• Journal of Communications and Networks
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• v.8 no.2
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• pp.205-211
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• 2006

This paper considers the maximum likelihood (ML) detection of 16-ary differential amplitude and phase shift keying (DAPSK) in Rayleigh fading channels. Based on the conditional likelihood function, two new receiver structures, namely ML symbol-by-symbol receiver and ML sequence receiver, are proposed. For the symbol-by-symbol detection, the conventional DAPSK detector is shown to be sub-optimum due to the complete separation in the phase and amplitude detection, but it results in very close performance to the ML detector provided that its circular amplitude decision thresholds are optimized. For the sequence detection, a simple Viterbi algorithm with only two states are adopted to provide an SNR gain around 1 dB on the amplitude bit detection compared with the conventional detector.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.11 no.1
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• pp.73-84
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• 1986

A statistical method is proposed which estimates an edge that is one of the basic features in image understanding. The conventional edge detection techniques are performed well for a deterministic singnal, but are not satisfactory for a statistical signal. In this paper, we use the likelihood function which takes account of the statistical property of a signal, and derive the decision function from it. We propose the maximum likelihood edge detection technique which estimates an edge point which maximizes the decision function mentioned above. We apply this technique to statistecal signals which are generated by using the random number generator. Simnulations show that the statistical edge detection technique gives satisfactory results. This technique is extended to the two-dimensional image and edges are found with a good accuracy.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.47 no.7
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• pp.1-7
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• 2010

In this paper, we use the maximum-likelihood detection by the estimation of trellis targets on the 16-level cell NAND flash memory. This mechanism has a performance gain by using a maximum-likelihood detector. The NAND flash memory channel is a memory channel because of the coupling effect. Thus, we use the known data arrays to finding the targets of trellis. The maximum-likelihood detection by proposed scheme performs better than the threshold detection on the 16-level cell NAND flash memory channel.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.11A
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• pp.1063-1071
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• 2008

This paper proposes a prior maximum likelihood (ML) detection verifier which has an ability to verify if the zero forcing (ZF) detection results are identical to the ML detection results. Since more than 90% of ZF detection results are identical to ML detection results, the proposed verifier makes it possible to omit the computationally complex ML detection in 90% cases of MIMO signal detections. The proposed verifier is designed by using the diversity gain obtained from converting MIMO signal into single input multiple output (SIMO) signals. In the proposed method, single input multiple output (SIMO) signals for each transmit antenna are separated from MIMO signals after the MIMO signals are detected by ZF method. Computer simulations show that the true alarm probability of the proposed verifier is more than 80% and the false alarm probability is less than $10^{-4}$.

• Journal of the Korean Data and Information Science Society
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• v.26 no.1
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• pp.261-269
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• 2015

Nowadays the application of change point analysis has been indispensable in a wide range of areas such as quality control, finance, environmetrics, medicine, geographics, and engineering. Identification of times where process changes would help minimize the consequences that might happen afterwards. The main objective of this paper is to compare the change-point detection capabilities of Bayesian estimate and maximum likelihood estimate. We applied Bayesian and maximum likelihood techniques to formulate change points having a step change and multiple number of change points in a Poisson rate. After a signal from c-chart and Poisson cumulative sum control charts have been detected, Monte Carlo simulation has been applied to investigate the performance of Bayesian and maximum likelihood estimation. Change point detection capacities of Bayesian and maximum likelihood estimation techniques have been investigated through simulation. It has been found that the Bayesian estimates outperforms standard control charts well specially when there exists a small to medium size of step change. Moreover, it performs convincingly well in comparison with the maximum like-lihood estimator and remains good choice specially in confidence interval statistical inference.

• 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.32 no.7C
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• pp.616-626
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• 2007

In spatially multiplexed MIMO systems that enable high data rate transmission over wireless communication channels, the spatial demultiplexing at the receiver is a challenging task, and various demultiplexing methods have been developed recently by many researchers. Among the previous methods, maximum likelihood detection with QR decomposition and M-algorithm (QRM-MM)), and sphere decoding (SD) schemes have been reported to achieve a (near) maximum likelihood (ML) performance. In this paper, we propose a novel signal detection method that achieves a near ML performance in a computationally efficient manner. The proposed method is demonstrated via a set of computer simulations that the proposed method achieves a near ML performance while requiring a complexity that is comparable to that of the conventional MMSE-OSIC. We also show that the log likelihood ratio (LLR) values for all bits are obtained without additional calculation but as byproduct in the proposed detection method, while in the previous QRM-MLD, SD, additional computation is necessary after the hard decision for LLR calculation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.6
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• pp.981-989
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• 2015

In a log likelihood ratio(LLR) calculation of the detected symbol, multiple-input multiple-output(MIMO) system applying an optimal or suboptimal algorithm such as a maximum likelihood(ML) detection, sphere decoding(SD), and QR decomposition with M-algorithm Maximum Likelihood Detection(QRM-MLD) suffers from exponential complexity growth with number of spatial streams and modulation order. In this paper, we propose a LLR calculation method with very low complexity in the QRM-MLD based symbol detector for a high order modulation based $N_T{\times}N_R$ MIMO system. It is able to approach bit error rate(BER) performance of full maximum likelihood detector to within 1 dB. We also analyze the BER performance through computer simulation to verify the validity of the proposed method.

• 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.

• Journal of Industrial Technology
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• v.24 no.B
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• pp.143-148
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• 2004

We present a fast algorithm for CDMA (code division multiple access) multiuser detection using the gradient guided search. The fast algorithm calculates the maximum likelihood (ML) metric so efficiently that it needs only O(K) additions in the presence of K users once some initialization is completed. The computational advantages of the fast algorithm over the conventional method are more noticeable as more iterations are required to obtain a suboptimal solution as in the initialization with matched filters.