• 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.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.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.9C
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• pp.897-904
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• 2006

Multiple input multiple output architectures, known to provide high spectral efficiencies, can provide the best performance in terms of the block error rate when a maximum likelihood (ML) detector is employed. The complexity of the ML detector, however, increases exponentially with the numbers of transmit antennas and signals in the constellation. The zero forcing (ZF) detector has been suggested as a reduced-complexity detection method at the cost of performance degradation. In order to improve the performance of the ZF detector while reducing the complexity of the ML detector, we propose a novel multistage decision method. Numerical results show that, despite the proposed detector has a lower complexity than the ML detector, the performance difference between the ML and proposed detectors is negligibly small at high SNR.

• 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 $1.0{\leq}K_p{\leq}3.0$.

• 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.

• Proceedings of the KIEE Conference
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• 1995.11a
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• pp.146-148
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• 1995

A CFAR algorithm for weibull clutter is discussed. The Maximum a posteriori(MAP) estimator for two parameters(skewness and scale) of the weibull clutter is proposed, assuming the probability density function of skewness parameter is known. And proposed MAP estimator is compared with the Maximum likelihood(ML) estimator. Using this MAP estimator, we can design CFAR detector which is shown to have smaller CFAR loss than ML CFAR detector by the statistical simulation method.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.44 no.1
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• pp.98-105
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• 2007

In this paper, we propose a timing detector using suboptimal maximum likelihood method. The proposed method has an simple reference signal generator. Additionally, timing detector's gain of the proposed method is the same to Early-Late gate and ML method. We reveal that tracking range of time tracker is narrow because of using data-decision, that is, tracking range is ${\pm}0.06ns$ for the 4-order Gaussian monocycle with 0.7ns pulse width. Therefore we can find that searcher must have very accurate acquisition procedure. When estimating a performance of time tracker, we consider a jitter in transmitter and receiver's pulse generation process as well as background noise. By using computer simulation, we propose mean/variance of timing detector and tracking process. Also we consider a mobility in tracking process, i.e., timing error modeled ramp function. In order to propose a performance of time tracker, we consider only one correlation demodulator.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.6C
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• pp.523-531
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• 2005

We derive decision regions of the maximum likelihood(ML) and suboptimum ML(S-ML) detectors in the first order moving average(FOMA) of an impulsive process. The ML and S-ML detectors are compared in terms of the bit-error-rate in the antipodal signaling system. Numerical results show that the S-ML detector, despite its reduced complexity and simpler structure, exhibits practically the same performance as the optimum ML detector. It is also shown that the performance gap between detectors for FOMA and independent and identically distributed noise becomes larger as the degree of noise impulsiveness increases.

• JSTS:Journal of Semiconductor Technology and Science
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• v.15 no.2
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• pp.255-266
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• 2015

In this paper, a low-complexity and low-power soft output multiple input multiple output (MIMO) symbol detector is proposed for mobile devices with two transmit and two receive antennas. The proposed symbol detector can support both the spatial multiplexing mode and spatial diversity mode in single hardware and shows the optimal maximum likelihood (ML) performance. By applying a multi-stage pipeline structure and using a complex multiplier based on the polar-coordinate, the complexity of the proposed architecture is dramatically decreased. Also, by applying a clock-gating scheme to the internal modules for MIMO modes, the power consumption is also reduced. The proposed symbol detector was designed using a hardware description language (HDL) and implemented using a 65nm CMOS standard cell library. With the proposed architecture, the proposed MIMO detector takes up an area of approximately $0.31mm^2$ with 183K equivalent gates and achieves a 150Mbps throughput. Also, the power estimation results show that the proposed MIMO detector can reduce the power consumption by a maximum of 85% for the various test cases.

• ETRI Journal
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• v.41 no.2
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• pp.145-159
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• 2019

To reduce the number of radio frequency (RF) chains in multiple input multiple output (MIMO) systems, generalized spatial modulation (GSM) techniques have been proposed in the literature. In this paper, we propose a zero-forcing (ZF)-based detector, which performs an initial pruning of the search tree that will be considered as the initial condition in a sphere decoding (SD) algorithm. The proposed method significantly reduces the computational complexity of GSM systems while achieving a near maximum likelihood (ML) performance. We analyze the performance of the proposed method and provide an analytic performance difference between the proposed method and the ML detector. Simulation results show that the performance of the proposed method is very close to that of the ML detector, while achieving a significant computational complexity reduction in comparison with the conventional SD method, in terms of the number of visited nodes. We also present some simulations to assess the accuracy of our theoretical results.