• Title/Summary/Keyword: 반복 알고리즘

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Efficient stop criterion algorithm of the turbo code using the maximum sign change of the LLR (LLR 최대부호변화를 적용한 터보부호의 효율적인 반복중단 알고리즘)

  • Shim Byoung-Sup;Jeong Dae-Ho;Lim Soon-Ja;Kim Tae-Hyung;Kim Hwan-Yong
    • Journal of the Institute of Electronics Engineers of Korea TC
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    • v.43 no.5 s.347
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    • pp.121-127
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    • 2006
  • It is well known the fact that turbo codes has better performance as the number of iteration and the interleaver size increases in the AWGN channel environment. However, as the number of iteration and the interleaver size are increased, it is required much delay and computation for iterative decoding. Therefore, it is important to devise an efficient criterion to stop the iteration process and prevent unnecessary computations and decoding delay. In this paper, it proposes the efficient stop criterion algorithm for turbo codes using the maximum sign change of LLR. It is verifying that the proposal variable iterative decoding controller can be reduced the average iterative decoding number compared to conventional schemes with a negligible degradation of the error performance.

New stop criterion using the absolute mean value of LLR difference for Turbo Codes (LLR 차의 절대 평균값을 이용한 터보부호의 새로운 반복중단 알고리즘)

  • Shim ByoungSup;Lee Wanbum;Jeong DaeHo;Lim SoonJa;Kim TaeHyung;Kim HwanYong
    • Journal of the Institute of Electronics Engineers of Korea TC
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    • v.42 no.5 s.335
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    • pp.39-46
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    • 2005
  • It is well known the fact that turbo codes has better performance as the number of iteration and the interleaver size increases in the AWGN channel environment. However, as the number of iteration and the interleaver size are increased, it is required much delay and computation for iterative decoding. Therefore, it is important to devise an efficient criterion to stop the iteration process and prevent unnecessary computations and decoding delay. In this paper, it proposes the efficient iterative decoding stop criterion using the absolute mean value of LLR difference. It is verifying that the proposal iterative decoding stop criterion can be reduced the average iterative decoding number compared to conventional schemes with a negligible degradation of the error performance.

Iterative Algorithms for Interference Alignment in Cellular Network (셀룰러 네트워크상의 간섭정렬을 위한 반복 알고리즘)

  • Yeo, Jeong Ho;Cho, Joon Ho
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.37B no.10
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    • pp.947-955
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    • 2012
  • In this paper, we propose iterative algorithms to obtain the transmit and the receive vectors for interference alignment in cellular network. Although the conventional interference alignment algorithms for interference channels can be applied to cellular network, the number of iterations required to achieve a high sum rate is very large. The key idea in the proposed algorithms is to ignore intra-cell interference in updating the transmit vector for uplink and the receive vector for downlink. Numerical results show that the proposed algorithms achieve higher sum rates than the conventional algorithms for given iteration numbers when multiple antennas and a single carrier are used for interference alignment. It is also shown that the proposed algorithms outperform the conventional algorithms when a single antenna and multiple subcarriers are used for interference alignment.

An Efficient Iterative Decoding Stop Criterion Algorithm for Reducing Computation of Turbo Code (터보부호의 계산량 감소를 위한 효율적인 반복중단 알고리즘)

  • Jeong Dae-Ho;Lim Soon-Ja;Kim Hwan-Yong
    • Journal of the Institute of Electronics Engineers of Korea SD
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    • v.42 no.6 s.336
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    • pp.9-16
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    • 2005
  • It is well blown about the fact that turbo code has better the BER performance as the number of decoding iterations increases in the AWGN channel environment. However, as the number of decoding iterations is increased under the several channel environments, any further iteration results in very little improvement, and it requires much delay and computation in proportion to the number of decoding iterations. In this paper, it proposes the efficient iterative decoding stop criterion algorithm which can largely reduce the computation and the average number of decoding iterations of turbo code. Through simulations, it is verifying that the proposed algorithm can efficiently stop the iterative decoding by using the variance value of LLR and can largely reduce the computation and the average number of decoding iterations without BER performance degradation. As a result of simulation, the computation for the proposed algerian is reduced by about $40\%$ compared to conventional CE algorithm. The average number of decoding iterations for the proposed algorithm is reduced by about $9.94\%$ and $8.32\%$ compared to conventional HDA and SCR algorithm respectively, and by about $2.16\%{\~}7.84\%$ compared to conventional CE algorithm.

Improvement of Iterative Algorithm for Live Variable Analysis based on Computation Reordering (사용할 변수의 예측에 사용되는 반복적 알고리즘의 계산순서 재정렬을 통한 수행 속도 개선)

  • Yun Jeong-Han;Han Taisook
    • Journal of KIISE:Software and Applications
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    • v.32 no.8
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    • pp.795-807
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    • 2005
  • The classical approaches for computing Live Variable Analysis(LVA) use iterative algorithms across the entire programs based on the Data Flow Analysis framework. In case of Zephyr compiler, average execution time of LVA takes $7\%$ of the compilation time for the benchmark programs. The classical LVA algorithm has many aspects for improvement. The iterative algorithm for LVA scans useless basic blocks and calculates large sets of variables repeatedly. We propose the improvement of Iterative algorithm for LVA based on used variables' upward movement. Our algorithm produces the same result as the previous iterative algorithm. It is based on use-def chain. Reordering of applying the flow equation in DFA reduces the number of visiting basic blocks and redundant flow equation executions, which improves overall processing time. Experimental results say that our algorithm ran reduce $36.4\%\;of\;LVA\;execution\;time\;and\;2.6\%$ of overall computation time in Zephyr compiler with benchmark programs.

신경망을 이용한 하이브리드 학습 제어 알고리즘의 연구

  • 고영철;왕지남
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 1996.04a
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    • pp.71-74
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    • 1996
  • 본 연구에서는 반복 학습제어 이론을 기초로 하는 하이브리드 신경망 제어기를 제안한다. 신경망으로는 백프로퍼게이션(backpropagation) 신경망을 사용하고, 기존의 반복 학습 제어 이론의 단점을 보안한 제어 알고리즘을 제안한다. 백프로퍼게이션 신경망의 맵핑(mapping)의 특징으로 원하는 목표 패턴에 추종할 수 있는 출력 패턴을 생성하고 반복 학습에 소요되는 학습시간을 줄일 수 있다. 실험결과에서 보듯이 제안된 제어 알고리즘은 목표패턴에 수렴함을 알 수 있다. 제시한 알고리즘은 CD-ROM 드라이브와 같은 광디스크 드라이브류의 초점 제어 등에 응용할 수 있다.

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A Simple Stopping Criterion for the MIN-SUM Iterative Decoding Algorithm on SCCC and Turbo code (반복 복호의 계산량 감소를 위한 간단한 복호 중단 판정 알고리즘)

  • Heo, Jun;Chung, Kyu-Hyuk
    • Journal of the Institute of Electronics Engineers of Korea TC
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    • v.41 no.4
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    • pp.11-16
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    • 2004
  • A simple stopping criterion for iterative decoding based on min-sum processing is presented. While most stopping criteria suggested in the literature, are based on Cross Entropy (CE) and its simplification, the proposed stopping criterion is to check if a decoded sequence is a valid codeword along the encoder trellis structure. This new stopping criterion requires less computational complexity and saves mem4)ry compared to the conventional stopping rules. The numerical results are presented on the 3GPP turbo code and a Serially Concatenated Convolutional Cods (SCCC).

K-means Algorithm in outside weight region of convergence for initial iteration learning (초기 반복학습 시 수렴영역을 벗어난 가중치에 의한 K-means 알고리즘)

  • Park SoHee;Cho CheHwang
    • Proceedings of the Acoustical Society of Korea Conference
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    • autumn
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    • pp.143-146
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    • 2001
  • 본 논문에서는 랜덤초기화 방법을 사용하여 초기 코드북을 생성하고, 이를 이용하여 초기 반복학습 시 수렴영역을 벗어난 2 이상의 가중치에 의한 K-means 알고리즘을 제안한다. 기존의 K-means 알고리즘이 국부적으로 최적화되고 초기 반복학습 시에 가중치의 영향이 크다는 점을 이용하여, 제안된 방법에서는 초기 반복학습 시의 가중치를 수렴영역에서 벗어난 큰 값으로 주고 이후 반복학습시의 가증치는 수렴영역 안에 있는 값으로 고정하여 코드북을 설계한다. 또한 초기 코드북을 얻기 위해 Splitting 방법과 같은 추가적인 과정 없이 랜덤한 방법에 의한 초기 코드북을 적용함으로써 제안된 알고리즘이 단순한 구조를 가지며, 구해진 코드북의 성능도 우수함을 확인할 수 있었다.

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D2D Power Control in the Cellular System: Iterative Algorithm and Convergence (셀룰라시스템에서 D2D 전력제어: 반복적 알고리즘과 수렴)

  • Oh, Changyoon
    • Proceedings of the Korean Society of Computer Information Conference
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    • 2017.07a
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    • pp.107-108
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    • 2017
  • 본 논문에서는 셀룰라시스템의 상향링크 자원을 사용하는 D2D 단말의 전송전력 최적화문제를 반복적 알고리즘을 적용하여 해결하고자 한다. 먼저 단말별 간섭함수를 정의하고, 제안하는 반복적 알고리즘에서는 개별 D2D 단말은 정의된 단말별 간섭함수를 자신의 전송전력값으로 선택한다. 다른 D2D 단말이 전송전력값을 업데이트할 경우, 간섭함수값도 변경된다. 반복적인 전송전력값 업데이트 과정을 거친 후, 각각의 D2D 단말들의 전송전력값은 일정한 값에 수렴하게 된다. 컴퓨터실험을 통하여 제안하는 반복적 알고리즘이 수렴함을 확인한다.

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Simple Stopping Criterion Algorithm using Variance Values of Noise in Turbo Code (터보부호에서 잡음 분산값을 사용한 간단한 반복중단 알고리즘)

  • Jeong Dae-Ho;Kim Hwan-Yong
    • Journal of the Institute of Electronics Engineers of Korea TC
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    • v.43 no.3 s.345
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    • pp.103-110
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    • 2006
  • Turbo code, a kind of error correction coding technique, has been used in the field of digital mobile communication system. As the number of iterations increases, it can achieves remarkable BER performance over AWGN channel environment. However, if the number of iterations Is increases in the several channel environments, any further iteration results in very little improvement, and requires much delay and computation in proportion to the number of iterations. To solve this problems, it is necessary to device an efficient criterion to stop the iteration process and prevent unnecessary delay and computation. In this paper, it proposes an efficient and simple criterion for stopping the iteration process in turbo decoding. By using variance values of noise derived from mean values of LLR in turbo decoder, the proposed algorithm can largely reduce the computation and average number of iterations without BER performance degradation. As a result of simulations, the computation of the proposed algorithm is reduced by about $66{\sim}80%$ compared to conventional algorithm. The average number of iterations is reduced by about $13.99%{\sim}15.74%$ compared to CE algorithm and about $17.88%{\sim}18.59%$ compared to SCR algorithm.