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• pp.295-299
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• 2004

In this paper, we compare and analyze the LMS ard RLS algorithm of IEEE802.15.3(HDR-WPAN) system. The LMS algorithm have two merits that easily embody and not complex, but convergence speed is slow. The RLS algorithm have fast convergence speed, but very complex. When equalization using LMS algorithm, it can achieve adaptive equalization after 250 sample in fading environment, but case of RLS algorithm can achieve adaptive equalization after just 50 sampls. The computer simulation proved that adaptive equalizer to fast equalization and stability of HDR-WPAN system is more effective using RLS algorithm then LMS algorithm.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.13 no.4
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• pp.83-89
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• 2013

An adaptive blind equalization is a technique using to minimize the Inter-symbol Interference occurred on a communication channel in the transmission of the high speed digital data. In this paper, we propose a blind equalization more improving performance of the conventional MSAGF-MMA adaptive blind equalization algorithm by applying a multiple step size. This algorithm apply a LMS algorithm with a several step size according to each region divided by absolute values of decision-directed error to MSAGF-MMA. By computer simulation, it is confirmed that the proposed algorithm has a performance highly enhanced in terms of a convergence speed, a residual ISI and a residual error and an ensemble averaged MSE in a steady status compared with MMA and MSAGF-MMA.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.4
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• pp.3-8
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• 2015

In this paper, we propose a blind equalization algorithm based on the error signal linearly combined a constellation-matched error (CME) and a non-constellation-matched error (non-CME). The new error signal was designed to include the non-CME term for reaching initial convergence and the CME term for improving intersymbol interference (ISI) performance of output signals, and it controls the error terms through a combining factor. By controlling the error terms, it generates an appropriate error signal for equalization process and improves convergence speed and ISI cancellation performance compared to those of conventional algorithms. In the simulation for 64-QAM and 256-QAM signals under the multipath channel and additive noise conditions, the proposed method was superior to CMA and CMA+DD concurrent equalization.

• International Journal of Naval Architecture and Ocean Engineering
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• v.13 no.1
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• pp.617-627
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• 2021

Underwater Acoustic Channels (UAC) have inherent sparse characteristics. The traditional adaptive equalization techniques do not utilize this feature to improve the performance. In this paper we consider the Variable Adaptive Subgradient Projection (V-ASPM) method to derive a new sparse equalization algorithm based on the Minimum Symbol Error Rate (MSER) criterion. Compared with the original MSER algorithm, our proposed scheme adds sparse matrix to the iterative formula, which can assign independent step-sizes to the equalizer taps. How to obtain such proper sparse matrix is also analyzed. On this basis, the selection scheme of the sparse matrix is obtained by combining the variable step-sizes and equalizer sparsity measure. We call the new algorithm Sparse-Control Proportional-MSER (SC-PMSER) equalizer. Finally, the proposed SC-PMSER equalizer is embedded into a turbo receiver, which perform turbo decoding, Digital Phase-Locked Loop (DPLL), time-reversal receiving and multi-reception diversity. Simulation and real-field experimental results show that the proposed algorithm has better performance in convergence speed and Bit Error Rate (BER).

• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.8B
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• pp.1445-1452
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• 2000

In general, the communication channel can be modeled as inter-symbol interference(ISI) and additive white gaussian noise channel. Viterbi algorithm is optimum detector for transmitted data at transmitter, but it needs large computational complexity. For the sake of this problem, adaptive equalizers are employed for channel equalization which is not attractive for mixed phase channel. In this paper, we propose the effective new channel equalizer for mixed phase channel and show the better performance than previous equalizers.

• Journal of Information Processing Systems
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• v.11 no.3
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• pp.342-353
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• 2015

It is widely accepted that single carrier frequency division multiple access (SC-FDMA) is an excellent candidate for broadband wireless systems. Channel estimation is one of the key challenges in SC-FDMA, since accurate channel estimation can significantly improve equalization at the receiver and, consequently, enhance the communication performances. In this paper, we study the application of compressive sensing for sparse channel estimation in a SC-FDMA system. By skillfully designing pilots, their patterns, and taking advantages of the sparsity of the channel impulse response, the proposed system realizes channel estimation at a low cost. Simulation results show that it can achieve significantly improved performance in a frequency selective fading sparse channel with fewer pilots.

• ETRI Journal
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• v.44 no.1
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• pp.125-134
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• 2022

Visible light communication (VLC) systems incorporate ambient lighting and wireless data transmission, and the experienced channel in indoor VLC is a major topic that should be examined for reliable communication. In this study, it is realized that multiple transmitters in classical alignment are the forceful factors for channel characteristics. In the frequency band, fluctuations with sudden drops are observed, where the fluctuation shape is related to the source layout and receiver location. These varying frequency-selective channels need solutions, especially for mobile users, because sustained channel estimation and equalization are necessary as the receiver changes its location. It is proven that using light-emitting diodes (LEDs) with highly directional beams as sources or using a detector with a narrow field of view (FOV) in the receiver may help partially alleviate the problem; the frequency selectivity of the channel reduces in some regions of the room. For flat fading channel characteristics all over the room, LEDs should be aligned in hexagonal cellular structure, and detector FOV should be arranged according to the cell dimension outcomes.

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

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.9
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• pp.2005-2013
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• 1997

The MCMA adaptive blind equalization algorithm has a excellent phase correction capabilities in addition to channel amplitude equalization, but has an inevitable error by mismatching between the original constellation points in arriving at the perfect equalization since unique new type constellation points are used as desired response instead of original constellation points and follows the slow convergence speed of CMA. In this paper, We propose an adaptive blind equalization algorithm with dual-mode, which has decision regions. Inside the decision regions, it operates as considering the moudlus of original data symbol point and outside the decision region, it operates as considerin gthe modulus of new constellation points. The proposed algorithm has a lower error in the steady state and rapid convergence speed toward steady state using the original data symbol points instead of new constellation points in the decision regions. From computer simulation, we confirm that the propposed algorithm has the performance superiority in residual ISI, convergence speed compared with the cnventional adaptive blind equalization algorithms, CMA, MCMA, Stop-and-Go algorithm.