• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.11
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• pp.1406-1409
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• 2016

In this paper, we propose the heuristic signal grouping algorithm to estimate channel state value over full blind communication situation which means that there is no information about the modulation scheme and the channel state information between the transmitter and the receiver. Hereafter, using the constellation rotation method and the probability density function(pdf) the modulation scheme is determined to perform automatic modulation classification(AMC). Furthermore, the modulation type and a channel state value estimation capability is evaluated by comparing the proposed scheme with other conventional techniques from the simulation results in terms of the symbol error rate(SER) and the root mean square error (RMSE).

• Proceedings of the IEEK Conference
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• 2001.09a
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• pp.85-88
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• 2001

In this paper we consider a problem of blind co-channel signal separation, the goal of which is to estimate multiple co-channel digitally modulated signals using an antenna array. We employ the joint maximum likelihood estimation and present a sequential algorithm, which is referred to as sequential joint maximum likelihood (SJML) algorithm. It separates multiple co-channel signal on-line and converges fast in overdetermined noisy communication environment. And the computational complexity of SJML for M-QAM (M=8, 16, 64,...) signals is less expensive compared to the SLSP. Useful behavior of this algorithm are confirmed by simulations.

• The KIPS Transactions:PartB
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• v.13B no.1 s.104
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• pp.27-34
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• 2006

In this study, we propose this new algorithm that generates score function in ICA(Independent Component Analysis) using entropy theory. To generate score function, estimation of probability density function about original signals are certainly necessary and density function should be differentiated. Therefore, we used kernel density estimation method in order to derive differential equation of score function by original signal. After changing formula to convolution form to increase speed of density estimation, we used FFT algorithm that can calculate convolution faster. Proposed score function generation method reduces the errors, it is density difference of recovered signals and originals signals. In the result of computer simulation, we estimate density function more similar to original signals compared with Extended Infomax and Fixed Point ICA in blind source separation problem and get improved performance at the SNR(Signal to Noise Ratio) between recovered signals and original signal.

• Journal of Advanced Navigation Technology
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• v.16 no.3
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• pp.426-432
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• 2012

In this paper, we investigate the signal to noise ratio (SNR) estimation performance of Cross quadrature amplitude modulation (QAM), which is being used for asymmetric digital subscriber line (ADSL), very high bit rate digital subscriber line (VDSL), and digital video broadcasting - cable (DVB-C), and has been found to be useful in adaptive modulation and blind equalization. At first, the symbol error rate (SER) performance of Cross QAM is analyzed in Rayleigh fading channel. Then we suggest error vector magnitude (EVM) based SNR estimation utilizing the selected constellation points having different types of decision region from one another, and verify that SNR estimation performance of each points have different performance pattern through simulation. From the simulation results, it has been found that when suggested selected constellation points are used for SNR estimation in Cross QAM, estimation performance is enhanced in additive white Gaussian noise (AWGN) channel or Ricean fading channel.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.6A
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• pp.473-479
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• 2012

In this paper, blind equalization technique using Gaussian two-cluster model is proposed. The proposed approach, by modeling the received M-QAM signals as Gaussian distributed two-cluster, minimizes the computational complexity and enhances the reliability of the signal estimates. In addition, by using a nonlinear estimator with variable parameters to estimate the transmitted signal, and by selectively applying the reduced constellation and the original constellation when estimating the signals, the reliability of the signal estimation was further improved. As a result, the proposed approach has improved the performance while reducing the complexity of the equalizer. Through computer simulations for blind equalization of higher-order signals of 64-QAM, it was confirmed that the proposed method showed better performance than traditional approaches.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.10a
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• pp.165-169
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• 2007

Due to the complexity of underwater acoustic channel, signal estimation in underwater acoustic communication field is considerably affected from time-varying multipath fading channels. On this reason, the original signals should have many long training signals to estimate the channel and the purposed signals, and the bit rate of signals having information may have small rate. In order to avoid this loss of efficiency in underwater communication, this paper employed a blind channel identification method which don't use training signals. Simulations have predicted performance of the employed method in multipath environment and an aquatic plant experiment has verified the simulation results.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.8A
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• pp.753-762
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• 2002

Blind equalization of transmission channel is important in communication areas and signal processing applications because it does not need training sequences, nor dose it require a priori channel information. In this paper, an adaptive blind MMSE channel equalization technique based on second-order statistics in investigated. We present an adaptive blind MMSE channel equalization using multichannel linear prediction error method for estimating cross-correlation vector. They can be implemented as RLS or LMS algorithms to recursively update the cross-correlation vector. Once cross-correlation vector is available, it can be used for MMSE channel equalization. Unlike many known subspace methods, our proposed algorithms do not require channel order estimation. Therefore, our algorithms are robust to channel order mismatch. Performance of our algorithms and comparisons with existing algorithms are shown for real measured digital microwave channel.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.10C
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• pp.1001-1009
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• 2009

In this paper, an efficient blind frequency offset estimation method for radio resource saving in orthogonal frequency division multiplexing (OFDM) systems is proposed. In the proposed method, we obtain two time different received OFDM signal blocks by using the cyclic prefix and define the cost function by using the two OFDM signal blocks. We show that the cost function can be approximately expressed as a closed form cosine function. The approximated cosine function can be obtained from three independent cost function values calculated at three different frequency offsets. In the proposed method, the frequency offset can be estimated by calculating a frequency offset minimizing the approximated cosine function without searching all the frequency offset range. Unlike the conventional methods such as MUSIC method, the accuracy of the proposed method is independent of the searching resolution since the closed form solution exists. The computer simulation shows that the performance of the proposed method is superior to those of the MUSIC and the oversampling method.

• Journal of Electrical Engineering and Technology
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• v.11 no.2
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• pp.529-536
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• 2016

In this paper we proposed an unsupervised algorithm to estimate the reverberation time (RT) directly from the reverberant speech signal. For estimation process we use maximum likelihood estimation (MLE) which is a very well-known and state of the art method for estimation in the field of signal processing. All existing RT estimation methods are based on the decay rate distribution. The decay rate can be obtained either from the energy envelop decay curve analysis of noise source when it is switch off or from decay curve of impulse response of an enclosure. The analysis of a pre-existing method of reverberation time estimation is the foundation of the proposed method. In one of the state of the art method, the reverberation decay is modeled as a Laplacian distribution. In this paper, the proposed method models the reverberation decay as a Gamma distribution along with the unification of an effective technique for spotting free decay in reverberant speech. Maximum likelihood estimation technique is then used to estimate the RT from the free decays. The method was motivated by our observation that the RT of a reverberant signal when falls in specific range, then the decay rate of the signal follows Gamma distribution. Experiments are carried out on different reverberant speech signal to measure the accuracy of the suggested method. The experimental results reveal that the proposed method performs better and the accuracy is high in comparison to the state of the art method.

• The Journal of the Acoustical Society of Korea
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• v.35 no.5
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• pp.331-339
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• 2016

This paper suggests an estimation method of the source signal and the channel impulse response (CIR) using ray-based blind deconvolution (RBD) in the underwater acoustic channel environment where Doppler effect exists by the relative motion between source and receiver. It is difficult to estimate the CIR on Doppler effect by the matched filter with a highly Doppler-sensitive waveform such as the m-sequence signal because Doppler shift can severely degrade the correlation between the received signal corrupted by Doppler effect and the original source signal. In this study, the Doppler-shifted source-signal's phase is estimated using the RBD, and the received signal is compensated by it to obtain the Doppler-corrected CIR. It is verified that using the matched filter with the received signal from the experimental data fails to estimate the CIR while the obtained CIR by the suggested method has the similarity to the propagation path of the ray model. Also, the results show that the reconstructed source signal using the RBD has the better Doppler shift compensation than the Doppler-shifted source signal derived from scattering function.