• Title/Summary/Keyword: Computational complexity

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Nulling algorithm design using approximated gradient method (근사화된 Gradient 방법을 사용한 널링 알고리즘 설계)

  • Shin, Chang Eui;Choi, Seung Won
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.9 no.1
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    • pp.95-102
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    • 2013
  • This paper covers nulling algorithm. In this algorithm, we assume that nulling points are already known. In general, nulling algorithm using matrix equation was utilized. But, this algorithm is pointed out that computational complexity is disadvantage. So, we choose gradient method to reduce the computational complexity. In order to further reduce the computational complexity, we propose approximate gradient method using characteristic of trigonometric functions. The proposed method has same performance compared with conventional method while having half the amount of computation when the number of antenna and nulling point are 20 and 1, respectively. In addition, we could virtually eliminate the trigonometric functions arithmetic. Trigonometric functions arithmetic cause a big problem in actual implementation like FPGA processor(Field Programmable gate array). By utilizing the above algorithm in a multi-cell environment, beamforming gain can be obtained and interference can be reduced at same time. By the above results, the algorithm can show excellent performance in the cell boundary.

A new fractal image decoding algorithm with fast convergence speed (고속 수렴 속도를 갖는 새로운 프랙탈 영상 복호화 알고리듬)

  • 유권열;문광석
    • Journal of the Korean Institute of Telematics and Electronics S
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    • v.34S no.8
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    • pp.74-83
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    • 1997
  • In this paper, we propose a new fractal image decoding algorithm with fast convergence speed by using the data dependence and the improved initial image estimation. Conventional method for fractal image decoding requires high-degrdd computational complexity in decoding process, because of iterated contractive transformations applied to whole range blocks. On proposed method, Range of reconstruction imagte is divided into referenced range and data dependence region. And computational complexity is reduced by application of iterated contractive transformations for the referenced range only. Data dependence region can be decoded by one transformations when the referenced range is converged. In addition, more exact initial image is estimated by using bound () function in case of all, and an initial image more nearer to a fixed point is estimated by using range block division estimation. Consequently, the convergence speed of reconstruction iamge is improved with 40% reduction of computational complexity.

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Complex LMS Fuzzy Adaptive Equalizer with Decision Feedback (판정궤환이 있는 복소 LMS 퍼지 적응 등화기)

  • 이상연;김재범;이기용;이충웅
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.21 no.10
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    • pp.2579-2585
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    • 1996
  • In this paper, a complex fuzzy adaptive decision feedback equalizer(CFADFE) based on the LMS algorithm is proposed. The propoed equalizer is based on the complex fuzzy adaptive equalizer. The CFADFE isconstructed from a set of changeable complex fuzzy IF-THEN rules, where the 'IF' part of the rule is characterized by the state from a set of changealble complex fuzzy IF-THEN rules, where the 'IF' part of the rule is characterized by the state of the desision feedback. the role of decision feedback is to reduce the computational complexity. Computer simulation of the decision feedback. The role of decision feedback is to reduce the computational complexity. Computer simulation shosw that the CFADFE notonly reduces the computational complexity but also improves the performance compared with the conventional complex fuzzy adaptive equalizers. We also show that the adaptation speed is greatly improved by incorporating some linguistic information about the channel into the equalzer. It is applied to M-ary QAM digital communication system with linear and nonlinear complex channel characteristics.

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STBC-OFDM Decoding Method for Fast-Fading Channels

  • Lee, Kyu-In;Kim, Jae-Kwon;Cho, Yong-Soo
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.32 no.2C
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    • pp.160-165
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    • 2007
  • In this paper, we propose a novel signal detection method that achieves the maximum likelihood (ML) performance but requires much less computational complexity than the ML detection. When the well-known linear decoding method is used for space-time block coded (STBC) OFDM systems in fast-fading channels, co-channel interference (CCI) as well as inter-carrier interference (ICI) occurs. A maximum likelihood (ML) method can be employed to deal with the CCI; however, its computational complexity is very high. In this paper, we propose a signal detection method for orthogonal space-time coded OFDM systems that achieves the similar error performance as the ML method, but requires much less computational complexity.

Design of Adaptive Beamforming Antenna using EDS Algorithm (EDS 알고리즘을 이용한 적응형 빔형성 안테나 설계)

  • Kim, Sung-Hun;Oh, Jung-Keun;You, Kwan-Ho
    • 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.

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Effect of Potential Model Pruning on Official-Sized Board in Monte-Carlo GO

  • Oshima-So, Makoto
    • International Journal of Computer Science & Network Security
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    • v.21 no.6
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    • pp.54-60
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    • 2021
  • Monte-Carlo GO is a computer GO program that is sufficiently competent without using knowledge expressions of IGO. Although it is computationally intensive, the computational complexity can be reduced by properly pruning the IGO game tree. Here, I achieve this by using a potential model based on the knowledge expressions of IGO. The potential model treats GO stones as potentials. A specific potential distribution on the GO board results from a unique arrangement of stones on the board. Pruning using the potential model categorizes legal moves into effective and ineffective moves in accordance with the potential threshold. Here, certain pruning strategies based on potentials and potential gradients are experimentally evaluated. For different-sized boards, including an official-sized board, the effects of pruning strategies are evaluated in terms of their robustness. I successfully demonstrate pruning using a potential model to reduce the computational complexity of GO as well as the robustness of this effect across different-sized boards.

Low-Complexity Lattice Reduction Aided MIMO Detectors Using Look-Up Table (Look-Up Table 기반의 복잡도가 낮은 Lattice Reduction MIMO 검출기)

  • Lee, Chung-Won;Lee, Ho-Kyoung;Heo, Seo-Weon
    • 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.

Low Complexity Iterative Detection and Decoding using an Adaptive Early Termination Scheme in MIMO system (다중 안테나 시스템에서 적응적 조기 종료를 이용한 낮은 복잡도 반복 검출 및 복호기)

  • Joung, Hyun-Sung;Choi, Kyung-Jun;Kim, Kyung-Jun;Kim, Kwang-Soon
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.36 no.8C
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    • pp.522-528
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    • 2011
  • The iterative detection and decoding (IDD) has been shown to dramatically improve the bit error rate (BER) performance of the multiple-input multiple-output (MIMO) communication systems. However, these techniques require a high computational complexity since it is required to compute the soft decisions for each bit. In this paper, we show IDD comprised of sphere decoder with low-density parity check (LDPC) codes and present the tree search strategy, called a layer symbol search (LSS), to obtain soft decisions with a low computational complexity. In addition, an adaptive early termination is proposed to reduce the computational complexity during an iteration between an inner sphere decoder and an outer LDPC decoder. It is shown that the proposed approach can achieve the performance similar to an existing algorithm with 70% lower computational complexity compared to the conventional algorithms.

Low Computational Complexity LDPC Decoding Algorithms for DVB-S2 Systems (DVB-S2 시스템을 위한 저복잡도 LDPC 복호 알고리즘)

  • Jung Ji-Won
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
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    • v.16 no.10 s.101
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    • pp.965-972
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    • 2005
  • In this paper, we first review LDPC codes in general and a belief propagation algorithm that works in logarithm domain. LDPC codes, which is chosen for second generation digital video broadcasting standard, are required a large number of computation due to large size of coded block and iteration. Therefore, we presented two kinds of low computational algorithm for LDPC codes. First, sequential decoding with partial group is proposed. It has same H/W complexity, and fewer number of iteration's are required at same performance in comparison with conventional decoder algerian. Secondly, 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. Through the simulation, we knew that the iteration number are reduced by half using subset algorithm and computational complexity of early detected method is about $50\%$ offs in case of check node update, $99\%$ offs in case of check node update compared to conventional scheme.