• Communications for Statistical Applications and Methods
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• v.25 no.6
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• pp.633-645
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• 2018

Gaussian error distributions are a common choice in traditional regression models for the maximum likelihood (ML) method. However, this distributional assumption is often suspicious especially when the error distribution is skewed or has heavy tails. In both cases, the ML method under normality could break down or lose efficiency. In this paper, we consider the log-concave and Gaussian scale mixture distributions for error distributions. For the log-concave errors, we propose to use a smoothed maximum likelihood estimator for stable and faster computation. Based on this, we perform comparative simulation studies to see the performance of coefficient estimates under normal, Gaussian scale mixture, and log-concave errors. In addition, we also consider real data analysis using Stack loss plant data and Korean labor and income panel data.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.5 no.5
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• pp.454-457
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• 2004

Partial response maximum likelihood (PRML) is a powerful and indispensable detection scheme for perpendicular magnetic recording channels. The proposed method is a low complexity detection scheme which is related to the PRML system. The simulation results show that PR(1,2,3,4,3,2,1)ML and PR(l,2,3,3,2,1)ML using modulation encoding with R=2/3 have the most improved performance at K=3,4. However, in the case of K=3, R=2/3 PR(1,1,1,1)ML effectively reduces the complexity compared to PR(1,2,3,3,2,1), but it has L5dB performance degradation at most. In the case of K=4, R=l PR(1,2,2,1)ML has very low complexity compared to R=2/3 PR(l,2,3,4,3,2,1)ML. but it has about 2dB performance degradation at most.

• Journal of Communications and Networks
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• v.11 no.1
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• pp.20-25
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• 2009

The maximum likelihood detection with QR decomposition and M-algorithm (QRM-MLD) has been presented as a suboptimum multiple-input multiple-output (MIMO) detection scheme which can provide almost the same performance as the optimum maximum likelihood (ML) MIMO detection scheme but with the reduced complexity. However, due to the lack of parallelism and the regularity in the decoding structure, the conventional QRM-MLD which uses the tree-structure still has very high complexity for the very large scale integration (VLSI) implementation. In this paper, we modify the tree-structure of conventional QRM-MLD into trellis-structure in order to obtain high operational parallelism and regularity and then apply the Viterbi algorithm to the QRM-MLD to ease the burden of the VLSI implementation.We show from our selected numerical examples that, by using the QRM-MLD with our proposed trellis-structure, we can reduce the complexity significantly compared to the tree-structure based QRM-MLD while the performance degradation of our proposed scheme is negligible.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37A no.10
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• pp.841-849
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• 2012

This paper proposes an low-complexity soft-output multiple-input multiple-output (soft-MIMO) detection algorithm for achieving soft-output maximum-likelihood (soft-ML) performance under max-log approximation. The proposed algorithm is based on a parallel tree-search (PTS) applying a channel ordering by a sorted-QR decomposition (SQRD) with altered sort order. The empty-set problem that can occur in calculation of log-likelihood ratio (LLR) for each bit is solved by inserting additional nodes at each search level. Since only the closest node is inserted among nodes with opposite bit value to a selected node, the proposed node insertion scheme is very efficient in the perspective of computational complexity. The computational complexity of the proposed algorithm is approximately 37-74% of that of existing algorithms, and from simulation results for a $4{\times}4$ system, the proposed algorithm shows a performance degradation of less than 0.1dB.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.8A
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• pp.768-776
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• 2010

In this paper, we consider a linear precoding for the effective spectrum sharing in multiple-input multiple-output (MIMO) cognitive radio system where a secondary user coexists with primary users. The secondary user employs the orthogonal space time block coding (OSTBC) at the transmitter. Assuming a flat fading channel and a maximum-likelihood receiver, the optimum precoder forces transmission referred to as eigen-beamforming. In this paper, to eliminate the interference, ZF criterion based eigen-beamforming is not only used but also the precoding weight is chosen to cancel the remaining interference. This weight is computed by vector's likelihood. Simulation results show stronger interference suppression capability, better SER performance, and higher capacity than the algorithm in [4].

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.25 no.12
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• pp.1275-1283
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• 2014

Characteristics of PCM(Pulse Code Modulation) waveform are suitable for target tracking. Especially in terms of dwell time, it is desirable to detect and track a moving target with the single PCM waveform for a MFR(Multi-Function Radar) which carries out multiple tasks. General PCM waveform processing includes Doppler filter bank caused by the characteristics of ambiguity function, to detect target and estimate Doppler frequency, which induces hardware burden and computational complexity. We propose a ML(Maximum Likelihood) based Doppler estimator for a PCM waveform, which is the closed form suboptimal solution and computationally efficient to estimate Doppler frequency and detect a moving target.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.25 no.3
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• pp.372-375
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• 2014

A monopulse based on maximum likelihood(ML) in jamming scenario can suppress jamming signal using an inverse matrix of a covariance matrix. In order to achieve adequate suppression of jamming signal, the sufficient number of snapshots is required. However, this is not possible in high PRF scenario, which hinders a real-time tracking. Moreover, even with the large number of snapshots, the estimation accuracy of the target direction is decreased in low JNR(Jammer to Noise Ratio) due to insufficient jammer suppression. In this paper, we propose a monopulse algorithm that doesn't degrade performance significantly with a small number of snapshots and in low JNR. We show its derivation that exploits noise-jammer subspace of a covariance matrix, along with its performance through simulation.

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.5
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• pp.865-872
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• 2020

In the fifth generation (5G) mobile networks, non-orthogonal multiple access (: NOMA) has been considered as a promising technology, to increase the channel capacity. In NOMA, the multiple users share the channel resources and multiplex simultaneously. Recently, for the stronger channel user, it was reported that the bit-error rate (: BER) performance with interactive mobile users is degraded, compared to the BER of non-interactive users. In this paper, in order to improve such degraded BER performance, we propose the maximum-likelihood (: ML) receiver. First, the closed-form expression for the BER of the ML receiver is derived, and then it is shown that the BER of the ML receiver is improved, compared with the BER of the ideal perfect successive interference cancellation (: SIC) receiver. Additionally, based on the analytical expression, Monte Carlo simulations validates the above-mentioned results.

• Proceedings of the Acoustical Society of Korea Conference
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• spring
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• pp.155-160
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• 2004

배열센서를 사용한 표적의 위치 추정은 레이다 및 소나에서 잘 알려진 문제이다. 최근에 Lee 등은 1 차원 수평 선배열 센서만을 사용하여 다중경로를 통해 들어오는 신호로부터 표적의 3 차원 위치를 추정하였다. 그러나 이 알고리즘에서 수중에서의 음속은 수심에 관계없이 일정하다고 가정하였기 때문에 음속이 수심에 따라 다양하게 변화하는 실제 수중환경에서는 그 추정성능이 현저히 저하된다. 따라서 본 논문에서는 표적의 거리, 깊이, 방위각으로 구성되는 3 차원 위치 추정을 위해 비균일 음속환경에서의 음파전달모델(ray propagation model)을 이용한 ML 기법(maximum likelihood estimation)을 적용하였으며 일정한 음속을 가정한 Lee 기법의 추정치를 초기값으로 한 탐색을 통해 ML 기법의 연산량을 감소시켰다.

• The KIPS Transactions:PartC
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• v.13C no.6 s.109
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• pp.749-756
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• 2006

Broadcast nature of wireless medium and path-loss reduction create a favourable condition for collaborative communications (CC) among single-antenna users to gain the powerful benefits of multi-antenna system without the demand for physical arrays. This paper proposes a CC strategy adapting to the propagation environment changes by optimizing the transmit signal amplification factors to simplify the structure of maximum likelihood (ML) detector and to obtain the minimum error probability as well. The closed-form BER expression was also derived and compared to the simulation results to evaluate the performance of the suggested solution. A variety of numerical results revealed the cooperation significantly outperforms non-cooperative counterpart under flat Rayleigh fading channel plus AWGN (Additive White Gaussian Noise).