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Journal articles on the topic 'Linear block codes'

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Published: 4 June 2021
Last updated: 6 September 2023

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1

Litwin, L., and K. Ramaswamy. "Linear block codes." IEEE Potentials 20, no. 1 (2001): 29–31. http://dx.doi.org/10.1109/45.913209.

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2

Feng, Keqin, Lanju Xu, and Fred J. Hickernell. "Linear error-block codes." Finite Fields and Their Applications 12, no. 4 (November 2006): 638–52. http://dx.doi.org/10.1016/j.ffa.2005.03.006.

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3

Dubey, Pankaj, Neelesh Gupta, and Meha Shrivastva. "Non Coherent Block Coded Modulation using Linear Components Codes." International Journal of Computer Applications 91, no. 13 (April 18, 2014): 5–8. http://dx.doi.org/10.5120/15939-5097.

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4

Tolhuizen, L. "New binary linear block codes (Corresp.)." IEEE Transactions on Information Theory 33, no. 5 (September 1987): 727–29. http://dx.doi.org/10.1109/tit.1987.1057346.

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5

Caire, G., and E. Biglieri. "Linear block codes over cyclic groups." IEEE Transactions on Information Theory 41, no. 5 (1995): 1246–56. http://dx.doi.org/10.1109/18.412673.

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6

Sklar, B., and F. J. Harris. "The ABCs of linear block codes." IEEE Signal Processing Magazine 21, no. 4 (July 2004): 14–35. http://dx.doi.org/10.1109/msp.2004.1311137.

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7

Tang, Li, and Aditya Ramamoorthy. "Coded Caching Schemes With Reduced Subpacketization From Linear Block Codes." IEEE Transactions on Information Theory 64, no. 4 (April 2018): 3099–120. http://dx.doi.org/10.1109/tit.2018.2800059.

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8

Wei, Ruey-Yi, Tzu-Shiang Lin, and Shi-Shan Gu. "Noncoherent Block-Coded TAPSK and 16QAM Using Linear Component Codes." IEEE Transactions on Communications 58, no. 9 (September 2010): 2493–98. http://dx.doi.org/10.1109/tcomm.2010.09.090413.

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9

Sole, Patrick, and Virgilio Sison. "Quaternary Convolutional Codes From Linear Block Codes Over Galois Rings." IEEE Transactions on Information Theory 53, no. 6 (June 2007): 2267–70. http://dx.doi.org/10.1109/tit.2007.896884.

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10

Micheli, Giacomo, and Alessandro Neri. "New Lower Bounds for Permutation Codes Using Linear Block Codes." IEEE Transactions on Information Theory 66, no. 7 (July 2020): 4019–25. http://dx.doi.org/10.1109/tit.2019.2957354.

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11

Niharmine, Lahcen, Hicham Bouzkraoui, Ahmed Azouaoui, and Youssef Hadi. "Simulated Annealing Decoder for Linear Block Codes." Journal of Computer Science 14, no. 8 (August 1, 2018): 1174–89. http://dx.doi.org/10.3844/jcssp.2018.1174.1189.

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12

Agrell, E. "Voronoi regions for binary linear block codes." IEEE Transactions on Information Theory 42, no. 1 (1996): 310–16. http://dx.doi.org/10.1109/18.481810.

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13

Said, A., and R. Palazzo. "New ternary and quaternary linear block codes." IEEE Transactions on Information Theory 42, no. 5 (1996): 1625–28. http://dx.doi.org/10.1109/18.532912.

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14

Kiely, A. B., S. J. Dolinar, R. J. McEliece, L. L. Ekroot, and Wei Lin. "Trellis decoding complexity of linear block codes." IEEE Transactions on Information Theory 42, no. 6 (1996): 1687–97. http://dx.doi.org/10.1109/18.556665.

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15

Laendner, Stefan, Thorsten Hehn, Olgica Milenkovic, and Johannes B. Huber. "The Trapping Redundancy of Linear Block Codes." IEEE Transactions on Information Theory 55, no. 1 (January 2009): 53–63. http://dx.doi.org/10.1109/tit.2008.2008134.

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16

Dumachev, V. N., A. N. Kopylov, and V. V. Butov. "Neural Net Decoders for Linear Block Codes." Bulletin of the South Ural State University. Series "Mathematical Modelling, Programming and Computer Software" 12, no. 1 (2019): 129–36. http://dx.doi.org/10.14529/mmp190111.

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17

WU, JA-LING, YUEN-HSIEN TSENG, and YUH-MING HUANG. "NEURAL NETWORK DECODERS FOR LINEAR BLOCK CODES." International Journal of Computational Engineering Science 03, no. 03 (September 2002): 235–55. http://dx.doi.org/10.1142/s1465876302000629.

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18

Dong, Xue-dong, Cheong Boon Soh, and Erry Gunawan. "Linear Block Codes for Four-Dimensional Signals." Finite Fields and Their Applications 5, no. 1 (January 1999): 57–75. http://dx.doi.org/10.1006/ffta.1998.0235.

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19

Khebbou, Driss, Reda Benkhouya, Idriss Chana, and Hussain Ben-Azza. "SIMPLIFIED SUCCESSIVE-CANCELLATION LIST POLAR DECODING FOR BINARY LINEAR BLOCK CODES." Journal of Southwest Jiaotong University 56, no. 6 (December 24, 2021): 616–26. http://dx.doi.org/10.35741/issn.0258-2724.56.6.54.

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This paper aims to take advantage of the performances of polar decoding techniques for the benefit of binary linear block codes (BLBCs) with the main objective is to study the performances of the SSCL decoding for short-length BLBCs. Polar codes are one of the most recent error-correcting codes to be invented, and they have been mathematically demonstrated to be able to correct all errors under a specific situation, using the successive-cancellation decoder. However, their performances for real-time wireless communications at short block lengths remain less attractive. To take advantage of the performance of these codes in favor of error correction codes of short block length, an adaptation of the simplified successive-cancellation list as a decoder for polar codes for the benefit of short block length binary linear block codes is presented in this paper. This adaptation makes it possible to take advantage of the performances of less complex decoding methods for polar codes for BLBCs with latency and complexity optimization of the standard successive-cancellation list decoder. The experiment shows that the method can achieve the performances of the most famous order statistic decoder for binary linear block codes, which can achieve the performances of maximum-likelihood decoding with computational complexity and memory constraints.
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20

Khebbou, Driss, Idriss Chana, and Hussain Ben-Azza. "Single parity check node adapted to polar codes with dynamic frozen bit equivalent to binary linear block codes." Indonesian Journal of Electrical Engineering and Computer Science 29, no. 2 (February 1, 2023): 816. http://dx.doi.org/10.11591/ijeecs.v29.i2.pp816-824.

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<span lang="EN-US">In the context of decoding binary linear block codes by polar code decoding techniques, we propose in this paper a new optimization of the serial nature of decoding the polar codes equivalent to binary linear block codes. In addition to the special nodes proposed by the simplified successive-cancellation list technique, we propose a new special node allowing to estimate in parallel the bits of its sub-code. The simulation is done in an additive white gaussian noise channel (AWGN) channel for several linear block codes, namely bose–chaudhuri–hocquenghem codes (BCH) codes, quadratic-residue (QR) codes, and linear block codes recently designed in the literature. The performance of the proposed technique offers the same performance in terms of frame error rate (FER) as the ordered statistics decoding (OSD) algorithm, which achieves that of maximum likelihood decoder (MLD), but with high memory requirements and computational complexity.</span>
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21

Yang, Kai, Xiaodong Wang, and Jon Feldman. "A New Linear Programming Approach to Decoding Linear Block Codes." IEEE Transactions on Information Theory 54, no. 3 (March 2008): 1061–72. http://dx.doi.org/10.1109/tit.2007.915712.

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22

Brown, Gavin, and Alexander M. Kasprzyk. "Seven new champion linear codes." LMS Journal of Computation and Mathematics 16 (2013): 109–17. http://dx.doi.org/10.1112/s1461157013000041.

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AbstractWe exhibit seven linear codes exceeding the current best known minimum distance $d$ for their dimension $k$ and block length $n$. Each code is defined over ${ \mathbb{F} }_{8} $, and their invariants $[n, k, d] $ are given by $[49, 13, 27] $, $[49, 14, 26] $, $[49, 16, 24] $, $[49, 17, 23] $, $[49, 19, 21] $, $[49, 25, 16] $ and $[49, 26, 15] $. Our method includes an exhaustive search of all monomial evaluation codes generated by points in the $[0, 5] \times [0, 5] $ lattice square.
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23

Berger, Y., and Y. Be'ery. "Soft trellis-based decoder for linear block codes." IEEE Transactions on Information Theory 40, no. 3 (May 1994): 764–73. http://dx.doi.org/10.1109/18.335888.

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24

Kiely, A. B., J. T. Coffey, and M. R. Bell. "Optimal information bit decoding of linear block codes." IEEE Transactions on Information Theory 41, no. 1 (1995): 130–40. http://dx.doi.org/10.1109/18.370113.

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25

McEliece, R. J. "On the BCJR trellis for linear block codes." IEEE Transactions on Information Theory 42, no. 4 (July 1996): 1072–92. http://dx.doi.org/10.1109/18.508834.

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26

Fossorier, M. P. C., Shu Lin, and J. Snyders. "Reliability-based syndrome decoding of linear block codes." IEEE Transactions on Information Theory 44, no. 1 (1998): 388–98. http://dx.doi.org/10.1109/18.651070.

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27

Dariti, Rabiî, and El Mamoun Souidi. "New families of perfect linear error-block codes." International Journal of Information and Coding Theory 2, no. 2/3 (2013): 84. http://dx.doi.org/10.1504/ijicot.2013.059702.

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28

Honary, B. "Low-complexity trellis decoding of linear block codes." IEE Proceedings - Communications 142, no. 4 (1995): 201. http://dx.doi.org/10.1049/ip-com:19952037.

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29

Manoukian, H. H., and B. Honary. "BCJR trellis construction for binary linear block codes." IEE Proceedings - Communications 144, no. 6 (1997): 367. http://dx.doi.org/10.1049/ip-com:19971611.

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30

Sweeney, P., and S. Wesemeyer. "Iterative soft-decision decoding of linear block codes." IEE Proceedings - Communications 147, no. 3 (2000): 133. http://dx.doi.org/10.1049/ip-com:20000300.

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31

Rocha Junior, V. C., and P. G. Farrell. "Algebraic Soft-Decision Techniques for Linear Block Codes." Journal of Communication and Information Systems 5, no. 1 (June 30, 1990): 59–72. http://dx.doi.org/10.14209/jcis.1990.4.

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32

Esmaeili, M., A. Alampour, and T. A. Gulliver. "Decoding Binary Linear Block Codes Using Local Search." IEEE Transactions on Communications 61, no. 6 (June 2013): 2138–45. http://dx.doi.org/10.1109/tcomm.2013.041113.120057.

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33

Ling, San, and Ferruh Özbudak. "Constructions and bounds on linear error-block codes." Designs, Codes and Cryptography 45, no. 3 (September 1, 2007): 297–316. http://dx.doi.org/10.1007/s10623-007-9119-9.

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34

Song, Young Joon. "Hybrid Maximum Likelihood Decoding for Linear Block Codes." International Journal of Multimedia and Ubiquitous Engineering 9, no. 10 (October 31, 2014): 91–100. http://dx.doi.org/10.14257/ijmue.2014.9.10.09.

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35

Altay, Gökmen, and Osman N. Ucan. "Heuristic construction of high-rate linear block codes." AEU - International Journal of Electronics and Communications 60, no. 9 (October 2006): 663–66. http://dx.doi.org/10.1016/j.aeue.2005.12.004.

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36

Wolf, J. K., and A. J. Viterbi. "On the weight distribution of linear block codes formed from convolutional codes." IEEE Transactions on Communications 44, no. 9 (1996): 1049–51. http://dx.doi.org/10.1109/26.536907.

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37

Lin, Chien-Ying, Yu-Chih Huang, Shin-Lin Shieh, and Po-Ning Chen. "Transformation of Binary Linear Block Codes to Polar Codes With Dynamic Frozen." IEEE Open Journal of the Communications Society 1 (2020): 333–41. http://dx.doi.org/10.1109/ojcoms.2020.2979529.

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38

Scholl, S., E. Leonardi, and N. Wehn. "FPGA implementation of trellis decoders for linear block codes." Advances in Radio Science 12 (November 10, 2014): 61–67. http://dx.doi.org/10.5194/ars-12-61-2014.

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Abstract. Forward error correction based on trellises has been widely adopted for convolutional codes. Because of their efficiency, they have also gained a lot of interest from a theoretic and algorithm point of view for the decoding of block codes. In this paper we present for the first time hardware architectures and implementations for trellis decoding of block codes. A key feature is the use of a sophisticated permutation network, the Banyan network, to implement the time varying structure of the trellis. We have implemented the Viterbi and the max-log-MAP algorithm in different folded versions on a Xilinx Virtex 6 FPGA.
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39

Aghaei, Amirhossein, Konstantinos Plataniotis, and Subbarayan Pasupathy. "Widely linear MMSE receivers for linear dispersion space-time block-codes." IEEE Transactions on Wireless Communications 9, no. 1 (January 2010): 8–13. http://dx.doi.org/10.1109/twc.2010.01.080897.

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40

Башкиров, А. В., И. В. Свиридова, М. В. Хорошайлова, and О. В. Свиридова. "STOCHASTIC DECODING OF LINEAR BLOCK CODES USING CHECK MATRIX." ВЕСТНИК ВОРОНЕЖСКОГО ГОСУДАРСТВЕННОГО ТЕХНИЧЕСКОГО УНИВЕРСИТЕТА, no. 6 (January 10, 2021): 79–84. http://dx.doi.org/10.36622/vstu.2020.16.6.011.

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Для итеративного декодирования на графах используется новый альтернативный подход - это стохастическое декодирование. Возможность стохастического декодирования была недавно предложена для декодирования LDPC-кодов. Эта статья расширяет применение стохастического подхода для декодирования линейных блочных кодов с помощью проверочных матриц (PCM), таких как коды Боуза - Чоудхури - Хоквингема (BCH), коды Рида - Соломона (RS) и блочные турбокоды на основе компонентов кодов BCH. Показано, как стохастический подход способен генерировать информацию мягкого выхода для итеративного декодирования с мягким входом и мягким выходом Soft - Input Soft - Output (SISO). Описывается структура стохастических переменных узлов высокой степени, используемых в кодах с помощью проверочных матриц PCM. Результаты моделирования для кода BCH (128, 120), кода RS (31, 25) и RS (63, 55) и турбокода блока BCH (256, 121) и (1024, 676) демонстрируют эффективность декодирования при закрытии к итеративному декодеру SISO с реализацией с плавающей запятой. Эти результаты показывают производительность декодирования, близкую к адаптивному алгоритму распространения доверия и/или турбо-ориентированному адаптированному алгоритму распространения доверия Stochastic decoding capability has recently been proposed for decoding LDPC codes. This paper expands on the application of the stochastic approach to decoding linear block codes using parity check matrices (PCMs) such as Bose-Chowdhury-Hawkingham (BCH) codes, Reed-Solomon (RS) codes, and BCH component-based block turbo codes. We show how the stochastic approach is able to generate soft-output information for iterative decoding with soft-input and soft-output Soft-Input Soft-Output (SISO). We describe the structure of high degree stochastic node variables used in codes using PCM parity check matrices. Simulation results for BCH code (128, 120), RS code (31, 25) and RS (63, 55), and BCH block turbo code (256, 121) and (1024, 676) demonstrate the decoding efficiency on close to SISO iterative decoder with floating point implementation. These results show decoding performance close to the adaptive trust propagation algorithm and / or turbo-oriented adapted trust propagation algorithm
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41

Anu Kathuria. "On traceable results of linear error correcting codes and resolvable BIBDS." International Journal of Science and Research Archive 2, no. 2 (May 30, 2021): 274–79. http://dx.doi.org/10.30574/ijsra.2021.2.2.0408.

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In this paper we relate how Equidistant Constant Weight Codes and Different Combinatorial Structures like Resolvable Balanced Incomplete Block Designs (RBIBD) , Nested Balanced Incomplete Block Designs (NBIBD) and Linear Codes are related with each other and then show how these Combinatorial Structures can be used as 2-Traceable (TA) Code.
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42

Dong, Xue Dong. "Linear Block Codes for Six-Dimensional Signals over Finite Fields." Applied Mechanics and Materials 385-386 (August 2013): 1358–61. http://dx.doi.org/10.4028/www.scientific.net/amm.385-386.1358.

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t is known that the performance of a signal constellation used to transmit digital information over the additive white Gaussian noise channel can be improved by increasing the dimensionality of the signal set used for transmission. This paper derives an algorithm for constructing codes for six-dimensional signals over finite fields of the algebraic integer ring of the cyclotomic field modulo irreducible elements with the norm , where is a prime number and or .These linear codes can correct some types of errors and provide an algebraic approach in an area which is currently mainly dominated by nonalgebraic convolutional codes.
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43

Lucas, R., M. Bossert, and M. Breitbach. "On iterative soft-decision decoding of linear binary block codes and product codes." IEEE Journal on Selected Areas in Communications 16, no. 2 (1998): 276–96. http://dx.doi.org/10.1109/49.661116.

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44

Ogasahara, Naonori, Manabu Kobayashi, and Shigeichi Hirasawa. "The construction of periodically time-variant convolutional codes using binary linear block codes." Electronics and Communications in Japan (Part III: Fundamental Electronic Science) 90, no. 9 (2007): 31–40. http://dx.doi.org/10.1002/ecjc.20271.

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45

MUNTEANU, V., D. TARNICERIU, and G. ZAHARIA. "Analysis of Linear Block Codes as Sources with Memory." Advances in Electrical and Computer Engineering 10, no. 4 (2010): 77–80. http://dx.doi.org/10.4316/aece.2010.04012.

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46

Elengical, S. M., F. Takawira, and H. Xu. "Reduced complexity maximum likelihood decoding of linear block codes." SAIEE Africa Research Journal 97, no. 2 (June 2006): 136–39. http://dx.doi.org/10.23919/saiee.2006.9488001.

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47

Khmelkov, A. N. "Optimal Syndrome Decoding of Cyclic Linear Block-Structured Codes." Telecommunications and Radio Engineering 69, no. 2 (2010): 169–79. http://dx.doi.org/10.1615/telecomradeng.v69.i2.80.

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48

Drolet, G. "Improvement of iterative decoding algorithm for linear block codes." Electronics Letters 38, no. 23 (2002): 1454. http://dx.doi.org/10.1049/el:20020981.

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49

Berger, Y., and Y. Be'ery. "Bounds on the trellis size of linear block codes." IEEE Transactions on Information Theory 39, no. 1 (1993): 203–9. http://dx.doi.org/10.1109/18.179359.

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50

Kasami, T., T. Takata, T. Fujiwara, and S. Lin. "On complexity of trellis structure of linear block codes." IEEE Transactions on Information Theory 39, no. 3 (May 1993): 1057–64. http://dx.doi.org/10.1109/18.256515.

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