• Title/Summary/Keyword: maximum likelihood (ML)

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Gradient-Search Based CDMA Multiuser Detection with Estimation of User Powers (Gradient 탐색에 기초한 CDMA 다중사용자 검출과 전력 추정)

  • Choi Yang-Ho
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.31 no.9C
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    • pp.882-888
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    • 2006
  • Multiuser detection can significantly increase system capacity and improve service quality compared with the existing matched filter. In this paper, we introduce an method which efficiently calculates the maximum likelihood (ML) metric based on the gradient search (GS). The ML detection needs user powers as well as their spreading codes. A method is also proposed that allows us to detect data bits with the estimation of user powers when they are unknown. Computer simulation shows that the proposed method can nearly achieve the same performance as the GS with perfectly hewn user powers.

Time-Delay Estimation in the Multi-Path Channel based on Maximum Likelihood Criterion

  • Xie, Shengdong;Hu, Aiqun;Huang, Yi
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.6 no.4
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    • pp.1063-1075
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    • 2012
  • To locate an object accurately in the wireless sensor networks, the distance measure based on time-delay plays an important role. In this paper, we propose a maximum likelihood (ML) time-delay estimation algorithm in multi-path wireless propagation channel. We get the joint probability density function after sampling the frequency domain response of the multi-path channel, which could be obtained by the vector network analyzer. Based on the ML criterion, the time-delay values of different paths are estimated. Considering the ML function is non-linear with respect to the multi-path time-delays, we first obtain the coarse values of different paths using the subspace fitting algorithm, then take them as an initial point, and finally get the ML time-delay estimation values with the pattern searching optimization method. The simulation results show that although the ML estimation variance could not reach the Cramer-Rao lower bounds (CRLB), its performance is superior to that of subspace fitting algorithm, and could be seen as a fine algorithm.

Performance Analysis of Maximum Likelihood Joint Detection for MIMO MC-CDMA Systems (순방향 다중 안테나 MC-CDMA 시스템에서 Maximum Likelihood 합동 검파 성능 분석)

  • Kim, Young-Ju;Song, Hyoung-Joon;Hong, Dae-Sik
    • Journal of the Institute of Electronics Engineers of Korea TC
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    • v.45 no.11
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    • pp.1-8
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    • 2008
  • In this paper, we analyze the symbol error rate (SER) performance of maximum likelihood (ML) joint detection in downlink multiple-input multiple-output (MIMO) multicarrier code division multiple access (MC-CDMA) systems by deriving a tight union bound on the symbol error rate (SER). The union bound for ML joint detection is utilized to demonstrate the performance of MIMO MC-CDMA systems quantitatively in multiuser and frequency selective Rayleigh fading environments. An analysis of the diversity order of the systems shows the effects of multiple users, spread subcarriers, and multiple antennas on the ML joint detection performance. Furthermore, the analysis shows that MIMO MC-CDMA systems without full loading can achieve more diversify than MIMO orthogonal frequency division multiplexing (OFDM) systems.

Performance of Interference Cancellation for Cooperative Communication Systems with Maximum Likelihood Equalizer (최대 우도 등화기를 적용한 협력통신 시스템의 간섭 제거 성능)

  • Kim, Joo-Chan;Kim, Jin-Young
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.10 no.2
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    • pp.7-12
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    • 2010
  • In this paper, we analyze and simulate the performance of a cooperative communication system adopting a maximum likelihood (ML) equalizer. In wireless communication systems, cooperative communication schemes employing several relays can be applied for extending the communication coverage. It is assumed that both relays and user terminals can move. Therefore, coverages of two or more relays can overlap each other. If wanted and interfering signals are transmitted through the same channel and there are one terminal in the overlapped region, its performance is degraded due to interference. Hence, we use a ML equalizer for rejecting the effect of interfering signal and enhancing the communication system performance. The cooperative system performance is evaluated in terms of bit error probability. From the simulation results, it is demonstrated that the ML receiver shows good interference cancellation performance although its complexity is high.

Derivation of the ML Based Monopulse Ratio Curve (ML 기반 모노 펄스 MR 커브의 수학식 유도)

  • Lim, Jong-Hwan;Kim, Heung-Su;Yang, Hoon-Gee;Chung, Young-Seek;Bae, Kyung-Bin
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
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    • v.22 no.10
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    • pp.960-965
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    • 2011
  • This paper presents the mathematical derivation of a maximum likelihood(ML)-based monopulse ratio(MR) curve. The derived form is, with the linear array assumed, shown to be the function of the number of array elements and the elements' spacing. Through some simulations, the acquired form is equivalent to the expected MR curve. Furthermore, we show the form, which consists of several terms, can be simplified by one tangent function.

Low Complexity Noise Predictive Maximum Likelihood Detection Method for High Density Perpendicular Magnetic Recording: (고밀도 수직자기기록을 위한 저복잡도 잡음 예측 최대 유사도 검출 방법)

  • 김성환;이주현;이재진
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.27 no.6A
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    • pp.562-567
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    • 2002
  • Noise predictive maximum likelihood(NPML) detector embeds noise predictions/ whitening process in branch metric calculation of Viterbi detector and improves the reliability of branch metric computation. Therefore, PRML detector with a noise predictor achieves some performance improvement and has an advantage of low complexity. This paper shows that NP(1221)ML system through noise predictive PR-equalized signal has less complexity and better performance than high order PR(12321)ML system in high density perpendicular magnetic recording. The simulation results are evaluated using (1) random sequence and (2) run length limited (1,7) sequence, and they are applied to linear channel and nonlinear channel with normalized linear density $1.0{\leq}K_p{\leq}3.0$.

Implementation of Noise Predictive Maximum Likelihood Detector in High Density Perpendicular Magnetic Recording (고밀도 수직자기기록에서 잡음 예측 최대 유사도 시스템에 대한 검출기 구현)

  • 김성환;이재진
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.28 no.3C
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    • pp.336-342
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    • 2003
  • Noise predictive maximum likelihood(NPML) detector embeds noise prediction/whitening process in branch metric calculation of Viterbi detector and improves the reliability of branch metric computation. Therefore, PRML detector with a noise predictor achieves some performance improvement and has an advantage of low complexity. This thesis random sequences are applied to linear channel. In perpendicular magnetic recording density KP=2.5, NP(121)ML and NP(1221)ML detection system which is based on a noise predictive PR-equalized signal are evaluated by the Performance through a computing simulation. Therefore, NPML systems are implemented and are verified by VHDL.

A computational note on maximum likelihood estimation in random effects panel probit model

  • Lee, Seung-Chun
    • Communications for Statistical Applications and Methods
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    • v.26 no.3
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    • pp.315-323
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    • 2019
  • Panel data sets have recently been developed in various areas, and many recent studies have analyzed panel, or longitudinal data sets. Often a dichotomous dependent variable occur in survival analysis, biomedical and epidemiological studies that is analyzed by a generalized linear mixed effects model (GLMM). The most common estimation method for the binary panel data may be the maximum likelihood (ML). Many statistical packages provide ML estimates; however, the estimates are computed from numerically approximated likelihood function. For instance, R packages, pglm (Croissant, 2017) approximate the likelihood function by the Gauss-Hermite quadratures, while Rchoice (Sarrias, Journal of Statistical Software, 74, 1-31, 2016) use a Monte Carlo integration method for the approximation. As a result, it can be observed that different packages give different results because of different numerical computation methods. In this note, we discuss the pros and cons of numerical methods compared with the exact computation method.

The restricted maximum likelihood estimation of a censored regression model

  • Lee, Seung-Chun
    • Communications for Statistical Applications and Methods
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    • v.24 no.3
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    • pp.291-301
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    • 2017
  • It is well known in a small sample that the maximum likelihood (ML) approach for variance components in the general linear model yields estimates that are biased downward. The ML estimate of residual variance tends to be downwardly biased. The underestimation of residual variance, which has implications for the estimation of marginal effects and asymptotic standard error of estimates, seems to be more serious in some limited dependent variable models, as shown by some researchers. An alternative frequentist's approach may be restricted or residual maximum likelihood (REML), which accounts for the loss in degrees of freedom and gives an unbiased estimate of residual variance. In this situation, the REML estimator is derived in a censored regression model. A small sample the REML is shown to provide proper inference on regression coefficients.

Low-Complexity Maximum-Likelihood Decoder for VBLAST-STBC Scheme Using Non-square OSTBC Code Rate 3/4

  • Pham Van-Su;Le Minh-Tuan;Mai Linh;Yoon Gi-Wan
    • Journal of information and communication convergence engineering
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    • v.4 no.2
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    • pp.75-78
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    • 2006
  • This work presents a low complexity maximum-likelihood decoder for signal detection in VBLAST-STBC system, which employs non-square O-STBC code rate 3/4. Stacking received symbols from different symbol duration and applying QR decomposition result in the special format of upper triangular matrix R so that the proposed decoder is able to provide not only ML-like BER performance but also very low computational load. The low computational load and ML-like BER performance properties of the proposed decoder are verified by computer simulations.