• Journal of Communications and Networks
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• v.10 no.4
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• pp.396-402
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• 2008

The use of network coding in wireless networks has been proposed in the literature for energy efficient broadcast. However, the decoding complexity of existing algorithms is too high for low-complexity devices. In this work we formalize the all-to-all information exchange problem and shows how to optimize the transmission scheme in terms of energy efficiency. Furthermore, we prove by construction that there exists O(1) -complexity network coding algorithms for grid networks which can achieve such optimality. We also present low-complexity heuristics for random. topology networks. Simulation results show that network coding algorithms outperforms forwarding algorithms in most cases.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.3C
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• pp.205-215
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• 2007

This paper presents low latency and/or computation algorithms of iterative codes of turbo codes, turbo product codes and low density parity check codes for use in wireless broadband communication systems. Due to high coding complexity of iterative codes, this paper focus on lower complexity and/or latency algorithms that are easily implementable in hardware and further accelerate the decoding speed.

• Journal of Electrical Engineering and Technology
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• v.11 no.4
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• pp.1020-1026
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• 2016

Motion estimation (ME) algorithms supporting quarter-pixel accuracy have been recently introduced to retain detailed motion information for high quality of video in the state-of-the-art video compression standard of H.264/AVC. Conventional sub-pixel ME algorithms in the spatial domain are faced with a common problem of computational complexity because of embedded interpolation schemes. This paper proposes a low-complexity sub-pixel motion estimation algorithm in the transform domain utilizing shifting matrix. Simulations are performed to compare the performances of spatial-domain ME algorithms and transform-domain ME algorithms in terms of peak signal-to-noise ratio (PSNR) and the number of bits per frame. Simulation results confirm that the transform-domain approach not only improves the video quality and the compression efficiency, but also remarkably alleviates the computational complexity, compared to the spatial-domain approach.

• IEMEK Journal of Embedded Systems and Applications
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• v.13 no.1
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• pp.1-8
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• 2018

This paper proposes a low complexity super resolution algorithm for frequency modulated continuous wave (FMCW) radar systems for foreign object debris (FOD) detection. FOD radar has a requirement to detect foreign object in small units in a large area. However, The fast Fourier transform (FFT) method, which is most widely used in FMCW radar, has a disadvantage in that it can not distinguish between adjacent targets. Super resolution algorithms have a significantly higher resolution compared with the detection algorithm based on FFT. However, in the case of the large number of samples, the computational complexity of the super resolution algorithms is drastically high and thus super resolution algorithms are difficult to apply to real time systems. In order to overcome this disadvantage of super resolution algorithm, first, the proposed algorithm coarsely obtains the frequency of the beat signal by employing FFT. Instead of using all the samples of the beat signal, the number of samples is adjusted according to the frequency of the beat signal. By doing so, the proposed algorithm significantly reduces the computational complexity of multiple signal classifier (MUSIC) algorithm. Simulation results show that the proposed method achieves accurate location even though it has considerably lower complexity than the conventional super resolution algorithms.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.4C
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• pp.217-225
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• 2011

In this paper, we propose an adaptive de-interlacing algorithm that is based on the degree of local complexity. The conventional intra field de-interlacing algorithms show the different performance according to the ways which find the edge direction. Furthermore, FDD (Fine Directional De-interlacing) algorithm has the better performance than other algorithms but the computational complexity of FDD algorithm is too high. In order to alleviate these problems, the proposed algorithm selects the most efficient de-interacing algorithm among LA (Line Average), MELA (Modified Edge-based Line Average), and LCID (Low-Complexity Interpolation Method for De-interlacing) algorithms which have low complexity and good performance. The proposed algorithm is trained by the DoLC (Degree of Local Complexity) for selection of the algorithms mentioned above. Simulation results show that the proposed algorithm not only has the low complexity but also performs better objective and subjective image quality performances compared with the conventional intra-field methods.

• 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.

• ETRI Journal
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• v.27 no.5
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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.

• 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.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.11C
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• pp.1581-1591
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• 2004

In this paper, we investigate the design of three low-complexity joint estimation algorithms(LJEAs) for frequency offset and carrier phase. The proposed LJEAs are based on the interpolation technique of correlation values of the received signal in frequency and phase domains. With these algorithms, the estimation ranges $\Delta$f$_{d}$${\times}$T$_{s}$ . are less than 1/2N$_{s}$ , and 1/N$_{s}$ which are comparable to conventional algorithms. The Proposed LJEAs require only 2N$_{s}$ or 4N$_{s}$ complex multiplications which are very simple compared with the conventional algorithms. Nevertheless the estimation accuracies of the LJEAs are as good as those of the conventional algorithms. Suitable areas of application include joint estimation of frequency offset and carrier phase in burst-mode digital transmission such as satellite communications.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.10
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• pp.3921-3944
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• 2015

Currently Energy-Saving (ES) methods in cellular networks could be improved, as compensation method for irregular Base Station (BS) deployment is not effective, most regional ES algorithm is complex, and performance decline caused by ES action is not evaluated well. To resolve above issues, a low-complexity energy efficient BS cooperation mechanism for Long Time Evolution (LTE) networks is proposed. The mechanism firstly models the ES optimization problem with coverage, resource, power and Quality of Service (QoS) constraints. To resolve the problem with low complexity, it is decomposed into two sub-problems: BS Mode Determination (BMD) problem and User Association Optimization (UAO) problem. To resolve BMD, regional dynamic multi-stage algorithms with BS cooperation pair taking account of load and geographic topology is analyzed. And then a distributed heuristic algorithm guaranteeing user QoS is adopted to resolve UAO. The mechanism is simulated under four LTE scenarios. Comparing to other algorithms, results show that the mechanism can obtain better energy efficiency with acceptable coverage, throughput, and QoS performance.