• The Journal of the Korea Contents Association
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• v.9 no.5
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• pp.84-90
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• 2009

In this paper, the new channel estimation was proposed that have the low complexity and high performance using Fuzzy inference method uses recently from various field for estimation about uncertainty in channel estimation of OFDM. Proposed method is channel estimation performance improve, calculation and interpolation for statistics character of channel using the pilot before LS channel estimation by Fuzzy inference method. Simulation result in QPSK proposed channel estimation method shows the enhancement of 5.5dB compared to the LS channel estimation and the deterioration of 1.3dB compared to the MMSE channel estimation in mean square error point $10^{-3}$. symbol error rate shows similarity performance the MMSE $10^{-1.96}$, proposed channel estimation $10^{-1.93}$ and enhancement of $10^{-0.35}$ compared to the LS channel estimation in signal to noise ratio point 20dB.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.25 no.7
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• pp.782-790
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• 2014

In this paper, we apply the 2-D Matrix Pencil Method(MPM) to the estimation of the direction of arrival(DOA) of multiple signals of interest(SOIs) in bistatic MIMO radar. The 2-D MPM shows remarkable performance under a low SNR environment and low computational complexity to estimate the DOA of multiple SOIs. Also, it is possible to estimate the direction of departure(DOD) which is an angle from transmitter to target. To verify the proposed algorithm, we applied the proposed algorithm to a uniformly spaced linear array(ULA) and compared the RMSE(Root Mean Square Error) of DOA and DOD under the various SNR with those of the 2-D Capon algorithm.

• The Journal of the Acoustical Society of Korea
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• v.41 no.2
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• pp.143-149
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• 2022

In this paper, we evaluate the underwater frequency diversity communication performance of Selective Combination (SC) using Maximum Likelihood Estimation (MLE). In an underwater multipath frequency selective channel, destructive interference fading due to delay spread of a received signal affects the increase in error and Signal to Noise Ratio (SNR) variability of an underwater acoustic communication. Selective Combination frequency diversity using a single sensor is applied as a transmission performance improvement technique according to the frequency selectivity of a channel. In the sea experiment applying MLE for SC decision value extraction, we evaluate the performance of SC frequency diversity and MLE-SC frequency diversity. In experiment result, we confirm through experiment that the Bit Error Rate (BER) is relatively lower when the decision value extracted through MLE-SC is applied than when the SC decision value is fixed.

• The Journal of the Acoustical Society of Korea
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• v.36 no.3
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• pp.218-227
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• 2017

In this paper, an algorithm to calculate both bearing and distance error for target detection and localization is proposed using the Cramer Rao lower bound to estimate the minium variance of their error in DOA (Direction Of Arrival) estimation. The performance of arrays in detection and localization depends on the accuracy of DOA, which is affected by a variation of SNR (Signal to Noise Ratio). The SNR is determined by sonar parameters such as a SL (Source Level), TL (Transmission Loss), NL (Noise Level), array shape and beam steering angle. For verification of the suggested method, a Monte Carlo simulation was performed to probabilistically calculate the bearing and distance error according to the SNR which varies with the relative position of the target in space and noise level.

• Journal of Communications and Networks
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• v.18 no.1
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• pp.19-26
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• 2016

In this paper, the performance of dual-hop multi-relay maximum ratio transmission (MRT) over Rayleigh flat fading channels is studied with both conventional (all relays participate the transmission) and opportunistic (best relay is selected to maximize the received signal-to-noise ratio (SNR)) relaying. Performance analysis starts with the derivation of the probability density function, cumulative distribution function and moment generating function of the SNR. Then, both approximate and asymptotic expressions of symbol error rate (SER) and outage probability are derived for arbitrary numbers of antennas and relays. With the help of asymptotic SER and outage probability, diversity and array gains are obtained. In addition, impact of imperfect channel estimations is investigated and optimum power allocation factors for source and relay are calculated. Our analytical findings are validated by numerical examples which indicate that multi-relay MRT can be a low complexity and reliable option in cooperative networks.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.12
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• pp.3174-3182
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• 1996

In this paper, a new receiver is proposed for the detection of the OFDM(orthogonal frequency division multiplexing) signals in the time-selective multipath fading channel. For the optimal detection, we estimate the transmitted symbols from OFDM demultiplexing signal using the LMLE(linear masimum likelihold estimation) algorithm. Also, in this paper, the lowerbound for BER(bit error rate) using Taylor series approximation is provided. If the matched filter is used for the OFDM receiver in the time-selectivemultipath fading channel, it is known that the SER(symbol error rate) is always greater than $10^{-1}$, due to the cross-talk between adjacent channels. But, the proposed receiver provides of SER with 15dB SNR. Also, it is found that for the receiver implemented using the LMLE algorithm, the performance is shown to be not affected by the increase of th enumber of subchannel and channel path.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.2A
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• pp.148-158
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• 2008

This paper proposes an efficient signal to noise ratio (SNR) estimation algorithm and its hardware implementation for adaptive transmission system using M-ary modulation scheme. In this paper, we present the implementation results of the proposed algorithm for the second generation digital video broadcasting via satellite (DVB-S2) system, and the proposed algorithm can be tailored to the other communication systems using adaptive transmissions. We built a look-up table (LUT) using the theoretical background of the received signal distribution, and by using this LUT we need just two comparators and a counter for the hardware implementation. For this reason, the hardware of the proposed scheme produces accurate estimation results even with extremely low complexity. The simulation results investigated in this paper reveal that the proposed method can produce estimation results within the specified SNR range in the DVB-S2 system, and it requires a few hundreds of samples for average estimation error of about 1 dB.

• The Journal of the Korea Contents Association
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• v.7 no.12
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• pp.254-261
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• 2007

In this paper, we propose a blind equalization method for advanced terrestrial digital multimedia broadcasting (AT-DMB) systems which use hierarchical modulation. The AT-DMB system adopts hierarchical 16-ary quadrature amplitude modulation (16-QAM) to ensure backward-compatibly with the differential quadrature phase shift keying (DQPSK) signal of the legacy terrestrial digital multimedia broadcasting (T-DMB) systems and to support higher transmission rate. Due to the hierarchical modulation, the conventional T-DMB signal and the additional signal have different error rate at same signal to noise ratio (SNR). By weighting the decided symbols differently according to the reliability of the symbols, i.e., high priority symbol with low error rate and low priority symbol with high error rate, we can improve the channel estimation accuracy. In this paper, we analyze SNR loss by hierarchical modulation and confirm it through simulations. Moreover, through simulations, we verify that the proposed weighting method improve BER compared to the no-weighting method.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.10
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• pp.1874-1881
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• 2010

A recursive linear stochastic error compensation algorithm is newly proposed for target localization in sensor network which provides range difference of arrival(RDOA) measurements. Target localization with RDOA is a well-known nonlinear estimation problem. Since it can not solve with a closed-form solution, the numerical methods sensitive to initial guess are often used before. As an alternative solution, a pseudo-linear estimation scheme has been used but the auto-correlation of measurement noise still causes unacceptable estimation errors under low SNR conditions. To overcome these problems, a stochastic error compensation method is applied for the target localization problem under the assumption that a priori stochastic information of RDOA measurement noise is available. Apart from the existing methods, the proposed linear target localization scheme can recursively compute the target position estimate which converges to true position in probability. In addition, it is remarked that the suggested algorithm has a structural reconciliation with the existing one such as linear correction least squares(LCLS) estimator. Through the computer simulations, it is demonstrated that the proposed method shows better performance than the LCLS method and guarantees fast and reliable convergence characteristic compared to the nonlinear method.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.2
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• pp.125-133
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• 2011

For any pattern matching based algorithm in WLAN environment, the characteristics of signal to noise ratio(SNR) to multiple access points(APs) are utilized to establish database in the training phase, and in the estimation phase, the actual two dimensional coordinates of mobile unit(MU) are estimated based on the comparison between the new recorded SNR and fingerprints stored in database. As fingerprinting method, k-nearest neighbor(KNN) has been widely applied for indoor location in wireless location area networks(WLAN), but its performance is sensitive to number of neighbors k and positions of reference points(RPs). So intuitive fuzzy c-means(IFCM) clustering algorithm is applied to improve KNN, which is the KNN/IFCM hybrid algorithm presented in this paper. In the proposed algorithm, through KNN, k RPs are firstly chosen as the data samples of IFCM based on signal to noise ratio(SNR). Then, the k RPs are classified into different clusters through IFCM based on SNR. Experimental results indicate that the proposed KNN/IFCM hybrid algorithm generally outperforms KNN, KNN/FCM, KNN/PFCM algorithm when the locations error is less than 2m.