• 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.

• 전자공학회논문지C
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• 제34C권2호
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• pp.50-60
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• 1997

Reconfiguration of a memory array using spare rows and columns has been known to be a useful technique to improve the yield. When the numbers of spare rows and scolumns are limited, respectively, the repair problem is known to be NP-complete. In this paper, we propose the reconfiguration algorithm for an array of memory cells using faulty cel clustering, which removes rows and columns algrithm is the simplest reconfiguration method with the time complexity of $O(n^2)$, where n is the number of faulty cells, however the repair rate is very low. Whereas the exhaustive search algorithm has a high repair rate, but the time complexity is $O(2^n)$. The proposed algorithm provides the same repair rate as the exhaustive search algorithm for almost all cases and runs as fast as the greedy method. It has the time complexity of $O(n^3)$ in the worst case. We show that the propsed algorithm provides more efficient solutions than other algorithms using simulations.

• Journal of Power Electronics
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• 제18권1호
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• pp.129-136
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• 2018

An accurate state-of-charge (SOC) estimation ensures the reliable and efficient operation of a lithium-ion battery management system. On the basis of a combined electrochemical model, this study adopts the forgetting factor least squares algorithm to identify battery parameters and eliminate the influence of test conditions. Then, it implements online SOC estimation with high accuracy and low run time by utilizing the low computational complexity of the unscented Kalman filter (UKF) and the rapid convergence of a particle filter (PF). The PF algorithm is adopted to decrease convergence time when the initial error is large; otherwise, the UKF algorithm is used to approximate the actual SOC with low computational complexity. The effect of the number of sampling particles in the PF is also evaluated. Finally, experimental results are used to verify the superiority of the combined method over other individual algorithms.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권5호
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• pp.2141-2155
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• 2020

In order to meet the requirements of background change, illumination variation, moving shadow interference and high accuracy in object detection of moving camera, and strive for real-time and high efficiency, this paper presents an object detection algorithm based on sparse approximation recursion and sparse coding migration in subspace. First, low-rank sparse decomposition is used to reduce the dimension of the data. Combining with dictionary sparse representation, the computational model is established by the recursive formula of sparse approximation with the video sequences taken as subspace sets. And the moving object is calculated by the background difference method, which effectively reduces the computational complexity and running time. According to the idea of sparse coding migration, the above operations are carried out in the down-sampling space to further reduce the requirements of computational complexity and memory storage, and this will be adapt to multi-scale target objects and overcome the impact of large anomaly areas. Finally, experiments are carried out on VDAO datasets containing 59 sets of videos. The experimental results show that the algorithm can detect moving object effectively in the moving camera with uniform speed, not only in terms of low computational complexity but also in terms of low storage requirements, so that our proposed algorithm is suitable for detection systems with high real-time requirements.

• Journal of Communications and Networks
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• 제13권3호
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• pp.232-239
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• 2011

This paper investigates the user selection problem of successive zero-forcing precoded multiuser multiple-input multiple-output (MU-MIMO) downlink systems, in which the base station and mobile receivers are equipped with multiple antennas. Assuming full knowledge of the channel state information at the transmitter, dirty paper coding (DPC) is an optimal precoding strategy, but practical implementation is difficult because of its excessive complexity. As a suboptimal DPC solution, successive zero-forcing DPC (SZF-DPC) was recently proposed; it employs partial interference cancellation at the transmitter with dirty paper encoding. Because of a dimensionality constraint, the base station may select a subset of users to serve in order to maximize the total throughput. The exhaustive search algorithm is optimal; however, its computational complexity is prohibitive. In this paper, we develop two low-complexity user scheduling algorithms to maximize the sum rate capacity of MU-MIMO systems with SZF-DPC. Both algorithms add one user at a time. The first algorithm selects the user with the maximum product of the maximum column norm and maximum eigenvalue. The second algorithm selects the user with the maximum product of the minimum column norm and minimum eigenvalue. Simulation results demonstrate that the second algorithm achieves a performance similar to that of a previously proposed capacity-based selection algorithm at a high signal-to-noise (SNR), and the first algorithm achieves performance very similar to that of a capacity-based algorithm at a low SNR, but both do so with much lower complexity.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제5권11호
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• pp.2052-2067
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• 2011

Complementary trees are two spanning trees rooted at the sink node satisfying that any source node's two paths to the sink node on the two trees are node-disjoint. Complementary trees routing strategy is a special node-disjoint multi-path routing approach. Several complementary trees routing algorithms have been proposed, in which path discovery methods based on depth first search (DFS) or Dijkstra's algorithm are used to find a path for augmentation in each round of path augmentation step. In this paper, a novel path discovery method based on multi-tree-growing (MTG) is presented for the first time to our knowledge. Based on this path discovery method, a complementary trees routing algorithm is developed with objectives of low average path length on both spanning trees and low complexity. Measures are employed in our complementary trees routing algorithm to add a path with nodes near to the sink node in each round of path augmentation step. The simulation results demonstrate that our complementary trees routing algorithm can achieve low average path length on both spanning trees with low running time, suitable for wireless sensor networks in industrial scenarios.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제5권8호
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• pp.1444-1456
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• 2011

This paper presents a low-complexity algorithm for an H.264/AVC encoder. The proposed motion estimation scheme determines the best coding mode for a given macroblock (MB) by finding motion-blurred MBs; identifying, before motion estimation, an early selection of MBs; and hence saving processing time for these MBs. It has been observed that human vision is more sensitive to the movement of well-structured objects than to the movement of randomly structured objects. This study analyzed permissible perceptual distortions and assigned a larger inter-mode value to the regions that are perceptually less sensitive to human vision. Simulation results illustrate that the algorithm can reduce the computational complexity of motion estimation by up to 47.16% while maintaining high compression efficiency.

• ETRI Journal
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• 제44권2호
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• pp.346-354
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• 2022

The SYN flooding attack is widely used in cyber attacks because it paralyzes the network by causing the system and bandwidth resources to be exhausted. This paper proposed a self-information approach for detecting the SYN flooding attack and provided a detection algorithm with a hierarchical policy on a detection time domain. Compared with other detection methods of entropy measurement, the proposed approach is more efficient in detecting the SYN flooding attack, providing low misjudgment, hierarchical detection policy, and low time complexity. Furthermore, we proposed a detection algorithm with limiting system resources. Thus, the time complexity of our approach is only (log n) with lower time complexity and misjudgment rate than other approaches. Therefore, the approach can detect the denial-of-service/distributed denial-of-service attacks and prevent SYN flooding attacks.

• 전자공학회논문지
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• 제51권5호
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• pp.11-19
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• 2014

본 논문에서는 고차 MIMO 시스템을 위한 저 복잡도의 병렬 구형 검출 알고리즘을 제안하였다. 제안된 알고리즘에서는 정적 가지치기와 가변 가능한 다수의 노드연산기에 의한 동적 가지치기 기법을 통해서 종래의 Fixed-complexity sphere decoder(FSD) 알고리즘 대비 더 낮은 복잡도를 갖게 되며, quasi-maximum likelihood 검출 성능을 보인다. 알고리즘과 함께 제안된 노드연산기 또한, 기존 구형검출기의 순차적 연산 구조를 갖는 노드 연산을 고정된 복잡도를 갖도록 제안하여 하드웨어 구현의 용이성을 제공한다. 16QAM 복조를 하는 고차 MIMO 무선통신의 몬테카를로 모의실험을 통해서, 종래의 저 복잡도를 갖는 FSD 알고리즘 대비, 제안된 알고리즘이 평균적으로 단 6.3%의 검출 시간이 증가되면서 평균 55% 탐색노드가 감소하여 연산 복잡도가 낮아지는 것을 보여주었다.

• 한국위성정보통신학회논문지
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• 제7권2호
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• pp.97-103
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• 2012

본 논문에서는 MIMO(Multi Input Multi Output) 시스템을 위한 적응형 검색범위 기반 복잡도 감소 QRD-M 기법을 제안한다. 기존의 fixed QRD-M 기법은 각 단계에서 survivor path들을 현 단계의 모든 가능한 성상도 심벌들로 확장하여 그 중 가장 작은 path metric을 가지는 M개를 선택한다. 성능의 저하를 최소화 하기 위해서는 큰 값의 M을 사용해야 하지만, 계산양 또한 증가하는 단점을 가진다. 이러한 단점을 보완하기 위해 측정된 평균 잡음 전력 값에 따라 survivor path의 개수나, 검색 범위를 적절히 조절하는 기법들이 제안되었다. 하지만 이 기법들에 채널 상태를 판별하기 위해 사용된 지표는 평균 잡음 전력 정보이므로 잡음 전력 값이 순간적으로 크게 변하는 경우 성능 저하를 가져올 수 있다. 제안된 기법에서는 수신 심벌 벡터와 QRD에 의해 임시적으로 추정된 심벌 벡터와의 Euclidean distance와 채널 행렬의 대각성분을 이용하여 순시적인 채널 정보를 추정하여 검색 범위를 적절히 조절하므로 기존의 기법의 단점을 보완한다. 실험 결과에서는 제안된 기법이 MLD(Maximum Likelihood Detection)의 성능에 근접하면서, 동일한 성능을 가지는 기존의 QRD-M 기법들에 비해 확연히 작은 복잡도를 가지는 것을 보인다.