• ETRI Journal
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• v.35 no.3
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• pp.371-377
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• 2013

An effective signal detection algorithm with low complexity is presented for multiple-input multiple-output orthogonal frequency division multiplexing systems. The proposed technique, QR-MLD, combines the conventional maximum likelihood detection (MLD) algorithm and the QR algorithm, resulting in much lower complexity compared to MLD. The proposed technique is compared with a similar algorithm, showing that the complexity of the proposed technique with T=1 is a 95% improvement over that of MLD, at the expense of about a 2-dB signal-to-noise-ratio (SNR) degradation for a bit error rate (BER) of $10^{-3}$. Additionally, with T=2, the proposed technique reduces the complexity by 73% for multiplications and 80% for additions and enhances the SNR performance about 1 dB for a BER of $10^{-3}$.

• Journal of Computing Science and Engineering
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• v.6 no.4
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• pp.310-319
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• 2012

Next generation wireless receivers demand low computational complexity algorithms with high computing power in order to perform fast signal detections and error estimations. Several signal detection and estimation algorithms have been proposed for next generation wireless receivers which are primarily designed to provide reasonable performance in terms of signal to noise ratio (SNR) and bit error rate (BER). However, none of them have been chosen for direct implementation as they offer high computational complexity with relatively lower computing power. This paper presents a low-complexity power-efficient algorithm that improves the computing power and provides relatively faster signal detection for next generation wireless multiuser receivers. Measurement results of the proposed algorithm are provided and the overall system performance is indicated by BER and the computational complexity. Finally, in order to verify the low-complexity of the proposed algorithm we also present a formal mathematical proof.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.2232-2235
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• 2003

In speech communication systems where two different speech codecs are interoperated, transcoding algorithm is a good approach because of its low complexity and improved synthesized speech quality. This paper proposes an efficient method to further improve the performance of transcoding algorithms as well as to reduce the complexity. In the conventional transcoding algorithms. a post-filter and a perceptual weighting filter should be operated sequentially because both decoding and encoding processes are needed. This results in the redundancy of the processing in terms of complexity and perceptual quality. Using the fact that their filter structures are similar, we replaced the two filters with one. The proposed algorithm requires 72.8% lower complexity than the conventional transcoding algorithm when we compare only the complexity of the filtering processes. The results of both objective and subjective tests verify that the proposed algorithm has slightly better quality than the conventional one.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.4C
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• pp.303-309
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• 2006

By combining the space-time diversity technique and iterative turbo codes, space-time turbo codes(STTCS) are able to provide powerful error correction capability. However, the multi-path transmission and iterative decoding structure of STTCS make the decoder very complex. In this paper, we propose a low complexity decoder, which can be used to decode STTCS as well as general iterative codes such as turbo codes. The efficient implementation of the backward recursion and the log-likelihood ratio(LLR) update in the proposed algorithm improves the computational efficiency. In addition, if we approximate the calculation of the joint LLR by using the approximate ratio(AR) algorithm, the computational complexity can be reduced even further. A complexity analysis and computer simulations over the Rayleigh fading channel show that the proposed algorithm necessitates less than 40% of the additions required by the conventional Max-Log-MAP algorithm, while providing the same overall performance.

• Proceedings of the KIEE Conference
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• 2004.05a
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• pp.56-58
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• 2004

In this paper, we propose an adaptive beamforming algorithm for array antenna. The proposed beamforming algorithm is based on EDS (Euclidean Direction Search) algorithm. Generally LMS algorithm has a much slower rate of convergence, but its low computational complexity and robustness make it a representative method of adaptive beamforming. Although the RLS algorithm is known for its fast convergence to the optimal Wiener solution, it still suffers from high computational complexity and poor performance. The proposed EDS algorithm has a rapid convergence better than LMS algorithm, and has a computational more simple complexity than RLS algorithm. In this paper we compared the efficiency of the EDS algorithm with a standard LMS algorithm.

• Journal of Korea Multimedia Society
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• v.21 no.8
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• pp.813-820
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• 2018

This paper proposes new frame rate up-conversion algorithms. Adaptive motion estimation based on block complexity information are used to obtain more accurate motion vectors. Because the information on block complexity is extracted from the motion estimation prediction size from the original frame, additional computational complexity is not imparted. In experimental results, the proposed algorithms provide robust frame interpolation performance for whole test sequences. Also, the computational complexity of the proposed algorithm is reduced to a benchmark algorithm.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.4
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• pp.258-264
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• 2004

This paper propose a method that GOP structure based on the picture complexity change realtime adaptive without pre-analysis or time delay. Proposed algorithm calculates the complexity of pictures at first, and the ratio of the complexity( X$\sub$p/ /X$\sub$i/) between P picture and I picture is calculated. The suitable M value for the three picture select by comparing with predetermined threshold. Used bit and vbv_delay the value of GOP is calculated according to selected M. Experimental results show that the prediction error is reduce than the fixed GOP structure. Since the complexity distribution of the sequence is different, applied limits of threshold value is changed, also.

• Journal of Korea Society of Digital Industry and Information Management
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• v.9 no.3
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• pp.21-30
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• 2013

Powell-Miller theory is a good method to express or treat incorrect information. But it has limitation that requires too much time to apply to actual situation because computational complexity increases in exponential and functional way. Accordingly, there have been several attempts to reduce computational complexity but side effect followed - certainty factor fell. This study suggested expanded Approximation Algorithm. Expanded Approximation Algorithm is a method to consider both smallest supersets and largest subsets to expand basic space into a space including inverse set and to reduce Approximation error. By using expanded Approximation Algorithm suggested in the study, basic probability assignment function value of subsets was alloted and added to basic probability assignment function value of sets related to the subsets. This made subsets newly created become Approximation more efficiently. As a result, it could be known that certain function value which is based on basic probability assignment function is closely near actual optimal result. And certainty in correctness can be obtained while computational complexity could be reduced. by using Algorithm suggested in the study, exact information necessary for a system can be obtained.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.2A
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• pp.100-107
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• 2011

Algorithms based on the QR decomposition of the equivalent space-time channel matrix have been proved useful in the detection of V-BLAST systems. Especially, the parallel detection (PD) algorithm offers ML approaching performance up to 4 transmit antennas with reasonable complexity. We show that when directly applied to STBCs, the PD algorithm may suffer a rather significant SNR degradation over ML detection, especially at high SNRs. However, simply extending the PD algorithm to allow p ${\geq}$ 2 candidate layers, i.e. p-PD, regains almost all the loss but only at a significant increase in complexity. Here, we propose a simplification to the p-PD algorithm specific to STBCs without a corresponding sacrifice in performance. The proposed algorithm results in significant complexity reductions for moderate to high order modulations.

• The Journal of the Acoustical Society of Korea
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• v.28 no.3E
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• pp.93-98
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• 2009

In this paper, we propose a new VSS-NLMS algorithm through a simple modification of the conventional NLMS algorithm, which leads to a low complexity algorithm with enhanced performance. The step size of the proposed algorithm becomes smaller as the error signal is getting orthogonal to the input vector. We also show that the proposed algorithm is an approximated normalized version of the KZ-algorithm and requires less computation than the KZ-algorithm. We carried out a performance comparison of the proposed algorithm with the conventional NLMS and other VSS algorithms using an adaptive channel equalization model. It is shown that the proposed algorithm presents good convergence characteristics under both stationary and non-stationary environments despites its low complexity.