• The Journal of the Acoustical Society of Korea
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• v.18 no.7
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• pp.112-117
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• 1999

In case of spectral subtraction for noise robust speech recognition system, this method often makes loss of speech signal. In this study, we propose a method that variation and determination of Gaussian function at semi-continuous HMM(Hidden Markov Model) is made on the basis of SNR criteria function, in which SNR means signal to noise ratio between estimation noise and subtracted signal per frame. For proving effectiveness of this method, we show the estimation error to be related with the magnitude of estimated noise through signal waveform. For this reason, Gaussian function is varied and determined by SNR. When we test recognition rate by computer simulation under the noise environment of driving car over the speed of 80㎞/h, the proposed Gaussian decision method by SNR turns out to get more improved recognition rate compared with the frequency subtracted and non-subtracted cases.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.20 no.12
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• pp.1287-1296
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• 2009

It is very important to estimate the Signal to Noise Ratio(SNR) of received signal in time varying channel state. Most SNR estimation techniques derive the SNR estimates solely from the samples of the received signal after the matched filter. In the severe distorted wireless channel, the performance of these estimators become unstable and degraded. LP-based SNR estimator which can operate on data samples collected at the front-end of a receiver shows more stable performance than other SNR estimator. In this paper, we study an efficient SNR estimation algorithm based on LP and propose a new estimation method to decrease the computation complexity. Proposed algorithm accomplishes the SNR estimation process efficiently because it uses the forward prediction error and its conjugate value during the linear prediction error update. Via the computer simulation, the performance of this proposed estimation method is compared and discussed with other conventional SNR estimators in digital communication channels.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.8C
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• pp.617-626
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• 2008

Opportunistic Beamforming (OBF) offers a way to provide the multiuser diversity even in slow fading channel by using randomly generated beam weights, leading to the substantially reduced feedback in the form of the instantaneous SNR from users. In spite of the advantage of the reduced feedback, the imperfect channel estimation might influence the quality of the estimated SNR and channel scheduler so bad that the selected AMC level would be higher than the achievable rate of the actual channel, resulting the corruption of transmitted packet. In this paper, we propose a conservative link adaptation, where the estimated SNR is scaled down by a conservative factor which minimizes the variance of the maximum difference between the actual channel SNR and the resultant SNR. To support the proposed scheme, we analyze the statistics of the difference of the channel SNR and the estimated SNR. Simulation results show that the introduction of conservative factor achieves more than two-fold performance improvement in the presence of channel estimation error and the fairness of PF scheduler is maintained when the least squared channel estimator is applied.

• Journal of Advanced Navigation Technology
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• v.15 no.5
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• pp.735-741
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• 2011

In this paper, we have analyzed the effect of SNR estimation error on the BER performance of MMSE-DFE in high-speed binary CDMA system. Since MMSE equalization algorithm requires the SNR value of input signal, it should be estimated using CAZAC sequence in preamble. However, when AWGN and ISI exist simultaneously, it is impossible to estimate the exact SNR value of input signal and thereby equalizer's performance may be deteriorated. The simulation results can be used as a guideline for selection of SNR estimation algorithm for MMSE-DFE design.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.12
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• pp.4934-4949
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• 2015

The unstable characteristic values of communication signals along with the varying SNR (Signal Noise Ratio) environment make it difficult to identify the modulations of signals. Most of relevant literature revolves around signal recognition under stable SNR, and not applicable for signal recognition at varying SNR. To solve the problem, this research developed a novel communication signal recognition algorithm based on Holder coefficient and cloud theory. In this algorithm, the two-dimensional (2D) Holder coefficient characteristics of communication signals were firstly calculated, and then according to the distribution characteristics of Holder coefficient under varying SNR environment, the digital characteristics of cloud model such as expectation, entropy, and hyper entropy are calculated to constitute the three-dimensional (3D) digital cloud characteristics of Holder coefficient value, which aims to improve the recognition rate of the communication signals. Compared with traditional algorithms, the developed algorithm can describe the signals' features more accurately under varying SNR environment. The results from the numerical simulation show that the developed 3D feature extraction algorithm based on Holder coefficient cloud features performs better anti-noise ability, and the classifier based on interval gray relation theory can achieve a recognition rate up to 84.0%, even when the SNR varies from -17dB to -12dB.

• Journal of Broadcast Engineering
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• v.18 no.6
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• pp.927-934
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• 2013

This paper aims to realize a Signal to Noise Ratio Estimator which constitutes a critical index of the broadcasting system in OFDM system with a synchronized type based on ISDB-T system. Of the elements which are comprising OFDM segments of ISDB-T system using the MSE algorithm suitable for ASIC design owing to its low complexity among a diverse SNR estimation methods, SNR estimation method using the broadcasting information data and the SNR estimation method using scattered pilot signal were realized by RTL. These two methods were compared in terms of their performance through simulation test not only in the AWGN channel which is an ideal channel, but also in SFN channel and frequency selective fading channel, which are distorted channels. Complexity of two methods were also compared through RTL realization. As a result of this comparison analysis, it was concluded that the SNR estimation method using scattered pilot signal shows more excellent performance and easiness in realization.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.46 no.1
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• pp.83-88
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• 2009

Selection relaying(SR) is usually based on signal-to-noise ratio(SNR) to decide whether or not to forward recovered symbols. However, instantaneous noise at relay is ignored, leading to the risk of erroneous retransmission induced by the relay that can be detrimental to the eventual detection of symbols at destination. To overcome this problem, we propose using new symbol error probability(SEP) related directly to reliability of received symbols instead of SNR. Simulation results show that the proposed SEP-based SR is considerably better than the conventional SNR-based SR under any relay position and threshold.

• Journal of the Korean Magnetics Society
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• v.7 no.2
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• pp.97-102
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• 1997

Off-track capability is used to determine the track pitch of hard disk drive system, and the off-track capability as a function of track pitch is called 747 curve. In this paper, 747 curves were simulated with computer. Side reading and recording parameters were obtained by magnetic field analysis using 3-D finite element method. Head read signal and noise voltages for calculation of signal to noise ratio (SNR) were obtained using reciprocity theorem. According to the 747 curves thus obtained, the off-track capability was increased as erase band width increased and as effective signal to noise ration $(SNR_{eff}}$ decreased. A simulated 747 curve and a measured 747 curve (using spin stand) of a planar silicon head with track width of 4.1 um were very similar, which indicated that the simulation was carried out properly.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.6B
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• pp.1042-1047
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• 1999

In this paper, two kinds of digital predistorters are proposed and their performances are analyzed in order to minimize ACI and SNR degradation caused by nonlinearly amplified TC-16QAM signal and to transmit high speed data in power and bandwidth limited land mobile satellite channel. Our simulation results show that LUT predistorter reduces the out-of-band ACI more efficiently as compared to intersymbol interpolated predistorter. Regarding the reduction of in-band SNR and total power intersymbol interpolated predistorter outperforms LUT predistorter. In the simulation mobile satellite channel and nonlinear HPA are modeled by Rician channel and Fujitsu SSPA, respectively.

• Proceedings of the IEEK Conference
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• 1999.06a
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• pp.687-690
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• 1999

Many high-resolution algorithms based on the eigen-decomposition analysis of observed covariance matrix, such as MVE, MUSIC, and EVM, have been proposed. However, the resolution of spectral estimates for these algorithms is severely degraded when Signal-to-Noise Ratio (SNR) is low and arrival angles of signal are close to each other. And EVM and MUSIC is powerful for the characteristic of SNR. But have the limitation that the number of signals presented is known. While MVE is bad the characteristic of SNR. In this study, we propose a modified MVE to enhance the resolution for Direction-Of-Arrival (DOA) estimation of underwater acoustic signal. This is to remove the limitation that existing algorithms should know the information for the number of signals. Because the algorithms founded on the eigen value estimate DOA with only the noise subspace, they have the high-resolution characteristic. And then, with the method reducing the effect of the signal subspace, we are to reduce the degradation because of complementary relationship between the signal subspace and the noise subspace. This paper, with using the simulation data, we have estimated the proposed algorithms, compared it with other high-resolution algorithms. The simulation results show that the modified MVE proposed is accurate and has a better resolution even though SNR is low, under the same condition.