• The Journal of the Acoustical Society of Korea
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• v.8 no.4
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• pp.44-52
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• 1989

The UCERSS (Unit Circle Eigendecomposition Rational Signal Subspace) algorithm has extended MUSIC (MUltiple Signal Classification ) by using eigendecomposition on the unit circle in order to estimate incident angles of multiple wide band signals. The purpose of this thesis is to further extend the UCERSS to be able to estimate the direction of arrivals of multiple wide band signals in very low SNR . The wide band ESPRIT (Estimation of Signal Parameter via Rotational Invariance Technique) uses covariance difference matrices to reduce noise components. In this paper the wide band ESPRIT which combines the ideas of UCERSS and ESPRIT Is proposed. Computer simulation results Indicate that the performances of the proposed approaches are superior to those of the UCERSS in very low SNR.

• Journal of The Institute of Information and Telecommunication Facilities Engineering
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• v.2 no.4
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• pp.17-27
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• 2003

This paper presents the channel estimation method with STBC applied to IEEE802.11a. Tenacious channel estimation method for OFDM system, that generally uses STTC, has been presented once and massive amount of calculation was needed However, regarding this paper, the amount of calculation can be reduced by using Curve Fitting, and channel tracking performance improvement can be achieved Based on the estimation method, computer simulation was done for the performance analysis and delay spread Doppler frequency and many other group sizes and numbers were considered As a result of the testing, we found out that Doppler frequency deviation effects equally as frequency offset. Also compared to the existing technique, channel estimated performance confirmed that have 0.9dB SNR improvement than old method.

• The Journal of the Acoustical Society of Korea
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• v.16 no.5
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• pp.68-75
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• 1997

Spectral subtraction is widely-used preprocessing technique for speech recognition in additive noise environments, but it requires a good estimate of the noise power spectrum. In this paper, we employ the histogram technique for the estimation of noise spectrum. This technique has advantages over other noise estimation methods in that it does not requires speech/non-speech detection and can estimate slowly-varying noise spectra. According to the speaker-independent isolated word recognition in both colored Gaussian and car noise environments under various SNR conditions. Histogram-technique-based spectral subtraction method yields superier performance to the one with conventional noise estimation method using the spectral average of initial frames during non-speech period.

• Proceedings of the IEEK Conference
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• 2001.09a
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• pp.773-776
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• 2001

열악한 전송 환경에서 고품질, 고신뢰성 통신을 지속적으로 하기 위해서 오류 정정 부호는 필수 적이다. 최근에 반복 복호를 통해 샤논의 채널 용량 한계에 근접하는 터보 부호와 LDPC부호가 가장 관심을 불러일으키고 있다. 반복 복호법은 성능 면에서는 우수해 지나 이에 따른 계산량 증가와 지연이 수반된다. 따라서 본 논문에서는 모의 실험을 통한 수신 데이터를 이용, SNR을 추정하여 LDPC 부호의 최대 반복 복호수에 따른 계산량과 지연을 효과적으로 줄일 수 있는 적응적 반복 복호수 설정 방식을 제안한다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.6C
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• pp.475-480
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• 2005

Information of the maximum Doppler frequency enable to optimize many channel-adaptive techniques and radio resource management methods for mobile radio communication systems. In this paper, we propose two maximum Doppler frequency estimators which are based on the level crossing rate(LCR) and the covariance function (COV). To eliminate the effect of additive noise, we analyze the conditions for the estimators independent of the signal-to-noise ratio(SNR) and implement the conditions with a simple downsampling process. The proposed methods achieve good SNR-independent performance.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.40 no.4
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• pp.1-9
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• 2003

Many CDMA systems provide pilot channels in order to help channel estimation process. Especially in wideband CDMA systems, the number of receive diversity paths can be large due to small chip duration and high multi-path resolution capability. Hence, the received signal power of each path is small for a given total SNR (signal-to-noise ratio) and the pilot power of each path may not be sufficiently large for accurate channel estimation. When the pilot power is small, one can use decision-directed channel estimation to utilize more energy of the received data. However, the decision errors can deteriorate the quality of decision-directed channel estimation. This paper proposes a novel channel estimation method that optimally utilizes receiver decisions as well as pilot symbols with the help of estimated SER (symbol error rate) and SNR. The proposed method computes two channel estimates using the pilot and the data channel filters and optimally combines them. The simulation results show that the proposed method is robust and outperforms the conventional pilot-symbol-aided channel estimation method.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.5
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• pp.843-850
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• 2017

The EMG amplitude estimator, which has been investigated as an indicator of muscle force, is utilized as the control input to artificial prosthetic limbs. This paper describes an application of the optimal EMG amplitude estimator to the surface EMG signals recorded during constant isometric %MVC (maximum voluntary contraction) for 30 seconds and reports on assessing performance of the amplitude estimator from the application. Surface EMG signals, a total of 198 signals, were recorded from biceps brachii muscle over the range of 20-80%MVC isometric contraction. To examine the estimator performance, a SNR(signal-to-noise ratio) was computed from each amplitude estimate. The results of the study indicate that ARV(average rectified value) and RMS(root mean square) amplitude estimation with forth order whitening filter and 250[ms] moving average window length are optimal and showed the mean SNR improvement of about 50%, 40% and 20% for each 20%MVC, 50%MVC and 80%MVC surface EMG signals, respectively.

• Journal of Positioning, Navigation, and Timing
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• v.6 no.4
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• pp.135-140
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• 2017

This paper proposes a signal merging algorithm to increase the signal-to-noise ratio (SNR) of a GPS correlator output to estimate the roll angle of a rotating vehicle in a weak GPS signal environment. Rotation Locked Loop (RLL) algorithm is used to estimate a roll angle using the characteristics that the power of the GPS signal measured at the receiver of a rotating vehicle varies periodically. First, delay times are calculated to synchronize GPS signals using satellites' and receiver's positions and the rotation frequency of a vehicle, and then correlator outputs are delayed in time and merged with each other, resulting in the increase of an SNR in a correlator output. Finally, simulations are conducted and the performance of the proposed algorithm is validated.

• 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.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.7
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• pp.3050-3065
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• 2016

Neural networks (NNs) are extensively used in applications requiring signal classification and regression analysis. In this paper, a NN based threshold selection algorithm for 60 GHz millimeter wave (MMW) time of arrival (TOA) estimation using an energy detector (ED) is proposed which is based on the skewness, kurtosis, and curl of the received energy block values. The best normalized threshold for a given signal-to-noise ratio (SNR) is determined, and the influence of the integration period and channel on the performance is investigated. Results are presented which show that the proposed NN based algorithm provides superior precision and better robustness than other ED based algorithms over a wide range of SNR values. Further, it is independent of the integration period and channel model.