Journal articles: 'Block turbo codes'

1

Ryumshin, K. Yu. "ON CYCLICITY OF BLOCK TURBO CODES." Telecommunications and Radio Engineering 71, no. 7 (2012): 623–29. http://dx.doi.org/10.1615/telecomradeng.v71.i7.40.

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Son, Jaeyong, Jun Jin Kong, and Kyeongcheol Yang. "Efficient decoding of block turbo codes." Journal of Communications and Networks 20, no. 4 (August 2018): 345–53. http://dx.doi.org/10.1109/jcn.2018.000050.

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3

Kerouédan, Sylvie, Patrick Adde, and Ramesh Pyndiah. "How we implemented block turbo codes?" Annales Des Télécommunications 56, no. 7-8 (July 2001): 447–54. http://dx.doi.org/10.1007/bf02995455.

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4

Afghah, Fatemeh, Mehrdad Ardebilipo, and Abolfazl Razi. "Fast Turbo Codes Concatenated With Space-Time Block Codes." Journal of Applied Sciences 8, no. 16 (August 1, 2008): 2867–73. http://dx.doi.org/10.3923/jas.2008.2867.2873.

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5

Pyndiah, R. M. "Near-optimum decoding of product codes: block turbo codes." IEEE Transactions on Communications 46, no. 8 (1998): 1003–10. http://dx.doi.org/10.1109/26.705396.

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Babich, Fulvio, Guido Montorsi, and Francesca Vatta. "Turbo Codes Performance Optimization over Block Fading Channels." Journal of Communications Software and Systems 2, no. 3 (April 5, 2017): 228. http://dx.doi.org/10.24138/jcomss.v2i3.285.

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In this paper, the best achievable performance of a turbo coded system on a block fading channel is obtained, assuming binary antipodal modulation. A rate 1/3 turbo code is considered, obtained by concatenating, through a random interleaver, an 8-states rate 1/2 and a rate 1 convolutional codes (CC). The block fading channel model is motivated by the fact that in many wireless systems the coherence time of the channel is much longer than one symbol interval, resulting in adjacent symbols being affected by the same fading value. The fading blocks will experience independent fades, assuming a sufficient separation in time, in frequency, or both in time and in frequency. This channel model is suitable for analyzing, forinstance, wireless communication systems employing techniques such as slow frequency-hopping, as is done in the Global System for Mobile communications (GSM).In such systems, coded information is transmitted over a small number of fading channels in order to achieve diversity. The best coded information allocations over a certain number of fading channels are evaluated, using the Eades-McKay algorithm to generate distinct permutations of a multiset. Bounds on the achievable performance due to coding are derived using information-theoretic techniques. In particular, in the paper an analytical method is proposed, based on the sphere-packing bounding technique, to assess the achievable performance. Moreover, simulation results are obtained and compared with the theoretical ones.

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Al-Dweik, A., S. Le Goff, and B. Sharif. "A Hybrid Decoder for Block Turbo Codes." IEEE Transactions on Communications 57, no. 5 (May 2009): 1229–32. http://dx.doi.org/10.1109/tcomm.2009.05.070107.

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8

Mahran, A., and M. Benaissa. "Adaptive Chase algorithm for block turbo codes." Electronics Letters 39, no. 7 (2003): 617. http://dx.doi.org/10.1049/el:20030421.

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Huebner, A., K. Sh Zigangirov, and Daniel J. Costello. "Laminated turbo codes: A new class of block-convolutional codes." IEEE Transactions on Information Theory 54, no. 7 (July 2008): 3024–34. http://dx.doi.org/10.1109/tit.2008.924702.

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10

Bee Leong Yeap, Tong Hooi Liew, J. Hamorsky, and L. Hanzo. "Comparative study of turbo equalization schemes using convolutional, convolutional turbo, and block-turbo codes." IEEE Transactions on Wireless Communications 1, no. 2 (April 2002): 266–73. http://dx.doi.org/10.1109/7693.994820.

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11

Du, Y., and K. T. Chan. "Enhanced Space-Time Block Coded Systems by Concatenating Turbo Product Codes." IEEE Communications Letters 8, no. 6 (June 2004): 388–90. http://dx.doi.org/10.1109/lcomm.2004.831327.

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Ramasamy, K., Mohammad Umar Siddiqi, Mohamad Yusoff Alias, and A. Arunagiri. "Performance comparison of convolutional and block turbo codes." IEICE Electronics Express 3, no. 13 (2006): 322–27. http://dx.doi.org/10.1587/elex.3.322.

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13

Lim, Je-Hun, and Young-Joon Song. "Efficient Decoding Technique for Block Product Turbo Codes." International Journal of Multimedia and Ubiquitous Engineering 11, no. 8 (August 31, 2016): 121–30. http://dx.doi.org/10.14257/ijmue.2016.11.8.13.

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Lu, Pen-Yao, Erl-Huei Lu, and Tso-Cho Chen. "An Efficient Hybrid Decoder for Block Turbo Codes." IEEE Communications Letters 18, no. 12 (December 2014): 2077–80. http://dx.doi.org/10.1109/lcomm.2014.2364229.

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15

Dave, S., Junghwan Kim, and S. C. Kwatra. "An efficient decoding algorithm for block turbo codes." IEEE Transactions on Communications 49, no. 1 (2001): 41–46. http://dx.doi.org/10.1109/26.898249.

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16

Nazarov, L. E., and I. V. Golovkin. "Turbo-Codes Based on Block Codes: Principles of Formation and Reception." Telecommunications and Radio Engineering 66, no. 14 (2007): 1291–300. http://dx.doi.org/10.1615/telecomradeng.v66.i14.70.

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17

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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18

Siegrist, M., T. Schorr, A. Dittrich, W. Sauer-Greff, and R. Urbansky. "Turbo Equalization Of Nonlinear ISI-channels Using High Rate FEC Codes." Advances in Radio Science 3 (May 12, 2005): 259–63. http://dx.doi.org/10.5194/ars-3-259-2005.

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Abstract. Turbo equalization is a widely known method to cope with low signal to noise ratio (SNR) channels corrupted by linear intersymbol interference (ISI) (Berrou and Galvieux, 1993; Hagenauer et al., 1997). Recently in this workshop it was reported that also for nonlinear channels a remarkable turbo decoding gain can be achieved (Siegrist et al., 2001). However, the classical turbo equalization relies on code rates at 1/3 up to 1/2 which makes it quite unattractive for high rate data transmission. Considering the potential of iterative equalization and decoding, we obtain a considerable turbo decoding gain also for high rate codes of less than 7% redundancy by using punctured convolutional codes and block codes.

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19

Deep, K. Ujwal, and Vidhyacharan Bhaskar. "Fast turbo codes with space-time block codes in fast fading channels." International Journal of Communication Systems 28, no. 5 (December 19, 2013): 944–51. http://dx.doi.org/10.1002/dac.2717.

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20

Kim, Sooyoung Kim, Woo Seok Yang Yang, and Ho-Jin Lee Lee. "Trellis-Based Decoding of High-Dimensional Block Turbo Codes." ETRI Journal 25, no. 1 (February 1, 2003): 1–8. http://dx.doi.org/10.4218/etrij.03.0103.0115.

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21

Wang, Kang, Xingcheng Liu, and Paul Cull. "Adaptive SNR estimation algorithms for decoding block turbo codes." Kybernetes 39, no. 8 (August 10, 2010): 1298–304. http://dx.doi.org/10.1108/03684921011063583.

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22

Zhou, Rong, RaphaËl Le Bidan, Ramesh Pyndiah, and AndrÉ Goalic. "Low-Complexity High-Rate Reed--Solomon Block Turbo Codes." IEEE Transactions on Communications 55, no. 9 (September 2007): 1656–60. http://dx.doi.org/10.1109/tcomm.2007.904365.

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23

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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Biswas, Kusan. "A Robust and High Capacity Data Hiding Method for H.265/HEVC Compressed Videos with Block Roughness Measure and Error Correcting Techniques." Symmetry 11, no. 11 (November 3, 2019): 1360. http://dx.doi.org/10.3390/sym11111360.

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Recently, the H.265/HEVC video coding has been standardised by the ITU-T VCEG and the ISO/IEC MPEG. The improvements in H.265/HEVC video coding structure (CTU, motion compensation, inter- and intra-prediction, etc.) open up new possibilities to realise better data hiding algorithms in terms of capacity and robustness. In this paper, we propose a new data hiding method for HEVC videos. The proposed method embeds data in 4 × 4 and some selected larger transform units. As theory of Human Visual System suggests that human vision is less sensitive to change in uneven areas, relatively coarser blocks among the 8 × 8 and 16 × 16 blocks are selected as embedding destinations based on the proposed Jensen-Shannon Divergence and Second Moment (JSD-SM) block coarseness measure. In addition, the SME(1,3,7) embedding technique is able to embed three bits of message by modifying only one coefficient and therefore exhibits superior distortion performance. Furthermore, to achieve better robustness against re-compression attacks, BCH and Turbo error correcting codes have been used. Comparative studies of BCH and Turbo codes show the effectiveness of Turbo codes. Experimental results show that the proposed method achieves greater payload capacity and robustness than many existing state-of-the-art techniques without compromising on the visual quality.

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Anim-Appiah, K., and S. W. McLaughlin. "Turbo codes cascaded with high-rate block codes for (O, κ)-constrained channels." IEEE Journal on Selected Areas in Communications 19, no. 4 (April 2001): 677–85. http://dx.doi.org/10.1109/49.920176.

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26

Soliman, Tamer H. M., Fengfan Yang, and Yang Ejaz. "The Design of New Modified Block and Matched S-Random Interleavers for Turbo Codes." International Journal of Modeling and Optimization 4, no. 5 (October 2014): 395–401. http://dx.doi.org/10.7763/ijmo.2014.v4.407.

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27

YU, XIANGBIN, and GUANGGUO BI. "FULL-RATE AND LOW-COMPLEXITY SPACE-TIME BLOCK CODING CONCATENATED WITH CHANNEL CODES." International Journal of Information Technology & Decision Making 06, no. 01 (March 2007): 5–14. http://dx.doi.org/10.1142/s0219622007002381.

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Space-time block (STB) coding has been an effective transmit diversity technique for combating fading recently. In this paper, a full-rate and low-complexity STB coding scheme with complex orthogonal design for multiple antennas is proposed, and turbo code is employed as channel coding to improve the proposed code scheme performance further. Compared with full-diversity multiple antennas STB coding schemes, the proposed scheme can implement full data rate, partial diversity and a smaller complexity, and has more spatial redundancy information. Moreover, using the proposed scheme can form efficient spatial interleaving, thus performance loss due to partial diversity is effectively compensated by the concatenation of turbo coding. Simulation results show that on the condition of the same system throughput and concatenation of turbo code, the proposed scheme has lower bit error rate (BER) than those low-rate and full-diversity multiple antennas STB coding schemes.

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28

Mahran, A., and M. Benaissa. "Iterative Decoding With a Hamming Threshold for Block Turbo Codes." IEEE Communications Letters 8, no. 9 (September 2004): 567–69. http://dx.doi.org/10.1109/lcomm.2004.835331.

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Nahidul, Md, Md Rakibul, Mahmudul Hasan, and Ohidujjaman O. "Designing a Sensible Block Semi-Random Interleaver for Turbo Codes." International Journal of Computer Applications 145, no. 2 (July 15, 2016): 14–17. http://dx.doi.org/10.5120/ijca2016910575.

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30

Chandra, Daryus, Zunaira Babar, Soon Xin Ng, and Lajos Hanzo. "Near-Hashing-Bound Multiple-Rate Quantum Turbo Short-Block Codes." IEEE Access 7 (2019): 52712–30. http://dx.doi.org/10.1109/access.2019.2911515.

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31

S Kumar, Parvathy, and N. Kumaratharan. "Performance Enhancement of MC-CDMA System through Turbo Block Codes." Universal Journal of Communications and Network 1, no. 2 (September 2013): 50–55. http://dx.doi.org/10.13189/ujcn.2013.010203.

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32

Sason, Igal, and Shlomo Shamai. "Bounds on the error probability ofml decoding for block and turbo-block codes." Annales Des Télécommunications 54, no. 3-4 (March 1999): 183–200. http://dx.doi.org/10.1007/bf02998579.

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33

Ghaith, Alaa. "Improvement Of Block Product Turbo Coding By Using A New Concept Of Soft Hamming Decoder." European Scientific Journal, ESJ 12, no. 18 (June 29, 2016): 167. http://dx.doi.org/10.19044/esj.2016.v12n18p167.

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The block product turbo code (BPTC) is classified as one of block turbo code concatenation forms. The Hamming code can detect two-bit error and correct one-bit error. The BPTC uses two Hamming codes for "column" coding and "row" coding, it has improved the Hamming code correcting only one error. In addition, the BPTC carries out block interleaving coding for disorganizing the transmission sequence before transmission, so as to avoid burst errors when the signal meets multi-path channel in the channel. This paper will discuss the decoding mechanism of the BPTC and analyze the efficiency of using a soft decoding algorithm in the decoding process. The soft Hamming Decoder is based on error patterns which belong to the same syndrome. It is shown that it is sufficient to investigate error patterns with one and two errors to gain up to 1.2 dB compared to hard decision decoding. Here, we will consider also the error patterns with three errors which belong to the determined syndrome, which increases the gain and improves the quality of the soft-output due to the increased number of comparisons with valid code words, in despite that, it will increase the complexity of the decoding process. The system is based on two Hamming block channel code combinations, which can be similar or different, a block interleaving to construct a BPSK modulation and BPTC coding system in the concept of feedback encoding in turbo code over an AWGN channel. To observe its coding improvement, we present the simulation results for the soft decoding of the BPTC codes of a code word length from 49 bits (using two (7,4) codes) up to 1440 bits (using two (127,120) codes).

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34

Yue, D. W., and E. H. Yang. "Asymptotically Gaussian Weight Distribution and Performance of Multicomponent Turbo Block Codes and Product Codes." IEEE Transactions on Communications 52, no. 5 (May 2004): 728–36. http://dx.doi.org/10.1109/tcomm.2004.826250.

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35

Nazarov, Lev E. "The Decoding Algorithms For Error-Correcting Product Codes Based On Project Geometry Low-Density Parity-Check Codes." Radioelectronics. Nanosystems. Information Technologies 12, no. 3 (October 30, 2020): 399–406. http://dx.doi.org/10.17725/rensit.2020.12.399.

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The focus of this paper is directed towards the investigation of the characteristics of symbol-by-symbol iterative decoding algorithms for error-correcting block product-codes (block turbo-codes) which enable to reliable information transfer at relatively low received signal/noise and provide high power efficiency. Specific feature of investigated product codes is construction with usage of low-density parity-check codes (LDPC) and these code constructions are in the class of LDPC too. According to this fact the considered code constructions have symbol-by-symbol decoding algorithms developed for total class LDPC codes, namely BP (belief propagation) and its modification MIN_SUM_BP. The BP decoding algorithm is iterative and for implementation the signal/noise is required, for implementation of MIN_SUM_BP decoding algorithm the signal/noise is not required. The resulted characteristics of product codes constructed with usage of LDPC based on project geometry (length of code words, information volume, code rate, error performances) are presented in this paper. These component LDPC codes are cyclic and have encoding and decoding algorithms with low complexity implementation. The computer simulations for encoding and iterative symbol-by-symbol decoding algorithms for the number of turbo-codes with different code rate and information volumes are performed. The results of computer simulations have shown that MIN_SUM_BP decoding algorithm is more effective than BP decoding algorithm for channel with additive white gaussian noise concerning error-performances.

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36

Ahn, Byungkyu, Sungsik Yoon, and Jun Heo. "Low Complexity Syndrome-Based Decoding Algorithm Applied to Block Turbo Codes." IEEE Access 6 (2018): 26693–706. http://dx.doi.org/10.1109/access.2018.2829087.

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37

Chen, Bin, and Mark F. Flanagan. "Network-turbo-coding-based cooperation with distributed space-time block codes." Transactions on Emerging Telecommunications Technologies 26, no. 6 (February 11, 2014): 992–1002. http://dx.doi.org/10.1002/ett.2780.

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38

Nazarov, L. E., and P. V. Shishkin. "The Characteristics of Error-Сorrecting Block Turbo-Codes Based on Low-Density Parity-Check Codes." INFORMACIONNYE TEHNOLOGII 24, no. 6 (June 7, 2018): 427–32. http://dx.doi.org/10.17587/it.24.427-432.

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Nazarov, L. E., and I. V. Golovkin. "Behavior of ultimate probability characteristics of iterative decoding of turbo codes based on block codes." Journal of Communications Technology and Electronics 51, no. 6 (June 2006): 670–76. http://dx.doi.org/10.1134/s1064226906060088.

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40

Babich, Fulvio, and Francesca Vatta. "On the Error Statistics of Turbo Decoding for Hybrid Concatenated Codes Design." Journal of Communications Software and Systems 15, no. 2 (June 7, 2019): 202. http://dx.doi.org/10.24138/jcomss.v15i2.669.

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In this paper we propose a model for the generation of error patterns at the output of a turbo decoder. One of the advantages of this model is that it can be used to generate the error sequence with little effort. Thus, it provides a basis for designing hybrid concatenated codes (HCCs) employing the turbo code as inner code. These coding schemes combine the features of parallel and serially concatenated codes and thus offer more freedom in code design. It has been demonstrated, in fact, that HCCs can perform closer to capacity than serially concatenated codes while still maintaining a minimum distance that grows linearly with block length. In particular, small memory-one component encoders are sufficient to yield asymptotically good code ensembles for such schemes. The resulting codes provide low complexity encoding and decoding and, in many cases, can be decoded using relatively few iterations.

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41

Weithoffer, Stefan, and Norbert Wehn. "Where to go from here? New cross layer techniques for LTE Turbo-Code decoding at high code rates." Advances in Radio Science 16 (September 4, 2018): 77–87. http://dx.doi.org/10.5194/ars-16-77-2018.

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Abstract. The wide range of code rates and code block sizes supported by todays wireless communication standards, together with the requirement for a throughput in the order of Gbps, necessitates sophisticated and highly parallel channel decoder architectures. Code rates specified in the LTE standard, which uses Turbo-Codes, range up to r=0.94 to maximize the information throughput by transmitting only a minimum amount of parity information, which negatively impacts the error correcting performance. This especially holds for highly parallel hardware architectures. Therefore, the error correcting performance must be traded-off against the degree of parallel processing. State-of-the-art Turbo-Code decoder hardware architectures are optimized on code block level to alleviate this trade-off. In this paper, we follow a cross-layer approach by combining system level knowledge about the rate-matching and the transport block structure in LTE with the bit-level technique of on-the-fly CRC calculation. Thereby, our proposed Turbo-Code decoder hardware architecture achieves coding gains of 0.4–1.8 dB compared to state-of-the-art accross a wide range of code block sizes. For the fully LTE compatible Turbo-Code decoder, we demonstrate a negligible hardware overhead and a resulting high area and energy efficiency and give post place and route synthesis numbers.

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Sari, Lydia, Masagus M. Ikhsan Assiddiq U.P., Syah Alam, and Indra Surjati. "Performance Analysis of CRC-Polar Concatenated Codes." JURNAL INFOTEL 12, no. 4 (September 27, 2020): 123–28. http://dx.doi.org/10.20895/infotel.v12i4.494.

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Polar code has been proven to obtain Shannon capacity for Binary Input Discrete Memoryless Channel (BIDMC) and its use has been proposed as the channel coding in 5G technology. However, its performance is limited in finite block length, compared to Turbo or LDPC codes. This research proposes the use of various CRC codes to complement Polar codes with finite block length and analyses the performance based on Block Error Rate (BLER) to Es/N0 (dB). The CRC codes used are of degrees 11 and 24, with 3 different polynomial generators for each degree. The number of bits in the information sequence is 32. The list sizes used are 1, 2, 4, and 8. Simulation results show that the concatenation of CRC and Polar codes will yield good BLER vs Es/N0 performance for short blocks of codeword, with rates 32/864 and 54/864. Concatenating CRC codes with Polar codes will yield a BLER performance of 10-2 with Es/N0 values of -9.1 to -7.5 dB when CRC codes of degree 11 is used, depending on the SC list used. The use of CRC codes of degree 24 enables a BLER performance of 10-2 with Es/N0 values of -7 to -6 dB when the SC list used is 1 or 2. The use of CRC codes of degree 24 combined with SC list with sizes 4 or 8 will improve the BLER performance to 10-2 with Es/N0 values of -8 to -7.5 dB

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43

Adamu, Mohammed Jajere, Li Qiang, Rabiu Sale Zakariyya, Charles Okanda Nyatega, Halima Bello Kawuwa, and Ayesha Younis. "An Efficient Turbo Decoding and Frequency Domain Turbo Equalization for LTE Based Narrowband Internet of Things (NB-IoT) Systems." Sensors 21, no. 16 (August 8, 2021): 5351. http://dx.doi.org/10.3390/s21165351.

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This paper addresses the main crucial aspects of physical (PHY) layer channel coding in uplink NB-IoT systems. In uplink NB-IoT systems, various channel coding algorithms are deployed due to the nature of the adopted Long-Term Evolution (LTE) channel coding which presents a great challenge at the expense of high decoding complexity, power consumption, error floor phenomena, while experiencing performance degradation for short block lengths. For this reason, such a design considerably increases the overall system complexity, which is difficult to implement. Therefore, the existing LTE turbo codes are not recommended in NB-IoT systems and, hence, new channel coding algorithms need to be employed for LPWA specifications. First, LTE-based turbo decoding and frequency-domain turbo equalization algorithms are proposed, modifying the simplified maximum a posteriori probability (MAP) decoder and minimum mean square error (MMSE) Turbo equalization algorithms were appended to different Narrowband Physical Uplink Shared Channel (NPUSCH) subcarriers for interference cancellation. These proposed methods aim to minimize the complexity of realizing the traditional MAP turbo decoder and MMSE estimators in the newly NB-IoT PHY layer features. We compare the system performance in terms of block error rate (BLER) and computational complexity.

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BAI, C., B. MIELCZAREK, I. J. FAIR, and W. A. KRZYMIEN. "Sub-Block Recovery Scheme for Iterative Decoding of Turbo Codes with the Sub-Block Structure." IEICE Transactions on Communications E91-B, no. 5 (May 1, 2008): 1375–86. http://dx.doi.org/10.1093/ietcom/e91-b.5.1375.

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A. Alzubi, Omar. "An Empirical Study of Irregular AG Block Turbo Codes over Fading Channels." Research Journal of Applied Sciences, Engineering and Technology 11, no. 12 (December 25, 2015): 1329–35. http://dx.doi.org/10.19026/rjaset.11.2240.

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Sudharsan, V., V. Vijay Karthik, and B. Yamuna. "Reliability Level List Based Iterative SISO Decoding Algorithm for Block Turbo Codes." TELKOMNIKA (Telecommunication Computing Electronics and Control) 16, no. 5 (October 1, 2018): 2040. http://dx.doi.org/10.12928/telkomnika.v16i5.7463.

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Zhang, Weidang, Xia Shao, Mahin Torki, Atousa HajShirMohammadi, and Ivan V. Bajic. "Unequal Error Protection of JPEG2000 Images Using Short Block Length Turbo Codes." IEEE Communications Letters 15, no. 6 (June 2011): 659–61. http://dx.doi.org/10.1109/lcomm.2011.041411.101620.

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Son, Jaeyong, Kyungwhoon Cheun, and Kyeongcheol Yang. "Low-Complexity Decoding of Block Turbo Codes Based on the Chase Algorithm." IEEE Communications Letters 21, no. 4 (April 2017): 706–9. http://dx.doi.org/10.1109/lcomm.2017.2650233.

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Sang Ik Han, John P. Fonseka, and Eric M. Dowling. "Constrained Turbo Block Convolutional Codes for 100 G and Beyond Optical Transmissions." IEEE Photonics Technology Letters 26, no. 10 (May 2014): 995–98. http://dx.doi.org/10.1109/lpt.2014.2311998.

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Zong Chen, Dr Joy Iong. "5G Systems with Low Density Parity Check based Chanel Coding for Enhanced Mobile Broadband Scheme." IRO Journal on Sustainable Wireless Systems 2, no. 1 (March 25, 2020): 42–49. http://dx.doi.org/10.36548/jsws.2020.1.005.

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Abstract:

The 5G mobile communication standard based radio access technology (RAT) is analysed for implementation of several candidate coding schemes in this paper. The third generation partnership project (3GPP) in the 5G scenario based on the Enhanced mobile broadband (eMBB) scheme is considered. Factors like flexibility, complexity of computation, bit error rate (BER), and block error rate (BLER) are considered for the purpose of evaluation of the coding schemes. In order to evaluate the performance various applications and services, a suitable set is of parameters are provided. The candidate schemes considered for this purpose are polar codes, low density parity check (LDPC) and turbo codes. Fair comparison is performed by investigation of block lengths and obtaining suitable rates by proper design. In an additive white Gaussian noise (AWGN) channel, the performance of BLER / BER is obtained for diverse block lengths and code rates based on simulation. The simulation results show that the performance of LDPC is relatively efficient for various code rates and block lengths despite the better performance of polar codes at short block lengths. As an added advantage, LDPC codes also offer relatively low complexity.

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Journal articles on the topic 'Block turbo codes'

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