• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.31 no.9C
• /
• pp.840-845
• /
• 2006

This paper presents a partial response maximum likelihood (PRML) detection method using partial response signal-to-noise ratio (PRSNR) that evaluates the signal quality of asymmetric optical recording channel. It is confirmed that the equalizer maximizing the PRSNR value can be most properly adapted to the asymmetric optical recording channel. The proposed PRML detection using this result has 1.8dB SNR gain at $8.5{\times}10-5$ bit error rate compared to PRML detection using typical adaptive equalizer.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.10 no.3
• /
• pp.1131-1143
• /
• 2016

Differential detection schemes do not require any channel estimation, which can be employed under user mobility with low computational complexity. In this work, a soft-input soft-output (SISO) differential detection algorithm is proposed for amplify-and-forward (AF) over time-varying relaying channels based cooperative communications system. Furthermore, maximum-likelihood (ML) detector for M-ary differential Phase-shift keying (DPSK) is derived to calculate a posteriori probabilities (APP) of information bits. In addition, when the SISO is exploited in conjunction with channel decoding, iterative detection and decoding approach by exchanging extrinsic information with outer code is obtained. Finally, simulation results show that the proposed non-coherent approach improves detection performance significantly. In particular, the system can obtain greater performance gain under fast-fading channels.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.34 no.3C
• /
• pp.304-310
• /
• 2009

This paper proposes a successive MAP (maximum a posteriori probability) detection scheme with SoIC(soft interference cancellation) to reduce the receiver complexity of hierarchical M-ary QAM system. For the successive MAP detection, modulation symbols generated from the other data streams are treated as Gaussian noise or eliminated as the soft interference according to their priorities. The log-likelihood ratio of the a posteriori probability (LAPRP) of each bit is calculated by the MAP detector with an adjusted noise variance in order to take the elimination and Gaussian assumption effect into account. By separating the detection process into the successive steps, the detection complexity is reduced to increase linearly with the number of bits per hierarchical M-ary QAM symbol. Simulation results show that the proposed detection provides a small performance degradation as compared to the optimal MAP detection.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.20 no.1
• /
• pp.45-51
• /
• 2016

In this paper, we develop an iterative maximum likelihood (ML) receiver for generalized spatial modulation systems. In the proposed ML receiver, to mitigate the deleterious effect of channel information errors on symbol detection, the instantaneous covariance matrix of effective noise is estimated, which is then used to obtain improved ML solutions. The estimated covariance matrix is updated through multiple iterations to enhance the estimation accuracy. The simulation results show that the proposed ML receiver outperforms the conventional ML detection scheme, which does not take the effect of channel information errors into account.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.68 no.3
• /
• pp.471-479
• /
• 2019

This research proposes a indoor magnetic map matching algorithm that improves the position accuracy by employing multiple magnetic sensors and probabilistic candidate weighting function. Since the magnetic field is easily distorted by the surrounding environment, the distorted magnetic field can be used for position mapping, and multiple sensor configuration is useful to improve mapping accuracy. Nevertheless, the position error is likely to increase because the external magnetic disturbances have repeated pattern in indoor environment and several points have similar magnetic field distortion characteristics. Those errors cause large position error, which reduces the accuracy of the position detection. In order to solve this problem, we propose a method to reduce the error using multiple sensors and likelihood boundaries that uses human walking characteristics. Also, to reduce the maximum position error, we propose an algorithm that weights according to their importance. We performed indoor walking tests to evaluate the performance of the algorithm and analyzed the position detection error rate and maximum distance error. From the results we can confirm that the accuracy of position detection is greatly improved.

• ETRI Journal
• /
• v.29 no.2
• /
• pp.240-242
• /
• 2007

This letter proposes a simplified maximum likelihood detection (SMLD) scheme to improve the detection performance of multiple-input multiple-output receivers. The SMLD detects V streams according to the first detected V sub-streams. Through an ML test, the most probable stream is selected. Moreover, to detect the layer with the worst post-detection SNR accurately, reverse ordering is applied to the SMLD. Simulation results show that the performance of the Vertical Bell Laboratories layered space-time (V-BLAST) system can be improved by adopting the SMLD technique. In the case of reverse ordering, the SMLD can achieve a similar ML performance with significant reduction in computational complexity.

• ETRI Journal
• /
• v.40 no.2
• /
• pp.218-226
• /
• 2018

Multiuser detection (MUD) and channel estimation techniques in space-division multiple-access aided orthogonal frequency-division multiplexing systems recently has received intensive interest in receiver design technologies. The maximum likelihood (ML) MUD that provides optimal performance has the cost of a dramatically increased computational complexity. The minimum mean-squared error (MMSE) MUD exhibits poor performance, although it achieves lower computational complexity. With almost the same complexity, an MMSE with successive interference cancellation (SIC) scheme achieves a better bit error rate performance than a linear MMSE multiuser detector. In this paper, hybrid ML-MMSE with SIC adaptive multiuser detection based on the joint channel estimation method is suggested for signal detection. The simulation results show that the proposed method achieves good performance close to the optimal ML performance at low SNR values and a low computational complexity at high SNR values.

• Journal of information and communication convergence engineering
• /
• v.2 no.4
• /
• pp.228-232
• /
• 2004

This paper proposes an efficient detection algorithm, which is composed of an interference nulling-and cancelling-based detection algorithm and a maximum likelihood (ML) detection algorithm having reduced numbers of signal points to be tested, for the quasi-orthogonal space-time code with four transmit antennas. When high-level modulation schemes are employed, the algorithm enables the quasi-orthogonal code to achieve near ML performance with a significant reduction in the computational load.

• 제어로봇시스템학회:학술대회논문집
• /
• 1991.10a
• /
• pp.120-124
• /
• 1991

In this paper, we consider the maneuvering detection and target tracking problem in uncertain linear discrete-time systems. The maneuvering detection is based on X$^{2}$ test[2,71, where Kalman filters have been utilized so far. The target tracking is performed by the maneuvering input compensation based on a maximum likelihood estimator. KF has been known to diverge when some modelling errors exist and fail to detect the maneuvering and to track the target in uncertain systems. Thus this paper adopt the FIR filter[l], which is known to be robust to modelling errors, for maneuvering detection and target tracking problem. Various computer simulations show the superior performance of the FIR filter in this problem.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.5 no.12
• /
• pp.2315-2325
• /
• 2011

We propose a novel reduced-state maximum-likelihood sequence detection (MLSD) structure using the Viterbi algorithm based on the second-order Volterra kernel modeling nonlinear distortion due to square law detection of multipath channels commonly occurring in chromatic dispersion (CD) or polarization mode dispersion (PMD) in optical communication systems. While all existing MLSD methods for square-law detection receivers are based on direct computation of branch metrics, the proposed algorithm provides an efficient and structured way to implement reduced-state MLSD with almost the same complexity of a MLSD for linear channels. As a result, the proposed algorithm reduces the number of parameters to be estimated and the complexity of computation.