• ETRI Journal
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• 제27권5호
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• pp.639-642
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• 2005

This paper proposes two kinds of complexity-reduced algorithms for a low density parity check (LDPC) decoder. First, sequential decoding using a partial group is proposed. It has the same hardware complexity and requires a fewer number of iterations with little performance loss. The amount of performance loss can be determined by the designer, based on a tradeoff with the desired reduction in complexity. Second, an early detection method for reducing the computational complexity is proposed. Using a confidence criterion, some bit nodes and check node edges are detected early on during decoding. Once the edges are detected, no further iteration is required; thus early detection reduces the computational complexity.

• 한국항행학회논문지
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• 제15권3호
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• pp.392-404
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• 2011

본 논문에서는 최근 4세대 이동통신에서 논의 되고 있는 기술인 셀 간 협력 통신이 가능한 다중 셀 환경에서 상향링크에서의 다중 사용자 신호 검출기술에 대해서 다루었다. 먼저 기존 검출 기술로 ML, ZF, MMSE 그리고 SIC 등을 다루었고, 보통 ML은 최적의 성능을 보이지만, 복잡도가 지수적으로 증가하며, ZF나 MMSE는 간단하지만 성능이 떨어지며, SIC는 복잡하고 오류전파 현상이 발행 할 수 있는 문제점을 가지고 있다. 이에 기존의 ZF/MMSE 에 비해서는 성능 개선이 이루어지면서, 복잡도를 유지 또는 감소시킬 수 있는 구조 제안을 위해서 ZF/MMSE 방식과 ML 의 적용구조를 단순화 시킨 부분 ML 복호 방식을 결합한 검출 방식을 제안하였다. 모의실험 결과, 제안방식은 ZF/MMSE 기반의 SIC 방식에 비해 BER 성능이 개선 또는 유지 되었으며, 복잡도 측면에서 감소하는 효과를 보였으며, 또한 복잡도 감소는 협력 기지국 및 안테나 수가 증가할수록 더 감소 효과가 커질 수 있음을 알 수 있었다.

• Journal of electromagnetic engineering and science
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• 제9권4호
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• pp.194-201
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• 2009

In this paper, a new spectrum sensing method based on energy detection is proposed and analyzed in a cognitive radio(CR) system. We employ a delay diversity receiver for sensing the primary user's spectrum with reasonable cost and complexity. Conventional CR with the receiver equipping multiple antennas requires additional hardware and space for installing multiple antennas in accordance with increase in the number of antennas. If the number of antennas increases, detection probability as well as hardware complexity and cost rise. Then, it is difficult to make a primary user detector practically. Therefore, we adopt a delay diversity receiver for solving problems of the conventional spectrum detector utilizing multiple antennas. We derive analytical expressions for the spectrum sensing performance of the proposed system. From the simulation results, it is demonstrated that the primary user detector with the delay diversity receiver has almost half the complexity and shows similar or improved performance as compared with that employing multiple antennas. Therefore, the proposed spectrum sensing structure can be a practical solution for enhancing the detection capacity in CR system operations. The results of this paper can be applied to legacy CR systems with simple modifications.

• 한국멀티미디어학회논문지
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• 제19권8호
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• pp.1310-1319
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• 2016

Face detection is the first step in a wide range of face applications. However, detecting faces in the wild is still a challenging task due to the wide range of variations in pose, scale, and occlusions. Recently, many deep learning methods have been proposed for face detection. However, further improvements are required in the wild. Another important issue to be considered in the face detection is the computational complexity. Current state-of-the-art deep learning methods require a large number of patches to deal with varying scales and the arbitrary image sizes, which result in an increased computational complexity. To reduce the complexity while achieving better detection accuracy, we propose a fully convolutional network-based face detection that can take arbitrarily-sized input and produce feature maps (heat maps) corresponding to the input image size. To deal with the various face scales, a multi-scale network architecture that utilizes the facial components when learning the feature maps is proposed. On top of it, we design multi-task learning technique to improve detection performance. Extensive experiments have been conducted on the FDDB dataset. The experimental results show that the proposed method outperforms state-of-the-art methods with the accuracy of 82.33% at 517 false alarms, while improving computational efficiency significantly.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제2권3호
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• pp.135-149
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• 2008

Traditional attack detection schemes based on packets or flows have very high computational complexity. And, network based anomaly detection schemes can reduce the complexity, but they have a limitation to figure out the pattern of the distributed global scale network attack. In this paper, we propose an efficient and fast method for detecting distributed global-scale network attack symptoms in high-speed backbone networks. The proposed method is implemented at the aggregate traffic level. So, our proposed scheme has much lower computational complexity, and is implemented in very high-speed backbone networks. In addition, the proposed method can detect attack patterns, such as attacks in which the target is a certain host or the backbone infrastructure itself, via collaboration of edge routers on the backbone network. The effectiveness of the proposed method are demonstrated via simulation.

• ETRI Journal
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• 제32권3호
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• pp.479-481
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• 2010

An optimal multiuser detection algorithm with a computational complexity of O(K log K) is proposed for the class of linear multiple-access systems which have constant cross-correlation values. Here the optimal multiuser detection is implemented by searching for a monotone sequence with maximum likelihood, under the ranking of sufficient statistics. The proposed algorithm is intuitive and concise. It is carried out in just two steps, and at each step only one kind of operation is performed. Also, the proposed algorithm can be extended to more complex systems having more than a single cross-correlation value.

• Journal of Communications and Networks
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• 제10권1호
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• pp.44-54
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• 2008

In this paper, an iterative multiple symbol differential detection for turbo coded differential unitary space-time modulation using a posteriori probability (APP) demodulator is investigated. Two approaches of different complexity based on linear prediction are presented to utilize the temporal correlation of fading for the APP demodulator. The first approach intends to take account of all possible previous symbols for linear prediction, thus requiring an increase of the number of trellis states of the APP demodulator. In contrast, the second approach applies Viterbi algorithm to assist the APP demodulator in estimating the previous symbols, hence allowing much reduced decoding complexity. These two approaches are found to provide a trade-off between performance and complexity. It is shown through simulation that both approaches can offer significant BER performance improvement over the conventional differential detection under both correlated slow and fast Rayleigh flat-fading channels. In addition, when comparing the first approach to a modified bit-interleaved turbo coded differential space-time modulation counterpart of comparable decoding complexity, the proposed decoding structure can offer performance gain over 3 dB at BER of $10^{-5}$.

• Journal of Computing Science and Engineering
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• 제6권4호
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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.

• Journal of Communications and Networks
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• 제18권1호
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• pp.27-39
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• 2016

This paper derives and analyzes a novel block fast Fourier transform (FFT) based joint detection algorithm. The paper compares the performance and complexity of the novel block-FFT based joint detector to that of the Cholesky based joint detector and single user detection algorithms. The novel algorithm can operate at chip rate sampling, as well as higher sampling rates. For the performance/complexity analysis, the time division duplex (TDD) mode of a wideband code division multiplex access (WCDMA) is considered. The results indicate that the performance of the fast FFT based joint detector is comparable to that of the Cholesky based joint detector, and much superior to that of single user detection algorithms. On the other hand, the complexity of the fast FFT based joint detector is significantly lower than that of the Cholesky based joint detector and less than that of the single user detection algorithms. For the Cholesky based joint detector, the approximate Cholesky decomposition is applied. Moreover, the novel method can also be applied to any generic multiple-input-multiple-output (MIMO) system.

• 디지털산업정보학회논문지
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• 제17권1호
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• pp.7-14
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• 2021

With the increased attention about healthcare and management of heart diseases, smart healthcare services and related devices have been actively developed recently. R wave is the largest representative signal among ECG signals. R wave detection is very important because it detects QRS pattern and classifies arrhythmia. Several R wave detection algorithms have been proposed with different features, but the remaining problem is their implementation in low-cost portable platforms for real-time applications. In this paper, we propose R wave detection based on optimal threshold and arrhythmia classification through QRS pattern considering complexity in smart healthcare environments. For this purpose, we detected R wave from noise-free ECG signal through the preprocessing method. Also, we classify premature ventricular contraction arrhythmia in realtime through QRS pattern. The performance of R wave detection and premature ventricular contraction arrhythmia classification is evaluated by using 9 record of MIT-BIH arrhythmia database that included over 30 premature ventricular contraction. The achieved scores indicate the average of 98.72% in R wave detection and the rate of 94.28% in PVC classification.