• Journal of electromagnetic engineering and science
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• v.12 no.4
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• pp.290-292
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• 2012

This paper proposes a setup for a best multisine design method that uses a time-domain optimization. The method is based on minimization of the time-domain error, so its resulting multisine has a very accurate ACLR estimation. This is because its probability distribution and sample-to-sample correlation are close to those of the original signal, which are crucial for the testing of nonlinear power amplifiers. In addition, a hyperbolic-tangent function is introduced to control the ripple of tone magnitudes within signal bandwidth. For the verification, multisines were generated and compared for many aspects such as normalized error, in-band ripple, and ACLR estimation. Test results with different numbers of tones provide supporting evidence that the suggested multisine design has better ripple suppression, by up to 7 dB, and better accuracy, by up to 0.2 dB, when compared to the conventional method. The accuracy of the ACLR was improved by about 5 dB when the number of tones was 4. The suggested method improves the ACLR estimation performance of multisine testing due to its closer resemblance to the target modulation signal.

• 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.

• Proceedings of the KOSOMBE Conference
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• v.1991 no.05
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• pp.65-70
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• 1991

A hybrid model which uses a probabilistic model and a MLP(multi layer perceptron) model for pattern recognition of EMG(electromyogram) signals is proposed in this paper. MLP model has problems which do not guarantee global minima of error due to learning method and have different approximation grade to bayesian probabilities due to different amounts and quality of training data, the number of hidden layers and hidden nodes, etc. Especially in the case of new test data which exclude design samples, the latter problem produces quite different results. The error probability of probabilistic model is closely related to the estimation error of the parameters used in the model and fidelity of assumtion. Generally, it is impossible to introduce the bayesian classifier to the probabilistic model of EMG signals because of unknown priori probabilities and is estimated by MLE(maximum likelihood estimate). In this paper we propose the method which get the MAP(maximum a posteriori probability) in the probabilistic model by estimating the priori probability distribution which minimize the error probability using the MLP. This method minimize the error probability of the probabilistic model as long as the realization of the MLP is optimal and approximate the minimum of error probability of each class of both models selectively. Alocating the reference coordinate of EMG signal to the outside of the body make it easy to suit to the applications which it is difficult to define and seperate using internal body coordinate. Simulation results show the benefit of the proposed model compared to use the MLP and the probabilistic model seperately.

• The Journal of the Acoustical Society of Korea
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• v.28 no.7
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• pp.680-685
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• 2009

In this paper, we propose a efficient noise power estimation technique for an integrated acoustic echo and noise suppression system in a frequency domain. The proposed method uses speech absence probability (SAP) derived from the microphone input signal as the smoothing parameter updating noise power to reduce the noise power estimation error resulted from the distortions in the unified structure where the noise suppression (NS) operation is placed after the acoustic echo suppression (AES) algorithm. Therefore, in the proposed approach, the smoothing parameter based on SAP derived from the input signal instead of echo-suppressed signal should stop updating noise power estimates during the distorted noise spectrum periods. The performance of the proposed algorithm is evaluated by the objective test under various environments and yields better results compared with the conventional scheme.

• Journal of Information Processing Systems
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• v.8 no.4
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• pp.669-684
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• 2012

Discrete wavelet transforms are extensively preferred in biomedical signal processing for denoising, feature extraction, and compression. This paper presents a new denoising method based on the modeling of discrete wavelet coefficients of ECG in selected sub-bands with Kernel density estimation. The modeling provides a statistical distribution of information and noise. A Gaussian kernel with bounded support is used for modeling sub-band coefficients and thresholds and is estimated by placing a sliding window on a normalized cumulative density function. We evaluated this approach on offline noisy ECG records from the Cardiovascular Research Centre of the University of Glasgow and on records from the MIT-BIH Arrythmia database. Results show that our proposed technique has a more reliable physical basis and provides improvement in the Signal-to-Noise Ratio (SNR) and Percentage RMS Difference (PRD). The morphological information of ECG signals is found to be unaffected after employing denoising. This is quantified by calculating the mean square error between the feature vectors of original and denoised signal. MSE values are less than 0.05 for most of the cases.

• ETRI Journal
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• v.34 no.4
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• pp.511-517
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• 2012

The best linear unbiased estimator (BLUE) is most suitable for practical application and can be determined with knowledge of only the first and second moments of the probability density function. Although the BLUE is an existing algorithm, it is still largely unexplored and has not yet been applied to channel estimation in amplify and forward (AF)-based wireless relay networks (WRNs). In this paper, a BLUE-based algorithm is proposed to estimate the overall channel impulse response between the source and destination of AF strategy-based WRNs. Theoretical mean square error (MSE) performance for the BLUE is derived to show the accuracy of the proposed channel estimation algorithm. In addition, the Cram$\acute{e}$r-Rao lower bound (CRLB) is derived to validate the MSE performance. The proposed BLUE channel estimation algorithm approaches the CRLB as the length of the training sequence and number of relays increases. Further, the BLUE performs better than the linear minimum MSE estimator due to the minimum variance characteristic exhibited by the BLUE, which happens to be a function of signal-to-noise ratio.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.22 no.3
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• pp.282-291
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• 2011

Adaptive modulation(AM) is an important technique to increase the system efficiency, in which transmitter selects the most suitable modulation mode adaptively according to channel state in the temporary and spatially varying communication environment. Fixed modulation on channels with varying signal-to-noise ratio(SNR) is that the bit-errorrate(BER) probability performance is changing with the channel quality. An adaptive modulation scheme can be designed to have a BER which is constant for all channel SNRs. The correct as well as fast and simple SNR estimation is required essentially for this adaptive modulation. In order to operate adaptive modulation system effectively, in this paper, we analyze the effect of SNR estimation performance to it through the average BER and data throughput. Applying SNR estimation based on auto-correlation of decision feedback signal and others to adaptive modulation system, we also confirm performance degradation or improvement of its which is decided by SNR estimation error at each transition point of modulation level. Since SNR estimation based on auto-correlation of decision feedback signal shows stable estimation performance for various quadrature amplitude modulation(QAM) comparatively, this can be reduced degradation than others at each transition point of modulation level.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.11
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• pp.5370-5393
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• 2019

In this paper, we consider a two-way relay non-orthogonal multiple access (TWR-NOMA) system with residual hardware impairments (RHIs) and channel estimation errors (CEEs), where two group users exchange their information via the decode-and-forward (DF) relay by using NOMA protocol. To evaluate the performance of the considered system, exact analytical expressions for the outage probability of the two groups users are derived in closed-form. Moreover, the asymptotic outage behavior in the high signal-to-noise ratio (SNR) regime is examined and the diversity order is derived and discussed. Numerical simulation results verify the accuracy of theoretical analyses, and show that: i) RHIs and CEEs have a deleterious effects on the outage probabilities; ii) CEEs have significant effects on the performance of the near user; iii) Due to the RHIs, CEEs, inter-group interference and intra-group interference, there exists error floors for the outage probability.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.2A
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• pp.98-106
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• 2008

To reduce the outage probability and to increase the transmission capacity, the importance of repeaters in cellular systems keeps increasing. Unlike optical repeaters which require wireline connections, RF repeaters are easy to install, have low limitations in location and also have a reduced operational expense such as the optical fiber maintenance cost. On the other hand, RF repeaters suffer the interference due to the feedback signals between the transmitter and receiver antennas, hence require an extra interference cancellation method when the amount of the feedback signal reduction by using the shielding is not sufficient. In this paper, a channel estimation method for two-path feedback interference signals in the ICS (Interference Cancellation System) repeaters using baseband signal processing is proposed and its performance is evaluated. When compared with the conventional method which estimates each multipath individually, the proposed method achieves 10 dB performance gain in terms of the normalized mean-squared-error.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.7
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• pp.72-85
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• 1998

In this paper, we propose a new method that sequentially estimates TDOA(Time Delay Of Arrival) and FDOA(Frequency Delay Of Arrival) for extracting the information about the bearing and relative velocity of a target in passive radar or sonar arrays. The objective is to efficiently estimate the TDOA and FDOA between two sensor signal measurements, corrupted by correlated Gaussian noise sources in an unknown way. The proposed method utilizes the one dimensional slice function of the third order cumulants between the two sensor measurements, by which the effect of correlated Gaussian measurement noises can be significantly suppressed for the estimation of TDOA. Because the proposed sequential algoritjhm uses the one dimensional complex ambiguity function based on the TDOA estimate from the first step, the amount of computations needed for accurate estimationof FDOA can be dramatically reduced, especially for the cases where high frequency resolution is required. It is demonstrated that the proposed algorithm outperforms existing TDOA/FDOA estimation algorithms based on the ML(maximum likelihood) criterionandthe complex ambiguity function of the third order cumulant as well, in the MSE(mean squared error) sense and computational burden. Various numerical resutls on the detection probability, MSE and the floatingpoint computational burden are presented via Monte-Carlo simulations for different types of noises, different lengths of data, and different signal-to-noise ratios.