• ETRI Journal
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• v.32 no.1
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• pp.163-165
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• 2010

A trend in 3D mesh compression is codec design with low computational complexity which preserves the input vertex and face order. However, this added information increases the complexity. We present a fast 3D mesh compression method that compresses the redundant shared vertex information between neighboring faces using simple first-order differential coding followed by fast entropy coding with a fixed length prefix. Our algorithm is feasible for low complexity designs and maintains the order, which is now part of the MPEG-4 scalable complexity 3D mesh compression standard. The proposed algorithm is 30 times faster than MPEG-4 3D mesh coding extension.

• JSTS:Journal of Semiconductor Technology and Science
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• v.16 no.4
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• pp.488-496
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• 2016

This paper presents a low-complexity non-iterative soft-decision Bose-Chaudhuri-Hocquenghem (SD-BCH) decoder architecture and design technique for wireless body area networks (WBANs). A SD-BCH decoder with test syndrome computation, a syndrome calculator, Chien search and metric check, and error location decision is proposed. The proposed SD-BCH decoder not only uses test syndromes, but also does not have an iteration process. The proposed SD-BCH decoder provides a 0.75~1 dB coding gain compared to a hard-decision BCH (HD-BCH) decoder, and almost similar coding gain compared to a conventional SD-BCH decoder. The proposed SD-BCH (63, 51) decoder was designed and implemented using 90-nm CMOS standard cell technology. Synthesis results show that the proposed non-iterative SD-BCH decoder using a serial structure can lead to a 75% reduction in hardware complexity and a clock speed 3.8 times faster than a conventional SD-BCH decoder.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.10
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• pp.3458-3478
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• 2022

Automatic modulation recognition is the core algorithm in the field of modulation classification in communication systems. Our investigations show that deep learning (DL) based modulation recognition techniques have achieved effective progress for multiple-input multiple-output (MIMO) systems. However, network complexity is always an additional burden for high-accuracy classifications, which makes it impractical. Therefore, in this paper, we propose a low-complexity dimensional interactive lightweight network (DilNet) for MIMO systems. Specifically, the signals received by different antennas are cooperatively input into the network, and the network calculation amount is reduced through the depth-wise separable convolution. A two-dimensional interactive attention (TDIA) module is designed to extract interactive information of different dimensions, and improve the effectiveness of the cooperation features. In addition, the TDIA module ensures low complexity through compressing the convolution dimension, and the computational burden after inserting TDIA is also acceptable. Finally, the network is trained with a penalized statistical entropy loss function. Simulation results show that compared to existing modulation recognition methods, the proposed DilNet dramatically reduces the model complexity. The dimensional interactive lightweight network trained by penalized statistical entropy also performs better for recognition accuracy in MIMO systems.

• ETRI Journal
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• v.32 no.6
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• pp.837-842
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• 2010

This paper proposes robust source localization methods for estimating the azimuth angle, elevation angle, velocity, and range using a low-complexity planar antenna array in impulsive non-Gaussian noise environments. The proposed robust source localization methods for wireless communication applications are based on nonlinear M-estimation provided from Huber and Hampel. Simulation results show the robustness performance of the proposed robust methods in impulsive non-Gaussian noise.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.22 no.7
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• pp.705-710
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• 2011

In this paper, we proposed the low computational complexity soft-decision e-BCH decoding algorithm based on the Chase algorithm. In order to make the test patterns, it is necessary to re-order the least reliable received symbols. In the process of ordering and finding optimal decoding symbols, high computational complexity is required. Therefore, this paper proposes the method of low computational complexity algorithm for soft-decision e-BCH decoding process.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.4
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• pp.1042-1058
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• 2024

Terahertz (THz) communication is becoming a key technology for future 6G wireless networks because of its ultra-wide band. However, the implementation of THz communication systems confronts formidable challenges, notably beam splitting effects and high computational complexity associated with them. Our primary objective is to design a hybrid precoder that minimizes the Euclidean distance from the fully digital precoder. The analog precoding part adopts the delay-phase alternating minimization (DP-AltMin) algorithm, which divides the analog precoder into phase shifters and time delayers. This effectively addresses the beam splitting effects within THz communication by incorporating time delays. The traditional digital precoding solution, however, needs matrix inversion in THz massive multiple-input multiple-output (MIMO) communication systems, resulting in significant computational complexity and complicating the design of the analog precoder. To address this issue, we exploit the characteristics of THz massive MIMO communication systems and construct the digital precoder as a product of scale factors and semi-unitary matrices. We utilize Schatten norm and Hölder's inequality to create semi-unitary matrices after initializing the scale factors depending on the power allocation. Finally, the analog precoder and digital precoder are alternately optimized to obtain the ultimate hybrid precoding scheme. Extensive numerical simulations have demonstrated that our proposed algorithm outperforms existing methods in mitigating the beam splitting issue, improving system performance, and exhibiting lower complexity. Furthermore, our approach exhibits a more favorable alignment with practical application requirements, underlying its practicality and efficiency.

• Journal of information and communication convergence engineering
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• v.4 no.1
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• pp.23-27
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• 2006

The discipline of software performance is very broad; it influences all aspects of the software development lifecycle, including architecture, design, deployment, integration, management, evolution and servicing. Thus, the complexity of software is an important aspect of development and maintenance activities. Much research has been dedicated to defining different software measures that capture what software complexity is. In most cases, the description of complexity is given to humans in forms of numbers. These quantitative measures reflect human-seen complexity with different levels of success. Software complexity growth has been recognized to be beyond human control. In this paper, we have focused our discussion on the increasing software complexity and the issue with the problems being faced in managing this complexity. This increasing complexity in turn affects the software productivity, which is declining with increase in its complexity.

• ETRI Journal
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• v.40 no.6
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• pp.699-713
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• 2018

Orthogonal frequency division multiplexing (OFDM) has been the overwhelmingly prevalent choice for high-data-rate systems due to its superior advantages compared with other modulation techniques. In contrast, a high peak-to-average-power ratio (PAPR) is considered the fundamental obstacle in OFDM systems since it drives the system to suffer from in-band distortion and out-of-band radiation. The partial transmit sequence (PTS) technique is viewed as one of several strategies that have been suggested to diminish the high PAPR trend. The PTS relies upon dividing an input data sequence into a number of subblocks. Hence, three common types of the subblock segmentation methods have been adopted - interleaving (IL-PTS), adjacent (Ad-PTS), and pseudorandom (PR-PTS). In this study, a new type of subblock division scheme is proposed to improve the PAPR reduction capacity with a low computational complexity. The results indicate that the proposed scheme can enhance the PAPR reduction performance better than the IL-PTS and Ad-PTS schemes. Additionally, the computational complexity of the proposed scheme is lower than that of the PR-PTS and Ad-PTS schemes.

• 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 Communications and Networks
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• v.18 no.3
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• pp.320-326
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• 2016

In existing literature on multiple-input multiple-output (MIMO) relaying communication systems, antenna selection is often implemented by maximizing the channel capacity or the output single-to-noise ratio (SNR). In this paper, we propose an energy-efficient low-complexity antenna selection scheme for MIMO relaying communication systems. The proposed algorithm is based on beamforming and maximizing the Frobenius norm to jointly optimize the transmit power, number of active antennas, and antenna subsets at the source, relaying and destination. We maximize the energy efficiency between the link of source to relay and the link of relay to destination to obtain the maximum energy efficiency of the system, subject to the SNR constraint. Compared to existing antenna selection methods forMIMO relaying communication systems, simulation results demonstrate that the proposed method can save more power in term of energy efficiency, while having lower computational complexity.