Relevant bibliographies by topics / Turbo codes

Academic literature on the topic 'Turbo codes'

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Published: 4 June 2021
Last updated: 25 May 2024

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Journal articles on the topic "Turbo codes"

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

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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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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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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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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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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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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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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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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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Dissertations / Theses on the topic "Turbo codes"

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Fournier, Stéphan. "Turbo codes." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1997. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp04/mq22763.pdf.

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Yan, Yun. "Turbo codes." Ohio : Ohio University, 1999. http://www.ohiolink.edu/etd/view.cgi?ohiou1175200238.

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Abbara, Mamdouh. "Turbo-codes quantiques." Phd thesis, Ecole Polytechnique X, 2013. http://pastel.archives-ouvertes.fr/pastel-00842327.

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L'idée des turbo-codes, construction très performante permettant l'encodage de l'information classique, ne pouvait jusqu'à présent pas être transposé au problème de l'encodage de l'information quantique. En effet, il subsistait des obstacles tout aussi théoriques que relevant de leur implémentation. A la version quantique connue de ces codes, on ne connaissait ni de résultat établissant une distance minimale infinie, propriété qui autorise de corriger un nombre arbitraire d'erreurs, ni de décodage itératif efficace, car les turbo-encodages quantiques, dits catastrophiques, propagent certaines erreurs lors d'un tel décodage et empêchent son bon fonctionnement. Cette thèse a permis de relever ces deux défis, en établissant des conditions théoriques pour qu'un turbo-code quantique ait une distance minimale infinie, et d'autre part, en exhibant une construction permettant au décodage itératif de bien fonctionner. Les simulations montrent alors que la classe de turbo-codes quantiques conçue est efficace pour transmettre de l'information quantique via un canal dépolarisant dont l'intensité de dépolarisation peut aller jusqu'à p = 0,145. Ces codes quantiques, de rendement constant, peuvent aussi bien être utilisés directement pour encoder de l'information quantique binaire, qu'être intégrés comme modules afin d'améliorer le fonctionnement d'autres codes tels que les LDPC quantiques.
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Xia, Bo. "Importance sampling for LDPC codes and turbo-coded CDMA." Diss., The University of Arizona, 2004. http://hdl.handle.net/10150/290093.

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Low-density parity-check (LDPC) codes have shown capacity-approaching performance with soft iterative decoding algorithms. Simulating LDPC codes at very low error rates normally takes an unacceptably long time. We consider importance sampling (IS) schemes for the error rate estimation of LDPC codes, with the goal of dramatically reducing the necessary simulation time. In IS simulations, the sample distribution is biased to emphasize the occurrence of error events and efficiency can be achieved with properly biased sample distributions. For LDPC codes, we propose an IS scheme that overcomes a difficulty in traditional IS designs that require codebook information. This scheme is capable of estimating both codeword and bit error rates. As an example, IS gains on the order of 105 are observed at a bit error rate (BER) of 10-15 for a (96, 48) code. We also present an importance sampling scheme for the decoding of loop-free multiple-layer trees. This scheme is asymptotically efficient in that, for an arbitrary tree and a given estimation precision, the required number of simulations is inversely proportional to the noise standard deviation. The motivation of this study is to shed light on an asymptotically efficient IS design for LDPC code simulations. For an example depth-3 regular tree, we show that only 2400 simulation runs are needed to achieve a 10% estimation precision at a BER of 10-75. Similar promising results are also shown for a length-9 rate-1/3 regular code after being converted to a decoding tree. Finally, we consider a convolutionally coded CDMA system with iterative multiuser detection and decoding. In contrast to previous work in this area, a differential encoder is inserted to effect an interleaver gain. We view the CDMA channel as a periodically time-varying ISI channel. The receiver jointly decodes the differential encoders and the CDMA channel with a combined trellis, and shares soft output information with the convolutional decoders in an iterative (turbo) fashion. Dramatic gains over conventional convolutionally coded systems are demonstrated via simulation. We also show that there exists an optimal code rate under a bandwidth constraint. The performance and optimal code rates are also demonstrated via density evolution analysis.
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Sauvé, Pierre-Paul. "Multibit decoding of turbo codes." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1998. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape10/PQDD_0004/MQ40947.pdf.

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SILVA, AMANDA CUNHA. "PERFORMANCE ANALYSIS OF TURBO CODES." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2006. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=9445@1.

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CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO
Códigos turbo são uma técnica de correção de erro eficiente que vem sendo proposta em diversos padrões de comunicações atuais. Esta técnica apresenta um desempenho que se aproxima dos limites teóricos estabelecidos na Teoria de Codificação. A razão para o excelente desempenho deste tipo de código baseia-se em dois fatores: uma estrutura de codificação composta por codificadores concatenados e uma estrutura de decodificação iterativa. Neste trabalho é realizada uma revisão da literatura onde a decodificação turbo é discutida segundo duas abordagens: uma que baseia-se na estrutura dos codificadores empregados e outra baseada na moderna teoria de grafos- fatores. O desempenho destes códigos é avaliado através de simulações. São considerados fatores como a estrutura dos codificadores, o tipo de modulação empregada, o algoritmo de decodificação utilizado, entre outros.
Turbo codes are an efficient error correcting technique that has been proposed for many communications standards. This technique achieves a performance that is near the theoretical limits established by Information Theory. The reason for this excellent performance of turbo codes relies on two aspects: a coding structure that is composed by concatenated encoders and an iterative decoding procedure. In the literature, two approaches for turbo decoding are presented: one that is based on the encoder structure and another that is built around the factor graphs theory. Both approaches are discussed in this work. Performance evaluation for these codes are obtained through simulations. Some aspects such as encoder structure, modulation scheme and decoding algorithm are considered and evaluated. Also codes derived from turbo codes by puncturing and shortening have been studied in this work.
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Podemski, Robert. "Analyse spectrale des turbo codes." Rennes 1, 1998. http://www.theses.fr/1998REN10150.

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Cette these est dediee aux proprietes spectrales des turbo-codes. Un nouvel algorithme de calcul du spectre des distances de hamming, appele algorithme de la fenetre coulissante, est propose. Cet algorithme est base sur l'algorithme de fano et utilise le concept de suite de retour a zero introduit dans cette these. L'algorithme de la fenetre coulissante tire avantage des proprietes des turbo-codes et, de ce fait, presente une complexite bien inferieure a celle de l'algorithme de fano, permettant ainsi le calcul du spectre des distances pour des turbo-codes utilisant un entrelacement pouvant atteindre 4. 000 bits. La seconde partie de la these donne les regles de construction de turbo-codes, presentant de bons spectres de distance. Les differents criteres que doivent remplir les elements constitutifs du turbo-codeur i. E. Les codes recursifs systematiques, l'entrelacement et le masque de poinconnage de facon a obtenir de bonnes performances sont alors donnes. Les resultats analytique sont verifies par la simulation, aussi bien dans le cas du decodage optimal que non-optimal (iteratif).
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Kim, Han Jo. "Improving turbo codes through code design and hybrid ARQ." [Gainesville, Fla.] : University of Florida, 2005. http://purl.fcla.edu/fcla/etd/UFE0012169.

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Martin, Philippa Anne. "Adaptive iterative decoding : block turbo codes and multilevel codes." Thesis, University of Canterbury. Electrical and Electronic Engineering, 2001. http://hdl.handle.net/10092/7853.

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New adaptive, iterative approaches to the decoding of block Turbo codes and multilevel codes are developed. Block Turbo codes are considered as they can readily provide high data rates, low decoding complexity and good performance. Multilevel codes are considered as they provide a moderate complexity approach to a high complexity code and can provide codes with good bandwidth efficiency. The work develops two adaptive sub-optimal soft output decoding algorithms for block Turbo codes. One is based on approximation and the other on the distance properties of the component codes. They can be used with different codes, modulation schemes, channel conditions and in different applications without modification. Both approaches provide improved performance compared to previous approaches on the additive white Gaussian noise (AWGN) channel. The approximation based adaptive algorithm is also investigated on the uncorrelated Rayleigh fiat fading channel and is shown to improve performance over previous approaches. Multilevel codes are typically decoded using a multistage decoder (MSD) for complexity reasons. Each level passes hard decisions to subsequent levels. If the approximation based adaptive algorithm is used to decode component codes in a traditional MSD it improves performance significantly. Performance can be improved further by passing reliability (extrinsic) information to all previous and subsequent levels using an iterative MSD. A new iterative multistage decoding algorithm for multilevel codes is developed by treating the extrinsic information as a Gaussian random variable. If the adaptive algorithms are used in conjunction with iterative multistage decoding on the AWGN channel, then a significant improvement in performance is obtained compared to results using a traditional MSD.
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Tixier, Audrey. "Reconnaissance de codes correcteurs." Electronic Thesis or Diss., Paris 6, 2015. http://www.theses.fr/2015PA066554.

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Dans cette thèse, nous nous intéressons au problème de la reconnaissance de code. Ce problème se produit principalement lorsqu'une communication est observée dans un milieu non-coopératif. Une liste de mots bruités issus d'un code inconnu est obtenue, l'objectif est alors de retrouver l'information contenue dans ces mots bruités. Pour cela, le code utilisé est reconstruit afin de décoder les mots observés. Nous considérons ici trois instances de ce problème et proposons pour chacune d'elle une nouvelle méthode. Dans la première, nous supposons que le code utilisé est un turbo-code et nous proposons une méthode pour reconstruire la permutation interne (les autres éléments du turbo-codeur pouvant être facilement reconstruits grâce aux méthodes existantes). Cette permutation est reconstruite pas à pas en recherchant l'indice le plus probable à chaque instant. Plus précisément, la probabilité de chaque indice est déterminée avec l'aide de l'algorithme de décodage BCJR. Dans la seconde, nous traitons le problème de la reconnaissance des codes LDPC en suggérant une nouvelle méthode pour retrouver une liste d'équations de parité de petits poids. Celle-ci généralise et améliore les méthodes existantes. Finalement, avec la dernière méthode, nous reconstruisons un code convolutif entrelacé. Cette méthode fait appel à la précédente pour retrouver une liste d'équations de parité satisfaites par le code entrelacé. Puis, en introduisant une représentation sous forme de graphe de l'intersection de ces équations de parité, nous retrouvons simultanément l'entrelaceur et le code convolutif
In this PhD, we focus on the code reconstruction problem. This problem mainly arises in a non-cooperative context when a communication consisting of noisy codewords stemming from an unknown code is observed and its content has to be retrieved by recovering the code that is used for communicating and decoding with it the noisy codewords. We consider here three possible scenarios and suggest an original method for each case. In the first one, we assume that the code that is used is a turbo-code and we propose a method for reconstructing the associated interleaver (the other components of the turbo-code can be easily recovered by the existing methods). The interleaver is reconstructed step by step by searching for the most probable index at each time and by computing the relevant probabilities with the help of the BCJR decoding algorithm. In the second one, we tackle the problem of reconstructing LDPC codes by suggesting a new method for finding a list of parity-check equations of small weight that generalizes and improves upon all existing methods. Finally, in the last scenario we reconstruct an unknown interleaved convolutional code. In this method we used the previous one to find a list of parity-check equations for this code. Then, by introducing a graph representing how these parity-check equations intersect we recover at the same time the interleaver and the convolutional code
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Books on the topic "Turbo codes"

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Giulietti, Alexandre, Bruno Bougard, and Liesbet Van der Perre. Turbo Codes. Boston, MA: Springer US, 2004. http://dx.doi.org/10.1007/978-1-4615-0477-1.

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Vucetic, Branka, and Jinhong Yuan. Turbo Codes. Boston, MA: Springer US, 2000. http://dx.doi.org/10.1007/978-1-4615-4469-2.

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Berrou, Claude, ed. Codes and Turbo Codes. Paris: Springer Paris, 2010. http://dx.doi.org/10.1007/978-2-8178-0039-4.

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Berrou, Claude. Codes and Turbo Codes. Paris: Springer-Verlag Paris, 2010.

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Abbasfar, Aliazam. Turbo-like Codes. Dordrecht: Springer Netherlands, 2007. http://dx.doi.org/10.1007/978-1-4020-6391-6.

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Giulietti, Alexandre. Turbo codes: Desirable and designable. Boston, MA: Kluwer Academic Publishers, 2004.

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Vucetic, Branka. Turbo codes: Principles and applications. Boston: Kluwer Academic Publishers, 2000.

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Vucetic, Branka. Turbo Codes: Principles and Applications. Boston, MA: Springer US, 2000.

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Sauve, Pierre-Paul. Multibit decoding of turbo codes. Ottawa: National Library of Canada, 1998.

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Giulietti, Alexandre. Turbo Codes: Desirable and Designable. Boston, MA: Springer US, 2004.

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Book chapters on the topic "Turbo codes"

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Rao, K. Deergha. "Turbo Codes." In Channel Coding Techniques for Wireless Communications, 181–231. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-15-0561-4_6.

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Kienle, Frank. "Turbo Codes." In Architectures for Baseband Signal Processing, 117–45. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4614-8030-3_6.

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Giulietti, Alexandre, Bruno Bougard, and Liesbet Van der Perre. "Turbo Codes." In Turbo Codes, 1–28. Boston, MA: Springer US, 2004. http://dx.doi.org/10.1007/978-1-4615-0477-1_1.

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Xu, Jun, Jin Xu, and Yifei Yuan. "Turbo Codes." In Channel Coding in 5G New Radio, 225–54. Boca Raton: CRC Press, 2022. http://dx.doi.org/10.1201/9781003336174-5.

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Cancellieri, Giovanni. "Turbo Codes." In Polynomial Theory of Error Correcting Codes, 473–502. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-01727-3_9.

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Deergha Rao, K. "Turbo Codes." In Channel Coding Techniques for Wireless Communications, 161–207. New Delhi: Springer India, 2015. http://dx.doi.org/10.1007/978-81-322-2292-7_6.

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Heegard, Chris, and Stephen B. Wicker. "Concatenated Codes." In Turbo Coding, 65–88. Boston, MA: Springer US, 1999. http://dx.doi.org/10.1007/978-1-4757-2999-3_4.

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Vucetic, Branka, and Jinhong Yuan. "Block Codes." In Turbo Codes, 13–36. Boston, MA: Springer US, 2000. http://dx.doi.org/10.1007/978-1-4615-4469-2_2.

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Vucetic, Branka, and Jinhong Yuan. "Convolutional Codes." In Turbo Codes, 37–72. Boston, MA: Springer US, 2000. http://dx.doi.org/10.1007/978-1-4615-4469-2_3.

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Vucetic, Branka, and Jinhong Yuan. "Introduction." In Turbo Codes, 1–12. Boston, MA: Springer US, 2000. http://dx.doi.org/10.1007/978-1-4615-4469-2_1.

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Conference papers on the topic "Turbo codes"

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Pyndiah, R. "Block turbo codes: ten years later." In IEE Seminar on Sparse-Graph Codes (Turbo Codes, Low Density Parity-Check Codes and Fountain Codes). IEE, 2004. http://dx.doi.org/10.1049/ic:20040505.

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Ng, S. X. "Integrated wireless multimedia turbo-transceiver design approaching the Rayleigh channel's capacity: interpreting Shannon's lessons in the turbo-era." In IEE Seminar on Sparse-Graph Codes (Turbo Codes, Low Density Parity-Check Codes and Fountain Codes). IEE, 2004. http://dx.doi.org/10.1049/ic:20040507.

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Huebner, A., M. Lentmaier, K. Sh Zigangirov, and D. J. Costello. "Laminated turbo codes." In 2005 IEEE International Symposium on Information Theory (ISIT). IEEE, 2005. http://dx.doi.org/10.1109/isit.2005.1523405.

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Koller, C., A. Graell i Amat, J. Kliewer, F. Vatta, and Danniel J. Costello. "Tuned turbo codes." In 2008 International Symposium on Information Theory and its Applications (ISITA 2008). IEEE, 2008. http://dx.doi.org/10.1109/isita.2008.4895619.

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Trajkovic, Vladimir D., Minyue Fu, and Peter J. Schreier. "Turbo Equalization With Irregular Turbo Codes." In 2007 4th International Symposium on Wireless Communication Systems. IEEE, 2007. http://dx.doi.org/10.1109/iswcs.2007.4392320.

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Kovaci, Maria, Horia Balta, Alexandre de Baynast, and Miranda M. Nafornita. "Performance Comparison of Punctured Turbo Codes and Multi Binary Turbo Codes." In 2007 International Symposium on Signals, Circuits and Systems. IEEE, 2007. http://dx.doi.org/10.1109/isscs.2007.4292768.

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Vafi, Sina, Tadeusz Wysocki, and Mehran Abolhasan. "Serially Concatenated Turbo Codes." In 2009 5th International Conference on Wireless Communications, Networking and Mobile Computing (WiCOM). IEEE, 2009. http://dx.doi.org/10.1109/wicom.2009.5303570.

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Poulin, David, Jean-Pierre Tillich, and Harold Ollivier. "Quantum serial turbo-codes." In 2008 IEEE International Symposium on Information Theory - ISIT. IEEE, 2008. http://dx.doi.org/10.1109/isit.2008.4594998.

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9

Moloudi, Saeedeh, Michael Lentmaier, and Alexandre Graell i Amat. "Spatially coupled turbo codes." In 2014 8th International Symposium on Turbo Codes and Iterative Information Processing (ISTC). IEEE, 2014. http://dx.doi.org/10.1109/istc.2014.6955090.

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10

Qi, Yongzhi, Deyuan Chen, and Can Zhang. "Punctured Turbo-Polar Codes." In 2019 IEEE 11th International Conference on Communication Software and Networks (ICCSN). IEEE, 2019. http://dx.doi.org/10.1109/iccsn.2019.8905352.

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Reports on the topic "Turbo codes"

1

Mitchell, Gregory. Investigation of Hamming, Reed-Solomon, and Turbo Forward Error Correcting Codes. Fort Belvoir, VA: Defense Technical Information Center, July 2009. http://dx.doi.org/10.21236/ada505116.

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2

McEliece, Robert, and Padhraic Smyth. Turbo Decoding of High Performance Error-Correcting Codes via Belief Propagation. Fort Belvoir, VA: Defense Technical Information Center, December 1998. http://dx.doi.org/10.21236/ada386835.

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