• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.11
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• pp.2405-2411
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• 2009

MMSE, ZF and ML are the decoding mechanisms for V-BLAST system, and ML shows the best performance decoding the original signal among them. However, it has a problem that the computation complexity is increased exponentially according to the number of transmit antennas and transmit degrees. In this paper, we propose a low complexity linear ML detection algorithm having low computation complexity, then analyze the system performance in BER and computation complexity comparing with other algorithms. In the simulation, the BER performance of the proposed algorithm is superior than ZF and MMSE detection algorithms, and similar to ML detection algorithm. However, its computation complexity was 50% less than ML algorithm. From the results, we confirm that the proposed algorithm is superior than other ML detection algorithms.

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

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.10a
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• pp.506-509
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• 2009

This paper studies about reducing the complexity of ML detection in MIMO/V-blast system, based on MMSE and ZF linear detectors. Beforehand, the receiver detects the signal using the linear detector such as ZF or MMSE. Moreover, the next step is to assess whether the signal is reliable or not by verifying the reliability condition, if the latter is reliable then it is the output if not it has to be detected by the advanced detector until the reliability condition is verified.

• 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.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.1
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• pp.126-130
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• 2005

In this paper, a low-complexity maximum-likelihood (ML) decoder based on QR decomposition, called real-valued LCMLDec decoder or RVLCMLDec for short, is proposed for the Vertical Bell Labs Layered Space-Time (V-BLAST) architecture, a promising candidate for providing high data rates in future fixed wireless communication systems [1]. Computer simulations, in comparison with other detection techniques, show that the proposed decoder is capable of providingthe V-BLAST schemes with ML performance at low detection complexity.

• 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 $1.0{\leq}K_p{\leq}3.0$.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.46 no.5
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• pp.88-94
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• 2009

We propose a scheme which reduce the computational complexity of the lattice reduction (LR) aided detector in MIMO system. The performance of the ML detection algorithm is good but the computational complexity grows exponentially with the number of antenna elements and constellation points. LR aided detector shows the same diversity with the ML scheme with relatively less complexity. But the LR scheme still requires many computations since it involves several iterations of size reduction and column vector exchange. We notice that the LR process depends not on the received signal but only on the channel matrix so we can apply LR process offline and store the results in Look-Up Table (LUT). In this paper we propose an algorithm to generate the LUT which require less memory requirement and we evaluate the performance and complexity of the proposed system. We show that the proposed system requires less computational complexity with similar detection performance compared with the conventional LR aided detector.

• 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.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2006.05a
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• pp.107-110
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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. By stacking received symbols from different received symbolduration and applying QR decomposition resulting the special format of upper triangular matrix R, 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.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.42 no.4
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• pp.731-738
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• 2017

In this paper, we proposed a modified ML detector for generalized spatial modulation which is a method among Multiple-input Multiple-output. This proposed method detects signal applying modified channel statement information based on priority. Complexity in conventional methods increases as increasing the number of active antennas. To solve this problem, we proposed a new ML method using static channel information decided by the number of transmit antennas and the number of receive antennas. This method detects active antennas one by one through priority. The proposed method has proved benefit on complexity compared with conventional method through simulations. When the number of transmit antennas is equal to 10, there is approximately 45% complexity reduction.