• Title/Summary/Keyword: Signal estimation error probability

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A Study on Maximum Posterior Probability Estimator for Direction of Arrival Estimation of Incoming Signal (입사신호의 도래방향 추정을 위한 최대 사후 확률 추정기에 대한 연구)

  • Lee, Kwan-Hyeong;Park, Sung-Kon;Jeong, Youn-Seo
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.9 no.2
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    • pp.190-195
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    • 2016
  • In this paper, we are comparative analysis both class method and proposal method in order to estimation of incident signal direction on uniform array antenna system. Proposal method of this paper decrease error probability for a signal direction of arrival estimation using maximum posterior probability estimator. If it decrease to signal estimation direction error probability, signal direction of arrival can correctly estimate. Through simulation, we were comparative analysis proposed method and class method. Also, we were comparative analysis about signal estimation error probability with increasing array antenna element. We show the superior performance of the proposed method relative to the class method to decrease of signal estimation error probability about 12%.

A Study on Combined DoA Estimation Algorithm using LCMV and Maximum Posterior on Uniform Linear Array Antenna (균일 선형 배열 안테나에서 선형구속최소분산 방법과 사후 추정 확률을 결합한 도래 방향 추정 알고리즘 연구)

  • Lee, Kwan-Hyeong;Park, Sung-Kon;Jeong, Youn-Seo
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.9 no.3
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    • pp.291-297
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    • 2016
  • In this paper, we are comparative analysis of exit algorithm and proposal algorithm for desired target direction of arrival estimation in correlation signal system. Proposed algorithm in this paper is to decrease target direction of arrival an estimation error probability using bayesian, maximum posterior, and MUSIC algorithm in order to decrease direction of arrival error probability as optimize and use linear constrained minimum variance to update weight value. Through simulation, we were comparative analysis proposed algorithm and exit MUSIC algorithm. In case SNR is 10dB and antenna element arrays are 9 and 12, We show the superior performance of the proposed method relative to the class method to decrease of signal estimation error probability about 11% and 13%, respectively.

Error Intensity Function Models for ML Estimation of Signal Parameter, Part I : Model Derivation (신호 파라미터의 ML 추정기법에 대한 에러 밀도 함수 모델에 관한 연구 I : 모델 정립)

  • Joong Kyu Kim
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.30B no.12
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    • pp.1-11
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    • 1993
  • This paper concentrates on models useful for analyzing the error performance of ML(Maximum Likelihood) estimators of a single unknown signal parameter: that is the error intensity model. We first develop the point process representation for the estimation error and the conditional distribution of the estimator as well as the distribution of error candidate point process. Then the error intensity function is defined as the probability dessity of the estimate and the general form of the error intensity function is derived. We then develop several intensity models depending on the way we choose the candidate error locations. For each case, we compute the explicit form of the intensity function and discuss the trade-off among models as well as the extendability to the case of multiple parameter estimation.

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Error Intensity Function Models for ML Estimation of Signal Parameter, Part II : Applications to Gaussian and Impulsive Noise Environments (신호 파라미터의 ML추정 기법에 대한 에러 밀도 함수모델에 관한 연구 II : 가우시안 및 임펄스 잡음 환경에의 적용)

  • Kim, Joong Kyu
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.32B no.1
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    • pp.85-95
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    • 1995
  • The error intensity models for the ML estimation of a signal parameter have been developed in a companion paper [1]. While the methods described in [1] are applicable to any estimation problem with continuous parameters, our main application in this paper is the time delay estimation, and comparisons among the models derived in [1] (i.e. LC, LM, and ALM models)have been made. We first consider the case where only additive Gaussian noise is involved, and then the shot noise environment where coherent impulsive noise is also involved in addition to the Gaussian noise. We compare the models in terms of the probability of error, MSE(Mean Squared Error), and the computational complexity, which are the most important performance criteria in the analysis of parameter estimation. In conclusion, the ALM model turned out to be the most adequate model of all from the viewpoints of the criteria mentioned above.

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A Modulation and Channel State Estimation Algorithm Using the Received Signal Analysis in the Blind Channel (블라인드 채널에서 수신 신호 분석 기법을 사용한 변조 및 채널 상태 추정 알고리즘)

  • Cho, Minhwan;Nam, Haewoon
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.41 no.11
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    • pp.1406-1409
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    • 2016
  • In this paper, we propose the heuristic signal grouping algorithm to estimate channel state value over full blind communication situation which means that there is no information about the modulation scheme and the channel state information between the transmitter and the receiver. Hereafter, using the constellation rotation method and the probability density function(pdf) the modulation scheme is determined to perform automatic modulation classification(AMC). Furthermore, the modulation type and a channel state value estimation capability is evaluated by comparing the proposed scheme with other conventional techniques from the simulation results in terms of the symbol error rate(SER) and the root mean square error (RMSE).

Location Estimation Enhancement Using Space-time Signal Processing in Wireless Sensor Networks: Non-coherent Detection

  • Oh, Chang-Heon
    • Journal of information and communication convergence engineering
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    • v.10 no.3
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    • pp.269-275
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    • 2012
  • In this paper, we proposed a novel location estimation algorithm based on the concept of space-time signature matching in a moving target environment. In contrast to previous fingerprint-based approaches that rely on received signal strength (RSS) information only, the proposed algorithm uses angle, delay, and RSS information from the received signal to form a signature, which in turn is utilized for location estimation. We evaluated the performance of the proposed algorithm in terms of the average probability of error and the average error distance as a function of target movement. Simulation results confirmed the effectiveness of the proposed algorithm for location estimation even in moving target environment.

Wire Rope Fault Detection using Probability Density Estimation (확률분포추정기법을 이용한 와이어로프의 결함진단)

  • Jang, Hyeon-Seok;Lee, Young-Jin;Lee, Kwon-Soon
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.61 no.11
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    • pp.1758-1764
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    • 2012
  • A large number of wire rope has been used in various inderstiries as Cranes and Elevators from expanding the scale of the industrial market. But now, the management of wire rope is used as manually operated by rope replacement from over time or after the accident.It is caused to major accidents as well as economic losses and personal injury. Therefore its time to need periodic fault diagnosis of wire rope or supply of real-time monitoring system. Currently, there are several methods has been reported for fault diagnosis method of the wire rope, to find out the feature point from extracting method is becoming more common compared to time wave and model-based system. This method has implemented a deterministic modeling like the observer and neural network through considering the state of the system as a deterministic signal. However, the out-put of real system has probability characteristics, and if it is used as a current method on this system, the performance will be decreased at the real time. And if the random noise is occurred from unstable measure/experiment environment in wire rope system, diagnostic criterion becomes unclear and accuracy of diagnosis becomes blurred. Thus, more sophisticated techniques are required rather than deterministic fault diagnosis algorithm. In this paper, we developed the fault diagnosis of the wire rope using probability density estimation techniques algorithm. At first, The steady-state wire rope fault signal detection is defined as the probability model through probability distribution estimate. Wire rope defects signal is detected by a hall sensor in real-time, it is estimated by proposed probability estimation algorithm. we judge whether wire rope has defection or not using the error value from comparing two probability distribution.

A New Gradient Estimation of Euclidean Distance between Error Distributions (오차확률분포 사이 유클리드 거리의 새로운 기울기 추정법)

  • Kim, Namyong
    • Journal of the Institute of Electronics and Information Engineers
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    • v.51 no.8
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    • pp.126-135
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    • 2014
  • The Euclidean distance between error probability density functions (EDEP) has been used as a performance criterion for supervised adaptive signal processing in impulsive noise environments. One of the drawbacks of the EDEP algorithm is a heavy computational complexity due to the double summation operations at each iteration time. In this paper, a recursive method to reduce its computational burden in the estimation of the EDEP and its gradient is proposed. For the data block size N, the computational complexity for the estimation of the EDEP and its gradient can be reduced to O(N) by the proposed method, while the conventional estimation method has $O(N^2)$. In the performance test, the proposed EDEP and its gradient estimation yield the same estimation results in the steady state as the conventional block-processing method. The simulation results indicates that the proposed method can be effective in practical adaptive signal processing.

Performance Analysis of Dual-Hop MBST-ADF Relay Networks Over Quasi-Static Rayleigh Fading Channels

  • Kim, Min-Chan;Lim, Sungmook;Ko, Kyunbyoung
    • International Journal of Contents
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    • v.14 no.1
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    • pp.18-27
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    • 2018
  • The objective of this study was to derive approximate closed-form error rates for M-ary burst symbol transmission (MBST) of dual-hop adaptive decode-and-forward (ADF) cooperative relay systems over quasi-static Rayleigh fading channels. Within a burst, there are pilot symbols and data symbols. Pilot symbols are used for channel estimation schemes and each relay node's transmission mode selection schemes. At first, our focus was on ADF relay systems' error-events at relay nodes. Each event's occurrence probability and probability density function (PDF) were then derived. With error-event based approach, we derived a tractable form of PDF for combined signal-to-noise ratio (SNR). Averaged error rates were then derived as approximate expressions for arbitrary link SNR with different modulation orders and numbers of relays. Its accuracy was verified by comparison with simulation results.

Approximated Outage Probability for ADF Relay Systems with Burst MPSK and MQAM Symbol Transmission

  • Ko, Kyunbyoung;Lim, Sungmook
    • International Journal of Contents
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    • v.11 no.1
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    • pp.7-14
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    • 2015
  • In this paper, we derive the outage probability for M-ary phase shifting keying (MPSK) and M-ary quadrature amplitude modulation (MQAM) burst transmission (BT) of adaptive decode-and-forward (ADF) cooperative relay systems over quasi-static Rayleigh fading channels. Within a burst, there are pilot symbols and data symbols. Pilot symbols are used for channel estimation schemes and each relay node's transmission mode selection schemes. At first, we focus on ADF relay systems in which the probability density function (PDF) is derived on the basis of error events at relay nodes corresponding to channel estimation errors. Next, the average outage probability is derived as an approximate expression for an arbitrary link signal-to-noise ratio (SNR) for different modulation orders. Its accuracy is demonstrated by comparison with simulation results. Further, it is confirmed that BT-ADF relay systems with pilot symbol based channel estimation schemes enables to select correctly decoded relay nodes without additional signaling between relay nodes and the destination node, and it is verified that the ideal performance is achieved with small SNR loss.