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Journal articles on the topic 'Turbo codes'

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Published: 4 June 2021

Last updated: 25 May 2024

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1

Topalov, Vladislav, Iryna Tregubova, Mykola Severyn, and Iryna Hurklis. "Modification of chaotic interleaver for turbo codes with a change to the duffing equation and accounting for the distance spectrum of the code." Eastern-European Journal of Enterprise Technologies 6, no. 9 (126) (December 21, 2023): 32–38. http://dx.doi.org/10.15587/1729-4061.2023.292850.

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Various types of interleavers in turbo codes and their parameters affecting the efficiency of turbo codes are considered. It is noted that the type of interleaver directly affects the efficiency and error correcting of turbo codes. Also, the efficiency of turbo codes is influenced by the parameters of the minimum distance, the length of interleaver, and the distance spectrum of the code. A modification of the chaotic interleaver of turbo codes is proposed with the change of the equation to the Duffing and with examining the code's distance spectrum with the condition of increasing the code's distance between the code words with a small weight. The algorithm for modifying the chaotic interleaver with the Duffing equation and with examining the code's distance spectrum of turbo codes is presented. The characteristics of the modified chaotic interleaver with the Duffing equation and with examining the code's distance spectrum of turbo codes according to various parameters of turbo codes are given. This modification of the interleaver of turbo codes increased the minimum distance between elements for different lengths of the interleaver and polynomials of the turbo code by 10 % …33 %. Given this, there was an increase in the energy efficiency of the turbo codes by 0,05, …, 0,25 dB in comparison with a chaotic interleaver without modification at the same value of the bit error probability. When increasing the length of the modified chaotic interleaver with the Duffing equation and applying distance spectrum of the code the increasing the energy efficiency of the turbo code slows down compared to the chaotic interleaver without modification. The application scope of the modified chaotic interleaving with the Duffing equation and with examining the code's distance spectrum of turbo codes is the infocommunication channels for mobile, wired, and satellite communications

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2

Rothweller, J. "Turbo codes." IEEE Potentials 18, no. 1 (1999): 23–25. http://dx.doi.org/10.1109/45.747241.

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3

Berrou, Claude, Charlotte Langlais, and Yi Yu. "Turbo codes and turbo algorithms." Journal of Communications Software and Systems 2, no. 3 (April 5, 2017): 179. http://dx.doi.org/10.24138/jcomss.v2i3.282.

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In the first part of this paper, several basic ideas that prompted the coming of turbo codes are commented on. We then present some personal points of view on the main advances obtained in past years on turbo coding and decoding such as the circular trellis termination of recursive systematic convolutional codes and double-binary turbo codes associated with Max-Log-MAP decoding. A novel evaluation method, called genieinitialised iterative processing (GIIP), is introduced to assess the error performance of iterative processing. We show that using GIIP produces a result that can be viewed as a lower bound of the maximum likelihood iterative decoding and detection performance. Finally, two wireless communication systems are presented to illustrate recent applications of the turbo principle, the first one being multiple-input/multiple-output channel iterative detection and the second one multi-carrier modulation with linear precoding.

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4

Robertson, P., and T. Wörz. "Coded modulation scheme employing turbo codes." Electronics Letters 31, no. 18 (August 31, 1995): 1546–47. http://dx.doi.org/10.1049/el:19951064.

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5

Banerjee, A., F. Vatta, B. Scanavino, and D. J. Costello. "Nonsystematic Turbo Codes." IEEE Transactions on Communications 53, no. 11 (November 2005): 1841–49. http://dx.doi.org/10.1109/tcomm.2005.858672.

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6

Li Ping. "Turbo-SPC codes." IEEE Transactions on Communications 49, no. 5 (May 2001): 754–59. http://dx.doi.org/10.1109/26.923796.

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7

Geng, Fu Quan, Zhi Gang Huang, Xuan Jie Ning, and Mao Fan Yang. "A Joint Improved Irregular Accumulate Concatenated Tree Coding and Frequency Hopping OFDM Modulation Scheme for Wireless Networks." Advanced Materials Research 902 (February 2014): 364–69. http://dx.doi.org/10.4028/www.scientific.net/amr.902.364.

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Joint channel coding and spread spectrum modulation technologies bring to wireless networks the tremendous amount of performance improvement, the elimination, and the mitigation of interference. This paper proposes an improved design for irregular accumulate concatenated tree (IACT) codes, which can be viewed as simply precoded by an accumulator. This class of codes belongs to the special turbo-like codes, which combines the advantages of fast encoder structures of turbo codes, and the advantages of parallel high-speed belief-propagation (BP) iterative decoding algorithm of low-density parity-check (LDPC) codes. The improved IACT codes can be coded via a Tanner graph. With these improved codes, we propose a joint IACT coding and frequency hopping orthogonal frequency division multiplexing (FH-OFDM) modulation scheme for wireless networks. We compare the performance of different coding bases such as the irregular concatenated tree (ICT) codes and turbo codes in the scheme by theoretical analysis and simulation. Numerical results are shown that the proposed scheme with these IACT codes has really good performance.

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8

Isaka, Motohiko. "4. Convolutional Codes and Turbo Codes." Journal of The Institute of Image Information and Television Engineers 70, no. 7 (2016): 576–81. http://dx.doi.org/10.3169/itej.70.576.

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9

Jose Raj, M., and Dr Sharmini Enoch. "Performance analysis of highly improved hybrid turbo codes for 4G wireless networks." International Journal of Engineering & Technology 8, no. 4 (October 19, 2019): 398. http://dx.doi.org/10.14419/ijet.v8i4.20841.

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Efficient error correcting codes are essential in modern digital communication systems. Highly Improved Hybrid Turbo Code (HIHTC) is a low complex error and efficient error correcting code with excellentBit Error Rate (BER) which is comparable to Low Complexity Hybrid Turbo Codes (LCHTC), Improved Low Complexity Hybrid Turbo Codes (ILCHTC) and other Hybrid Turbo Codes. Rate 1/3 HIHTC shows a BER of 10-5 for E b/No of 1.7 dB which is closer to the E b/No of Improved Low Complexity Hybrid Turbo Codes. In this paper we analyze the performance of HIHTC in comparison with otherLow Complexity Hybrid Turbo Codes, for their performance in 4G and 5G wireless networks

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10

Et. al., Mrs Channaveeramma E. ,. "Performance Comparison of Turbo coder and low-density parity check codes." Turkish Journal of Computer and Mathematics Education (TURCOMAT) 12, no. 10 (April 28, 2021): 5898–901. http://dx.doi.org/10.17762/turcomat.v12i10.5408.

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Wireless communication systems will suffer from the noise introduced in the channels. Channel codes are the essential part of wireless communication systems which help in detection and correction of errors due to the noise introduced in the channel. Turbo codes and LDPC codes are the Forward Error Correction (FEC) channel coding techniques which have the error correcting capability near to Shannon codes along with improvement in transmission rate and energy efficiency.Turbo codes were introduced in 1993[1]. LDPC codes were discovered in 1960 by R.Galleger in his Ph.D dissertation at MIT.They became implementable, after the discovery of Turbo codes[2]. The satellite communications such as DVB-RCS, telecommunications such as 3G, 4G, Wireless metropolitan standards IEEE 802.16(WiMax) uses turbo codes[3]. G.hn/G.9960 (ITU-T standard for networking over power lines, phone lines and coaxial cable), 802.3 an(10GBps ethernet over twisted pair), CMMB(China multimedia mobile broadcasting), DVB-S2/DVB-T2/DVB-C2(Digital video broadcasting , second generation), DMB-T/H(Digital video broadcasting), Wimax(IEEE 802.16e standard for microwave communications), 802.11n-2009(wi-Fi standard) are the few standards where the LDPC codes are employed.[4]

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11

Hall, E. K., and S. G. Wilson. "Stream-oriented turbo codes." IEEE Transactions on Information Theory 47, no. 5 (July 2001): 1813–31. http://dx.doi.org/10.1109/18.930920.

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12

Iscan, Onurcan, and Wen Xu. "Window-Interleaved Turbo Codes." IEEE Communications Letters 22, no. 4 (April 2018): 676–79. http://dx.doi.org/10.1109/lcomm.2018.2794359.

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13

Bingeman, M., and A. K. Khandani. "Symbol-based turbo codes." IEEE Communications Letters 3, no. 10 (October 1999): 285–87. http://dx.doi.org/10.1109/4234.798019.

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14

Barbulescu, A. S., and S. S. Pietrobon. "Rate compatible turbo codes." Electronics Letters 31, no. 7 (March 30, 1995): 535–36. http://dx.doi.org/10.1049/el:19950406.

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15

Poulin, David, Jean-Pierre Tillich, and Harold Ollivier. "Quantum Serial Turbo Codes." IEEE Transactions on Information Theory 55, no. 6 (June 2009): 2776–98. http://dx.doi.org/10.1109/tit.2009.2018339.

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16

Jiang, F., M. R. Becker, and L. C. Perez. "Time-Varying Turbo Codes." IEEE Communications Letters 8, no. 8 (August 2004): 529–31. http://dx.doi.org/10.1109/lcomm.2004.833828.

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17

Gazi, Orhan, and A. Ylmaz. "Fast Decodable Turbo Codes." IEEE Communications Letters 11, no. 2 (February 2007): 173–75. http://dx.doi.org/10.1109/lcomm.2007.061528.

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18

Mackenzie, Dana. "Impossible inventions: Turbo codes." New Scientist 212, no. 2834 (October 2011): 42–43. http://dx.doi.org/10.1016/s0262-4079(11)62538-4.

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19

Xiao Hai-Lin, Ouyang Shan, and Xie Wu. "Quantum turbo product codes." Acta Physica Sinica 60, no. 2 (2011): 020301. http://dx.doi.org/10.7498/aps.60.020301.

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20

Aksoy, Kenan, and Ümit Aygölü. "New Punctured Turbo Codes." AEU - International Journal of Electronics and Communications 57, no. 3 (January 2003): 206–13. http://dx.doi.org/10.1078/1434-8411-54100163.

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21

Kbaier Ben Ismail, D., C. Douillard, and S. Kerouédan. "Improving irregular turbo codes." Electronics Letters 47, no. 21 (2011): 1184. http://dx.doi.org/10.1049/el.2011.2258.

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22

Ivanov, Yu Yu, B. O. Bodnarenko, Ye O. Zvuzdetskyi, and Yu S. Zditovetskyi. "Decoding Difficulty Estimation of the Convolutional Turbo-Codes and Turbo-Product Codes." Visnyk of Vinnytsia Politechnical Institute 172, no. 1 (2024): 51–55. http://dx.doi.org/10.31649/1997-9266-2024-172-1-51-55.

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23

Gazi, Orhan, and A. Ozgur Yilmaz. "Turbo Product Codes Based on Convolutional Codes." ETRI Journal 28, no. 4 (August 8, 2006): 453–60. http://dx.doi.org/10.4218/etrij.06.0105.0187.

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24

Burr, A. "Turbo-codes: the ultimate error control codes?" Electronics & Communication Engineering Journal 13, no. 4 (August 1, 2001): 155–65. http://dx.doi.org/10.1049/ecej:20010402.

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25

Yuan, Shuai, Min Dan Bai, and Hua Qing Zhang. "Adaptive Decoding for Turbo Codes over CDMA2000 Mobile System." Applied Mechanics and Materials 135-136 (October 2011): 171–78. http://dx.doi.org/10.4028/www.scientific.net/amm.135-136.171.

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As a powerful branch of error-control coding, Turbo codes have been paid a great attention since they are proposed. Due to the powerful error correcting capability, Turbo codes are very attractive for mobile wireless systems to combat channel fading. However, there are many kinds of decoding algorithms for Turbo codes, any of them have merits and demerits. In this paper, we present a new method to decode Turbo codes over cdma2000 mobile system, that is introducing a controller to achieve the purposer of adaptive decoding. And this method make the system more reliable.

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26

Beeharry, Yogesh, Tulsi P. Fowdur, and Krishnaraj M. S. Soyjaudah. "Performance of Hybrid Binary and Non-Binary Turbo Decoding Schemes for LTE and DVB-RCS Standards." ECTI Transactions on Electrical Engineering, Electronics, and Communications 17, no. 1 (September 9, 2019): 1–13. http://dx.doi.org/10.37936/ecti-eec.2019171.215363.

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Binary and Non-Binary Turbo codes have been deployed in several digital communication standards to perform error correction. In order to enhance their error performance, several schemes such as Joint Source Channel Decoding (JSCD), extrinsic information scaling mechanisms, and prioritized QAM constellation mapping have been proposed for improving the error performance of error correcting codes. In this paper, hybrid schemes comprising of JSCD, regression based extrinsic information scaling, and prioritized 16-Quadrature Amplitude Modulation (QAM) with binary and non-binary Turbo codes have been presented. Significant improvement in error performance has been observed with the proposed scheme as compared to the conventional one. The hybrid scheme in the case of binary symmetric and asymmetric LTE Turbo codes, and triple binary Turbo codes outperform the conventional scheme by 0.8 dB on average. With duo-binary Turbo codes for the DVB-RCS standard, the hybrid scheme outperforms the conventional one with an average gain of 0.9 dB in BER performance.

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27

Abdulhamid, Mohanad, and Mbugua Thairu. "Performance Analysis of Turbo Codes Over AWGN Channel." Scientific Bulletin of Electrical Engineering Faculty 19, no. 1 (April 1, 2019): 43–48. http://dx.doi.org/10.1515/sbeef-2019-0009.

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AbstractTurbo coding is a very powerful error correction technique that has made a tremendous impact on channel coding in the past two decades. It outperforms most known coding schemes by achieving near Shannon limit error correction using simple component codes and large interleavers. This paper investigates the turbo coder in detail. It presents a design and a working model of the error correction technique using Simulink, a companion softwareto MATLAB. Finally, graphical and tabular results are presented to show that the designed turbo coder works as expected.

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28

Sah, Dhaneshwar. "Iterative Decoding of Turbo Codes." Journal of Advanced College of Engineering and Management 3 (January 10, 2018): 15. http://dx.doi.org/10.3126/jacem.v3i0.18810.

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<p><strong> </strong>This paper presents a Thesis which consists of a study of turbo codes as an error-control Code and the software implementation of two different decoders, namely the Maximum a Posteriori (MAP), and soft- Output Viterbi Algorithm (SOVA) decoders. Turbo codes were introduced in 1993 by berrouet at [2] and are perhaps the most exciting and potentially important development in coding theory in recent years. They achieve near- Shannon-Limit error correction performance with relatively simple component codes and large interleavers. They can be constructed by concatenating at least two component codes in a parallel fashion, separated by an interleaver. The convolutional codes can achieve very good results. In order of a concatenated scheme such as a turbo codes to work properly, the decoding algorithm must affect an exchange of soft information between component decoders. The concept behind turbo decoding is to pass soft information from the output of one decoder to the input of the succeeding one, and to iterate this process several times to produce better decisions. Turbo codes are still in the process of standardization but future applications will include mobile communication systems, deep space communications, telemetry and multimedia. Finally, we will compare these two algorithms which have less complexity and which can produce better performance.</p><p><strong>Journal of Advanced College of Engineering and Management</strong>, Vol.3, 2017, Page: 15-30</p>

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29

Shafieipour, Mohammad, Heng-Siong Lim, and Teong-Chee Chuah. "Decoding of Turbo Codes in Symmetric Alpha-Stable Noise." ISRN Signal Processing 2011 (March 29, 2011): 1–7. http://dx.doi.org/10.5402/2011/683972.

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This paper investigates the decoding of turbo codes in impulsive symmetric α-stable (SαS) noise. Due to the nonexistence of a closed-form expression for the probability density function (pdf) of α-stable processes, numerical-based SαS pdf is used to derive branch transition probability (btp) for the maximum a posteriori turbo decoder. Results show that in Gaussian noise, the turbo decoder achieves similar performance using both the conventional and the proposed btps, but in impulsive channels, the turbo decoder with the proposed btp substantially outperforms the turbo decoder utilizing the conventional btp. Results also confirm that the turbo decoder incorporating the proposed btp outperforms the existing Cauchy-based turbo decoder in non-Cauchy impulsive noise, while the two decoders accomplish similar performance in Cauchy noise.

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30

Wamankar, Rajni, and Prof Ashish Raghuwanshi. "A Review on VLSI Aspects of Error Detection and Correction on SOCs." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 01 (January 15, 2024): 1–9. http://dx.doi.org/10.55041/ijsrem28070.

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The implementation of error detection and correction codes on system on chip (SOC) is one of the key challenges in VLSI design owing to the fact that SOCs are often limited in terms of computation power and memory. Turbo codes is a category of error detection and correction codes which have moderate complexity but exhibit a steep descent in the error floor. The name is derived from the fact that two decoders try to simultaneously decode the encoded sequence of bits synonymous with the turbo engines. This paper presents a VLSI perspective and comprehensive review on need of error detection and correction. The emphasis has been laid on the error detection and correction employing the turbo encoding mechanism. The turbo encoding mechanism has been chosen as the baseline technique as it shows adherence to the Shannon’s limit while exhibiting a steep plummet in the error rate, in the error rate even at low SNR values. The important features of the turbo encoding-decoding process has been cited with explanations. A review of the various categories of turbo codes and similar approaches has been presented. Salient features of contemporary work have been cited. Keywords: Very Large Scale Integration (VLSI), Error Detection and Correction, Trustworthiness, Turbo Codes, Shannon’s Limit.

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31

Xu, Jin, Ying Zhao, and Shu Qiang Duan. "Research and Realization by FPGA of Turbo Codes." Advanced Materials Research 588-589 (November 2012): 765–68. http://dx.doi.org/10.4028/www.scientific.net/amr.588-589.765.

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Turbo Code is a channel coding with excellent error-correcting performance in the condition of low noise-signal ratio.It has a superior decoding performance approaching the Shannon limit by adopting the random coding and decoding. This paper focuses on Turbo code and its implementation with FPGA and deeply analyzes the decoding theory and algorithm of Turbo code. Firstly, it analyzes the decoding theory of Turbo code. Then, it discusses key issues in the process of implementation with the most excellent and complicated Max—log—MAP algorithm. At last, it ends up with the Turbo encoder and decoding algorithm which hardware is successfully implemented finally.

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32

Lei, Xinyu. "The Comparison of RS Codes, LDPC Codes, And Turbo Codes." Highlights in Science, Engineering and Technology 81 (January 26, 2024): 496–504. http://dx.doi.org/10.54097/8tn0ya36.

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Error correction codes have been widely used in various fields in recent years, including the communication field, storage field, digital media field, computer network field, and so on. In this paper, the development history of error correction codes is briefly summarized; and the principles and performance of three kinds of error correction control codes are systematically summarized starting from RS codes, LDPC codes, and Turbo codes. Three types of error correction codes are compared and analyzed in the field of wireless optical communication, and the error correction characteristics of different codes in three different weather conditions are compared and summarized for the applicable environments. The error correction codes are also compared in the field of aviation flight telemetry, and which codes are suitable for uplink and downlink telemetry in flight telemetry are summarized. At the same time, the paper provides an outlook on the future development trend of error correction codes.

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33

Benedetto, S., and G. Montorsi. "Role of recursive convolutional codes in turbo codes." Electronics Letters 31, no. 11 (May 25, 1995): 858–59. http://dx.doi.org/10.1049/el:19950622.

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34

Xiao, Hailin, Ju Ni, Wu Xie, and Shan Ouyang. "A construction of quantum turbo product codes based on CSS-type quantum convolutional codes." International Journal of Quantum Information 15, no. 01 (February 2017): 1750003. http://dx.doi.org/10.1142/s0219749917500034.

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As in classical coding theory, turbo product codes (TPCs) through serially concatenated block codes can achieve approximatively Shannon capacity limit and have low decoding complexity. However, special requirements in the quantum setting severely limit the structures of turbo product codes (QTPCs). To design a good structure for QTPCs, we present a new construction of QTPCs with the interleaved serial concatenation of [Formula: see text]-type quantum convolutional codes (QCCs). First, [Formula: see text]-type QCCs are proposed by exploiting the theory of CSS-type quantum stabilizer codes and QCCs, and the description and the analysis of encoder circuit are greatly simplified in the form of Hadamard gates and C-NOT gates. Second, the interleaved coded matrix of QTPCs is derived by quantum permutation SWAP gate definition. Finally, we prove the corresponding relation on the minimum Hamming distance of QTPCs associated with classical TPCs, and describe the state diagram of encoder and decoder of QTPCs that have a highly regular structure and simple design idea.

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35

Cui, Linli, Fan Yang, and Qicong Peng. "Parallel algorithm for Turbo codes." JOURNAL OF ELECTRONIC MEASUREMENT AND INSTRUMENT 24, no. 7 (August 3, 2010): 638–42. http://dx.doi.org/10.3724/sp.j.1187.2010.00638.

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36

Gnaedig, David, Emmanuel Boutillon, Michel JÉZéquel, Vincent C. Gaudet, and P. Glenn Gulak. "On multiple slice turbo codes." Annales Des Télécommunications 60, no. 1-2 (February 2005): 79–102. http://dx.doi.org/10.1007/bf03219808.

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37

Sedy, Jakub, Pavel Silhavy, Ondrej Krajsa, and Ondrej Hrouza. "Performance Analysis of Turbo Codes." Communications - Scientific letters of the University of Zilina 15, no. 2A (July 31, 2013): 167–73. http://dx.doi.org/10.26552/com.c.2013.2a.167-173.

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38

Le Bars, P., C. Le Dantec, and P. Piret. "Bolt interleavers for turbo codes." IEEE Transactions on Information Theory 49, no. 2 (February 2003): 391–400. http://dx.doi.org/10.1109/tit.2002.807279.

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39

Schlegel, C., and A. Grant. "Differential space-time turbo codes." IEEE Transactions on Information Theory 49, no. 9 (September 2003): 2298–306. http://dx.doi.org/10.1109/tit.2003.815818.

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40

Li Ping, W. K. Leung, and K. Y. Wu. "Low-rate turbo-Hadamard codes." IEEE Transactions on Information Theory 49, no. 12 (December 2003): 3213–24. http://dx.doi.org/10.1109/tit.2003.820018.

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41

Shea, J. M. "Concatenated parity and turbo codes." Electronics Letters 37, no. 16 (2001): 1029. http://dx.doi.org/10.1049/el:20010711.

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42

Santhosh Kumar, K. B., and B. R. Sujatha. "Turbo codes for telemedicine applications." Journal of Physics: Conference Series 1706 (December 2020): 012156. http://dx.doi.org/10.1088/1742-6596/1706/1/012156.

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43

Kousa, M. A., and A. H. Mugaibel. "Puncturing effects on turbo codes." IEE Proceedings - Communications 149, no. 3 (June 1, 2002): 132–38. http://dx.doi.org/10.1049/ip-com:20020230.

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44

Wilde, Mark M., Min-Hsiu Hsieh, and Zunaira Babar. "Entanglement-Assisted Quantum Turbo Codes." IEEE Transactions on Information Theory 60, no. 2 (February 2014): 1203–22. http://dx.doi.org/10.1109/tit.2013.2292052.

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45

Moloudi, Saeedeh, Michael Lentmaier, and Alexandre Graell i Amat. "Spatially Coupled Turbo-Like Codes." IEEE Transactions on Information Theory 63, no. 10 (October 2017): 6199–215. http://dx.doi.org/10.1109/tit.2017.2735965.

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46

Chang, Y. "Parallel decoding of turbo codes." Electronics Letters 32, no. 13 (1996): 1188. http://dx.doi.org/10.1049/el:19960776.

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47

Berrou, C., and M. Jézéquel. "Frame-oriented convolutional turbo codes." Electronics Letters 32, no. 15 (1996): 1362. http://dx.doi.org/10.1049/el:19960912.

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48

Adde, P., R. Pyndiah, and C. Berrou. "Performance of hybrid turbo codes." Electronics Letters 32, no. 24 (1996): 2209. http://dx.doi.org/10.1049/el:19961453.

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49

Keying Wu and Li Ping. "Multilayer turbo space-time codes." IEEE Communications Letters 9, no. 1 (2005): 55–57. http://dx.doi.org/10.1109/lcomm.2005.01030.

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50

Dong, Quang Trung, Matthieu Arzel, Christophe Jego, and Warren J. Gross. "Stochastic Decoding of Turbo Codes." IEEE Transactions on Signal Processing 58, no. 12 (December 2010): 6421–25. http://dx.doi.org/10.1109/tsp.2010.2072924.

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