• The Journal of Korean Institute of Communications and Information Sciences
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• v.25 no.12A
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• pp.1781-1786
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• 2000

본 논문에서는, 적응 간섭 제거기(AIC : adaptive interference canceller)에 사용되는 적응 알고리즘 중 계산량이 적고, 하드웨어적 복잡성이 낮은 최소 평균 자승(LMS)알고리즘의 적응화 상수(constant step size)를 여러 개 사용하여 빠른 수렴 속도와 낮은 평균 자승 에러를 가지는 방법을 제안한다. 최소 평균 자승 알고리즘에서 적응화 상수는 수렴속도와 평균 자승 에러를 제거하는데, 적응화 상수가 증가할수록 수렴속도가 빨라지는 반면, 평균 자승 에러는 증가하게 된다. 이 논문에서는 수렴속도를 증가하는 동시에 평균 자승 에러를 줄이기 위해, 최소 평균 자승 알고리즘에서 세 개의 적응화 상수를 가지는 새로운 검출기를 제안한다. 이 구조에서, 매 반복횟수에 따른 각 그룹 출력 값들을 가지고, 선택(selection)부분에서 평균 자승 에러들을 비교하며, 가장 작은 평균 자승 에러를 나타내는 그룹의 에러 값과 필터 계수 값들이 선택되어져 여러 적응화 상수 최소 평균 자승 알고리즘(several step size LMS algorithm)부분에서 각 그룹의 필터 계수를 갱신하는데 필요한 정보로 이용된다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.10
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• pp.2303-2309
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• 1997

This paper presents a convergence analysis of the stocastic gradient adaptive algorithm based on the least mean absolute third (LMAT) error criteriohn. Under the assumption that the signals involved are zero-mean, wide-sense sateionaryand gaussian, a set of nonlinear difference equations that characterizes the mean and mean-squared behavior of the algorithm is derived. Computer simulation resutls show fairly good agreements between the theoetical and empirical behaviors of the algorithm.

• The Journal of the Acoustical Society of Korea
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• v.14 no.1E
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• pp.56-64
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• 1995

The least mean fourth (LMF) adaptive algorithm is a stochastic gradient method that minimizes the error in the mean fourth sense. Despite its potential advantages, the algorithm is much less popular than the conventional least mean square (LMS) algorithm in practice. This seems partly because the analysis of the LMF algorithm is much more difficult than that of the LMS algorithm, and thus not much still has been known about the algorithm. In this paper, we explore the statistical convergence behavior of the LMF algorithm when the input to the adaptive filter is zero-mean, wide-sense stationary, and Gaussian. Under a system idenrification mode, a set of nonlinear evolution equations that characterizes the mean and mean-squared behavior of the algorithm is derived. A condition for the conbergence is then found, and it turns out that the conbergence of the LMF algorithm strongly depends on the choice of initial conditions. Performances of the LMF algorithm are compared with those of the LMS algorithm. It is observed that the mean convergence of the LMF algorithm is much faster than that of the LMS algorithm when the two algorithms are designed to achieve the same steady-state mean-squared estimation error.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.12
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• pp.2353-2362
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• 2015

In this paper, we employ the single channel full duplex radio for wireless local area network (WLAN) systems, and design digital interference cancellers using adaptive signal processing. When the full duplex scheme is used for WLAN systems with multiple transmit and receive antennas, some interference is caused through the feedback of transmit signals from multiple antennas. To remove the feedback interference, we derive the least mean square (LMS), normalized LMS (NLMS), and recursive least squares (RLS) algorithms based on adaptive signal processing techniques. In addition, we analyze the theoretical convergence of the proposed LMS and RLS methods. The channel capacity of full duplex radios increases by two times than that of half duplex radios, when the packet error rate (PER) performances for the two systems are identical. Through numerical simulations in WLAN systems, it is shown that the full duplex method with the proposed interference cancellers has a similar PER performance with the conventional half duplex transmission scheme.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.10A
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• pp.935-942
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• 2006

The performance of ROF systems can be severely degraded due to nonlinear effects in the channel. Also, Orthogonal Frequency Division Multiplex(OFDM), as a standard for broadband wireless and mobile internet networks, is being proposed for deployment with ROF systems to facilitate the total performance of a system. In this paper, at first, the performance of the OFDM-based RoF system with a Mach-Zehnder(MZ) modulator distortion effects has been analyzed at 5.8GHz. Evaluation of mean-squared error of the proposed OFDM-RoF system was carried out to compare with the conventional single carrier system based RoF link after the modulator distortion case and also for fixed signal to noise ratio(SNR) of 20dB using undistorted OFDM signal. Nominal and offset baising pre-distortion techniques are applied in proposed system to linearize the OFDM-RoF link. Finally, a comparison between the aforementioned pre-distortion techniques applied showed important observation in terms of distortion-free dynamic range and SNR to choose offset pre-distortion technique for our proposed system.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.18 no.7
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• pp.1028-1035
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• 1993

The signed regressor (SR) algorithm employs one bit quantization on the input regressor (or tap input) in such a way that the quantized input sequences become +1 or -1. The algorithm is computationally more efficient by nature than the popular least mean square (LMS) algorithm. The behavior of the SR algorithm unfortunately is heavily dependent on the characteristics of the input signal, and there are some Inputs for which the SR algorithm becomes unstable. It is known, however, that such a stability problem does not take place with the SR algorithm when the input signal is Gaussian, such as in the case of speech processing. In this paper, we explore a statistical analysis of the SR algorithm. Under the assumption that signals involved are zero-mean and Gaussian, and further employing the commonly used independence assumption, we derive a set of nonlinear evolution equations that characterizes the mean and mean-squared behavior of the SR algorithm. Experimental results that show very good agreement with our theoretical derivations are also presented.

• Journal of Satellite, Information and Communications
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• v.7 no.1
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• pp.53-58
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• 2012

In this paper, we evaluate and analyze representative estimation methods for the sparse channel. In order to evaluate error performance of matching pursuit(MP) and minimum mean square error(MMSE) algorithm, lower bound of MMSE is determined by Cramer-Rao bound and compared with upper bound of MP. Based on analysis of those bounds, mean square error of MP which is effective in the estimation of sparse channel can be larger than that of MMSE according to the number of estimated tap and signal-to-noise ratio. Simulation results show that the performances of both algorithm are reversed on the sparse channel with Rayleigh fading according to signal-to-noise ratio.

• The Journal of the Acoustical Society of Korea
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• v.18 no.7
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• pp.23-32
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• 1999

This paper presents a stochastic convergence analysis of LMS algorithm and VS-LMS algorithm for IIR filters using equation error formulation. Under the assumption that the signal is white Gaussian, theoretical equations that characterize the mean and mean-squared behaviors of the algorithms are derived. Computer simulation results show fairly good agreements between the theoretical and the empirical behaviors of the algorithms.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 1998.05a
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• pp.400-404
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• 1998

본 논문에서는 도심지 이동 통신에서 SINR 성능을 향상시키기 위해 기존의 배열 안테나에 최소 평균 자승(LMS) 알고리즘을 적용하여 실제 배열 출력과 이상적 출력간의 최소 평균 오차(MSE)를 최소화하고 안테나의 배열로부터 가중치를 결합한 신호에 의해 방향성을 적절히 제어하여 간섭신호를 효과적으로 제거한다. 배열 출력 신호 대 간섭에 추가된 잡음비(SINR) 성능 분석에 적합한 삼차원적 분석을 사용하여 적응 배열 원소를 사용한 성능과 모노폴 안테나 원소에서 배열의 성능을 비교한다. 또한, SINR 패턴 각 비(PAR)를 사용하여 적응 배열 원소 방위, 내부 원소간의 간격들 그리고 입사 신호 방향들과 같은 다른 배열 매개 변수들에서 배열 성능을 계산하고 SINR 패턴의 양적 평가를 한다. 결과로서, 적응 배열 원소가 가정된 신호 환경에 있어 4상파형(quarterwave) 모노폴(monopole) 안테나 배열보다 더 바람직하다.

• The Journal of the Acoustical Society of Korea
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• v.37 no.5
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• pp.271-275
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• 2018

There are several methods for estimating the time delay between incoming signals to two sensors. Among them, the GCC-PHAT (Generalized Cross Correlation-Phase Transform) method, which estimates the relative delay from the signal whitening and the cross-correlation between the different signal inputs to the two sensors, is a traditionally well known method for achieving stable performance. In this paper, we have identified a part of GCC-PHAT that can improve the periodicity. Also, we apply the auto-correlation method that is widely used as a method to improve the periodicity. Comparing the proposed method with the GCC-PHAT method, we show that the proposed method improves the mean square error performance by 5 dB ~ 15 dB at the SNR above 0 dB for white Gaussian signal source and also show that the method improves the mean square error performance up to 15 dB at the SNR above 2 dB for the color signal source.