• Journal of Communications and Networks
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• v.16 no.6
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• pp.583-591
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• 2014

In wireless communications, knowledge of the signal-to-noise ratio is required in diverse communication applications. In this paper, we derive the variance of the maximum likelihood estimator in the data-aided and non-data-aided schemes for determining the optimal shrinkage factor. The shrinkage factor is usually the constant that is multiplied by the unbiased estimate and it increases the bias slightly while considerably decreasing the variance so that the overall mean squared error decreases. The closed-form biased estimators for binary-phase-shift-keying and quadrature phase-shift-keying systems are then obtained. Simulation results show that the mean squared error of the proposed method is lower than that of the maximum likelihood method for low and moderate signal-to-noise ratio conditions.

• 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.

• International Journal of Computer Science & Network Security
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• v.24 no.3
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• pp.182-188
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• 2024

Hardware components are an integral part of Hardware Define Radio (HDR) for seamless operations and optimal performance. On the other hand, Software Define Radio (SDR) is a program that does not rely on any hardware components for its performance. Both of the latter radio programmers utilize modulation functions to make their core components from signal processing viewpoint. The following paper concentrates on SDR based modulation and their performance under different modulations. The bit error rate (BER) of modulations such as PSK, QAM, and PSAM were used as indicators to test channel quality estimation in planar Rayleigh fading. Though it is not commonly used for channel fading, the method of the adder determines the regionally segmented channel fading. Thus, the estimation error of the channel change substantially reduces the performance of the signal, hence, proving to be an effective option. Moreover, this paper also elaborates that BER is calculated as a function of the sample size (signal length) with an average of 20 decibels. Consequently, the size of the results for different modulation schemes has been explored. The analytical results through derivations have been verified through computer simulation. The results focused on parameters of amplitude estimation error for 1dB reduction in the average signal-to-noise ratio, while the combined amplitude deviation estimation error results are obtained for a 3.5 dB reduction

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.8
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• pp.890-894
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• 2014

In this paper, we derive the CRLB (Cramer-Rao Lower Bound) of effective carrier-to-noise power ratio ($C/N_0$) estimation for a GPS (Global Positioning System) L1 C/A (Coarse/Acquisition) signal under band-limited white noise jamming environments. The quality of a received GPS signal is commonly described in terms of its $C/N_0$, implying that the noise is white and thus can be described by scalar noise density. However, if some intentional interference is received to a victim GPS receiver, then the $C/N_0$ is no longer the efficacious performance indicator. The correct and straightforward measurement to analyze the receiving situation is the effective $C/N_0$. In this paper, we consider a band-limited white noise jamming whose bandwidth is 2MHz and is the same as one of the first null-to-null bandwidth of the GPS L1 C/A signal.

• Journal of Broadcast Engineering
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• v.13 no.5
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• pp.565-573
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• 2008

This paper proposes noise reduction methods to improve the channel estimation performance in Equalization On-Channel Repeater (E-OCR) for Terrestrial-Digital Multimedia Broadcasting (T-DMB) system. In the E-OCR for T-DMB system, the channel estimation is performed by the pilot signal extraction and the channel coefficient estimation. Since the performance of the channel estimation highly depends on the estimated channel coefficients whose accuracy is associated with the received signal-to-noise ratio (SNR), it is important to reduce noise existing at the estimated channel coefficients. To reduce such noise components, various noise reduction methods of the estimated channel coefficients based on the M -point weighted moving average are proposed. Computer simulations show that the proposed methods improve the estimation performance by more than 2 to 3 dB in terms of the symbol error rate after equalization.

• The Journal of the Acoustical Society of Korea
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• v.35 no.2
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• pp.102-109
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• 2016

This paper proposes a noise suppression method through SNR (Singal-to Noise Ratio) estimation in the two microphone array environment of close spacing. The conventional method uses a noise suppression method for a gain function obtained through the SNR estimation based on coherence function from full band. However, this method cause performance decreased by the noise damage that affects all the feature vector component. So, we propose a noise suppression method that allocates a frequency domain signal into N constant multi frequency band and each frequency band gets a gain function through SNR estimation based on coherence function. Performance evaluation of the proposed method is shown by comparison with PESQ (Perceptual Evaluation of Speech Quality) value which is an objective quality evaluation method provided by the ITU-T (International Telecommunications Union Telecommunication).

• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.6
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• pp.994-1003
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• 1994

In this paper, a scheme of noise cancellation using spectral subreaction method with single input in an autombile noise environment is proposed. In order to remove the changing automonile noise components form the noisy speech signal, the noise of various states is analyzed and its characteristics are presented. For the decision of speech/nonspeech and the estimation of noise spectrum, a classification function is proposed on the basis of noise analysis. This function presents the precise decision of speech/nonspeech and the optimal estimation of noise spectrum with less computation. As the result of the estimation of noise spectrum by the proposed classification function, the clean speech signal is extracted from the noisy speech signal with high signal-to-ratio.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2000.06a
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• pp.1710-1715
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• 2000

Estimation of damping ratio for vibration signals measured on the passenger car's seat is useful for the objective evaluation of impact harshness in car. The vibration signal is a transient signal represented by many coupled modes of suspension system. Wavelet transform automatically decouples these modes in the time-frequency domain. Damping ratios for decoupled modes are obtained by logarithmic treatment for the Wavelet transformed signal. The objective evaluation using Wavelet transform has been well corresponded with subjective evaluation done by skilled engineers.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.1
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• pp.87-94
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• 2009

Noise estimation and suppression are a crucial factor of many speech communication and recognition systems. In this paper, proposed algorithm is based on the ratio of variance normalized of noisy power spectrum in time-frequency domain. Our proposed algorithm tracks the threshold and controls the trade-off between residual noise and distortion. This algorithm is evaluated by the ITU-T P.835 signal distortion (SIG) and segment signal to noise ratio (SNR), and is superior to the conventional methods.

• The Journal of the Acoustical Society of Korea
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• v.28 no.4
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• pp.383-391
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• 2009

In speech signal processing, speech signal corrupted by noise should be enhanced to improve quality. Usually noise estimation methods need flexibility for variable environment. Noise profile is renewed on silence region to avoid effects of speech properties. So we have to preprocess finding voice region before noise estimation. However, if received signal does not have silence region, we cannot apply that method. In this paper, we proposed SNR estimation method for continuous speech signal. The waveform which is stationary region of voiced speech is very correlated by pitch period. So we can estimate the SNR by correlation of near waveform after dividing a frame for each pitch. For unvoiced speech signal, vocal track characteristic is reflected by noise, so we can estimate SNR by using spectral distance between spectrum of received signal and estimated vocal track. Lastly, energy of speech signal is mostly distributed on voiced region, so we can estimate SNR by the ratio of voiced region energy to unvoiced.