• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.7
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• pp.1531-1538
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• 2015

In this paper, we proposed receiver structure based on an iterative turbo equalization to cope with phase difference between two sensors in MIMO underwater communication channel. In a space-time coded system, it is often assumed that there are no phase errors among the multiple transmitter and receiver chains. In this paper, we have studied the effect of the phase errors between different transmit sensors and different propagation paths in the environment of MIMO underwater communication system, and have shown through BER performance by computer simulations that the bit-error-rate performance can be severely degraded. A decision-directed estimation and compensation algorithm has been proposed to minimize their effects on the system performance. In this paper, we investigate the phase differences and their effects on multiple-input and multiple-output systems, and propose a compensation algorithm for underwater channel model to minimize their effects.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.3
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• pp.627-632
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• 2021

ITL (information-theoretic learning) has been applied successfully to adaptive signal processing and machine learning applications, but there are difficulties in deciding the kernel size, which has a great impact on the system performance. The correntropy algorithm, one of the ITL methods, has superior properties of impulsive-noise robustness and channel-distortion compensation. On the other hand, it is also sensitive to the kernel sizes that can lead to system instability. In this paper, considering the sensitivity of the kernel size cubed in the denominator of the cost function slope, a new adaptive kernel estimation method using the rate of change in error power in respect to the kernel size variation is proposed for the correntropy algorithm. In a distortion-compensation experiment for impulsive-noise and multipath-distorted channel, the performance of the proposed kernel-adjusted correntropy algorithm was examined. The proposed method shows a two times faster convergence speed than the conventional algorithm with a fixed kernel size. In addition, the proposed algorithm converged appropriately for kernel sizes ranging from 2.0 to 6.0. Hence, the proposed method has a wide acceptable margin of initial kernel sizes.

• 전자공학회논문지 IE
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• v.45 no.1
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• pp.44-49
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• 2008

In this paper, the performance for the non-linear satellite channel including the characteristics of group delay and gain ripple of transponder is analyzed with multi-level QAM-OFDM schemes. Comparing the BER performances between general OFDM and CI(Carrier Interferometry)-OFDM for various QAM schemes, the degree of performance improvement is presented in AWGN environments for specified nonlinear characteristics. The simulations are performed with the 36MHz bandwidth of transponder channel and 120Mbps transmission rate for QPSK, 8QAM, 16QAM, 32QAM, 64QAM schemes between normal and worst case condition. It is shown that the improvement measure by the CI-OFDM for the group delay of channel and nonlinear characteristic of HPA outperforms that for the gain ripple in the case of higher level QAM scheme in normal condition. And the simulation results show that the additional techniques like the channel coding and compensation scheme against the nonlinear characteristic are required for 32QAM and higher level QAM in worst case condition.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.12
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• pp.5036-5041
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• 2010

This paper introduces the complex-version of an Euclidean distance minimization algorithm based on a set of delta functions. The algorithm is analyzed to be able to compensate inherently the channel phase distortion caused by inferior complex channels. Also this algorithm has a relatively small size of Gaussian kernel compared to the conventional method of using a randomly generated symbol set. This characteristic implies that the information potential between desired symbol and output is higher so that the algorithm forces output more strongly to gather close to the desired symbol. Based on 16 QAM system and phase distorted complex-channel models, mean squared error (MSE) performance and concentration performance of output symbol points are evaluated. Simulation results show that the algorithm compensates channel phase distortion effectively in constellation performance and about 5 dB enhancement in steady state MSE performance.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.9A
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• pp.830-837
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• 2005

ISI is caused by delay spread in the multipath channel environment. There are two kinds of channel equalizer: Linear and Non-Linear type according to the structures. In this paper, we propose an improved adaptive linear equalizer to mitigate ISI. The proposed adaptive equalizer is constructed by using asymmetrical Dsmvenu filter based on USE sub-optimal receiver. Asymmetrical structure of the transversal filter is realized by moving the main tap position from center to side. If this structure is used, we can divide ISI to precusor and postcusor. As a result the proposed equalizer has a larger extended compensation range than conventional adaptive linear equalizer. In computer simulation, we compare the bit error rate performance of the proposed linear equalizer with the conventional one on the S-V channel which is modeled for WB systems.

• Journal of Broadcast Engineering
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• v.20 no.5
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• pp.738-747
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• 2015

It is difficult to use a recognition algorithm of an image in a foggy environment because the color and edge information is removed. One of the famous defogging algorithm is haze removal by using 'Dark Channel Prior(DCP)' which is used to predict for transmission rate using color information of an image and eliminates fog from the image. However, in case that the image has factors such as sunset or yellow dust, there is overemphasized problem on the color of certain channel after haze removal. Furthermore, in case that the image includes an object containing high RGB channel, the transmission related to this area causes a misestimated issue. In this paper, we purpose an enhanced fog elimination algorithm by using improved color normalization and haze rate revision which correct mis-estimation haze area on the basis of color information and edge information of an image. By eliminating the color distortion, we can obtain more natural clean image from the haze image.

• Journal of Broadcast Engineering
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• v.21 no.5
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• pp.770-781
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• 2016

As a result of reducing color information and edge information, object distinction in haze image occurs with difficulty. One of the famous defogging algorithm is haze removal by using 'Dark Channel Prior(DCP)', which is used to predict for transmission rate using color information of an image and eliminates haze from the image. But, In case that haze rate is estimated under color information, there is a miscalculated issue which is posed by haze rate and transmission in area with high brightness such as a white object or a light source. In this paper, We deal with a miscalculated issue by correcting from around haze rate, after application of color normalization used by main white part of image haze. Moreover, We calculation improved transmission based on the result of improved haze rate estimation. And then haze image quality is developed through refining transmission.

• International Journal of Computer Science & Network Security
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• v.23 no.7
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• pp.1-8
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• 2023

An Orthogonal Frequency Division Multiplexing (OFDM) based wireless communication system has drawn wide attention for its high transmission rate and high spectrum efficiency in not only radio but also Underwater Acoustic (UWA) applications. Because of the narrow sub-carrier spacing of OFDM, orthogonality between sub-carriers is easily affected by Doppler effect caused by the movement of transmitter or receiver. Previously, Doppler compensation signal processing algorithm for Desired propagation path was proposed. However, other Doppler shifts caused by delayed Undesired signal arriving from different directions cannot be perfectly compensated. Then Receiver Bit Error Rate (BER) is degraded by Inter-Carrier-Interference (ICI) caused in the case of Multi-path Doppler channel. To mitigate the ICI effect, a modified Delay and Doppler Profiler (mDDP), which estimates not only attenuation, relative delay and Doppler shift but also sampling clock shift of each multi-path component, is proposed. Based on the outputs of mDDP, an ICI canceling multi-tap equalizer is also proposed. Computer simulated performances of one-tap equalizer with the conventional Time domain linear interpolated Channel Transfer Function (CTF) estimator, multi-tap equalizer based on mDDP are compared. According to the simulation results, BER improvement has been observed. Especially, in the condition of 16QAM modulation, transmitting vessel speed of 6m/s, two-path multipath channel with direct path and ocean surface reflection path; more than one order of magnitude BER reduction has been observed at CNR=30dB.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.2A
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• pp.98-106
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• 2005

We propose a new wireless fair queueing algorithm, WFQ-R (Wireless Fair Queueing with Retransmission), which is well matched with the LLR (Link Level Retransmission) algorithm and does not require channel prediction. In the WFQ-R algorithm, the share consumed by retransmission is regarded as a debt of the retransmitted flow to the other flows. Thus, the WFQ-R algorithm achieves wireless fairness with the LLR algorithm by penalizing flows that use wireless resources without permission under the MAC layer. Through simulations, we showed that our WFQ-R algorithm maintains fairness adaptively and maximizes system throughput. Furthermore, our WFQ-R algorithm is able to achieve flow separation and compensation.

• Journal of Broadcast Engineering
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• v.14 no.2
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• pp.144-153
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• 2009

Recently, as the necessity of a light-weighted video encoding technique has been rising for applications such as UCC(User Created Contents) or Multiview Video, Distributed Video Coding(DVC) where a decoder, not an encoder, performs the motion estimation/compensation taking most of computational complexity has been vigorously investigated. Wyner-Ziv coding reconstructs an image by eliminating the noise on side information which is decoder-side prediction of original image using channel code. Generally the side information of Wyner-Ziv coding is generated by using frame interpolation between key frames. The channel code such as Turbo code or LDPC code which shows a performance close to the Shannon's limit is employed. The noise model of Wyner-Ziv coding for channel decoding is called Virtual Channel Noise and is generally modeled by Laplacian or Gaussian distribution. In this paper, we propose a Wyner-Ziv coding method based on the frequency-adaptive channel noise modeling in transform domain. The experimental results with various sequences prove that the proposed method makes the channel noise model more accurate compared to the conventional scheme, resulting in improvement of the rate-distortion performance by up to 0.52dB.