Bibliographies thématiques / Ordered Statistic Decoding

Littérature scientifique sur le sujet « Ordered Statistic Decoding »

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Publié le 14 mars 2023

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Articles de revues sur le sujet "Ordered Statistic Decoding"

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Wu, Daolong, Ying Li, Xudong Guo et Yue Sun. « Ordered Statistic Decoding for Short Polar Codes ». IEEE Communications Letters 20, no 6 (juin 2016) : 1064–67. http://dx.doi.org/10.1109/lcomm.2016.2539170.

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Qin, Kangjian, et Zhaoyang Zhang. « Low-Latency Adaptive Ordered Statistic Decoding of Polar Codes ». IEEE Access 7 (2019) : 134226–35. http://dx.doi.org/10.1109/access.2019.2940525.

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Qiao, Guo Lei. « Parallel Decoding Scheme Based on OSD and KNIH Algorithms ». Advanced Materials Research 433-440 (janvier 2012) : 4813–16. http://dx.doi.org/10.4028/www.scientific.net/amr.433-440.4813.

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In this contribution, KNIH algorithm and Ordered Statistic Decoding (OSD) algorithm are investigated, based on which, a novel KNIH-OSD parallel decoding scheme for LDPC codes is proposed. KNIH decoding algorithm processes certain LRPs of a received sequence, while OSD algorithm processes certain MRIPs of a received sequence. If there are too many errors in MRIPs, the OSD algorithm will fail, on the contrary, if there are too many errors in LRPs, the KNIH algorithm will fail. This contribution proposes a parallel decoding scheme based on the complementary characteristic of these two algorithms. Simulation results show that the proposed scheme is feasible and effective. Compared with OSD and KNIH algorithm, the decoding performance is improved.
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Yu, Shuyan, et Qin Huang. « Hard Reliability-Based Ordered Statistic Decoding and Its Application to McEliece Public Key Cryptosystem ». IEEE Communications Letters 26, no 3 (mars 2022) : 490–94. http://dx.doi.org/10.1109/lcomm.2021.3137529.

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Jan, Qasim, Shahid Hussain, Muhammad Furqan, Zhiwen Pan, Nan Liu et Xiaohu You. « A Novel Flip-List-Enabled Belief Propagation Decoder for Polar Codes ». Electronics 10, no 18 (18 septembre 2021) : 2302. http://dx.doi.org/10.3390/electronics10182302.

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Due to the design principle of parallel processing, belief propagation (BP) decoding is attractive, and it provides good error-correction performance compared with successive cancellation (SC) decoding. However, its error-correction performance is still inferior to that of successive cancellation list (SCL) decoding. Consequently, this paper proposes a novel flip-list- (FL)-enabled belief propagation (BP) method to improve the error-correction performance of BP decoding for polar codes with low computational complexity. The proposed technique identifies the vulnerable channel log-likelihood ratio (LLR) that deteriorates the BP decoding result. The FL is utilized to efficiently identify the erroneous channel LLRs and correct them for the next BP decoding attempt. The preprocessed channel LLR through FL improves the error-correction performance with minimal flipping attempts and reduces the computational complexity. The proposed technique was compared with the state-of-the-art BP, i.e., BP bit-flip (BP-BF), generalized BP-flip (GBPF), cyclic redundancy check (CRC)-aided (CA-SCL) decoding, and ordered statistic decoding (OSD), algorithms. Simulation results showed that the FL-BP had an excellent block error rate (BLER) performance gain up to 0.7 dB compared with BP, BP-BF, and GBPF decoder. Besides, the computational complexity was reduced considerably in the high signal-to-noise ratio (SNR) regime compared with the BP-BF and GBPF decoding methods.
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Yue, Chentao, Mahyar Shirvanimoghaddam, Branka Vucetic et Yonghui Li. « A Revisit to Ordered Statistics Decoding : Distance Distribution and Decoding Rules ». IEEE Transactions on Information Theory 67, no 7 (juillet 2021) : 4288–337. http://dx.doi.org/10.1109/tit.2021.3078575.

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Xing, Yusheng, et Guofang Tu. « A Low-Complexity Ordered Statistics Decoding Algorithm for Short Polar Codes ». Applied Sciences 9, no 5 (26 février 2019) : 831. http://dx.doi.org/10.3390/app9050831.

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In this paper, we propose a low-complexity ordered statistics decoding (OSD) algorithm called threshold-based OSD (TH-OSD) that uses a threshold on the discrepancy of the candidate codewords to speed up the decoding of short polar codes. To determine the threshold, we use the probability distribution of the discrepancy value of the maximal likelihood codeword with a predefined parameter controlling the trade-off between the error correction performance and the decoding complexity. We also derive an upper-bound of the word error rate (WER) for the proposed algorithm. The complexity analysis shows that our algorithm is faster than the conventional successive cancellation (SC) decoding algorithm in mid-to-high signal-to-noise ratio (SNR) situations and much faster than the SC list (SCL) decoding algorithm. Our addition of a list approach to our proposed algorithm further narrows the error correction performance gap between our TH-OSD and OSD. Our simulation results show that, with appropriate thresholds, our proposed algorithm achieves performance close to OSD’s while testing significantly fewer codewords than OSD, especially with low SNR values. Even a small list is sufficient for TH-OSD to match OSD’s error rate in short-code scenarios. The algorithm can be easily extended to longer code lengths.
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Yue, Chentao, Mahyar Shirvanimoghaddam, Giyoon Park, Ok-Sun Park, Branka Vucetic et Yonghui Li. « Probability-Based Ordered-Statistics Decoding for Short Block Codes ». IEEE Communications Letters 25, no 6 (juin 2021) : 1791–95. http://dx.doi.org/10.1109/lcomm.2021.3058978.

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Alnawayseh, Saif E. A., et Pavel Loskot. « Complexity Reduction of Ordered Statistics Decoding Using Side Information ». IEEE Communications Letters 16, no 2 (février 2012) : 249–51. http://dx.doi.org/10.1109/lcomm.2011.121311.111997.

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Lim, Fabian, Aleksandar Kavcic et Marc Fossorier. « List Decoding Techniques for Intersymbol Interference Channels Using Ordered Statistics ». IEEE Journal on Selected Areas in Communications 28, no 2 (février 2010) : 241–51. http://dx.doi.org/10.1109/jsac.2010.100213.

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Thèses sur le sujet "Ordered Statistic Decoding"

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Yue, Chentao. « Decoding Techniques based on Ordered Statistics ». Thesis, The University of Sydney, 2021. https://hdl.handle.net/2123/25059.

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Short code design and related decoding algorithms have gained a great deal of interest among industry and academia recently, triggered by the stringent requirements of the new ultra-reliable and low-latency communications (URLLC) service for mission-critical Internet of Things (IoT) services. URLLC services mandate the use of short block-length codes to achieve hundred-of-microsecond time-to-transmit latency and ultra-low block error rates. As a theoretical milestone, Polyanskiy et al. have given new capacity bounds tighter than Shannon's work at the finite block length regime. However, with most conventional channel codes such as LDPC, Polar, Turbo, and convolutional codes suffering from performance degradation when the code length is short, it is still an open research problem to seek potential coding schemes for URLLC. As a kind of maximum-likelihood decoding algorithm, ordered statistics decoding (OSD) can be applied with classical strong channel codes, e.g. BCH codes and Reed-Solomon codes, to potentially meet the requirements of URLLC. In this thesis, I am taking a step towards seeking practical decoders for URLLC by revisiting the OSD and significantly reducing its decoding complexity. I first provide a comprehensive analysis of the OSD algorithm by characterizing the statistical properties, evolution and the distribution of the Hamming distance, and the weighted Hamming distance (WHD) from codeword estimates to the received sequence in the OSD algorithm. I prove that the distance distributions in OSD can be characterized as mixture models capturing the decoding error probability and code weight distribution, reflecting the inherent relations between error rate performance, distance, and channel conditions. Based on the statistical properties of distances and with the aim to reduce the decoding complexity, several decoding techniques are proposed, and their decoding error performance and complexity are accordingly analyzed. Simulation results for decoding various eBCH codes demonstrate that the proposed techniques can be conveniently combined with the OSD algorithm and its variants to significantly reduce the decoding complexity with a negligible loss in decoding error performance. Finally, I proposed two complete decoding designs, namely segmentation-discarding decoding, and probability-based ordered statistics decoding, as potential solutions for URLLC scenarios. Simulation results for different codes show that our proposed decoding algorithm can significantly reduce the decoding complexity compared to the existing OSD algorithms in the literature.
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Fossorier, Marc P. C. « Decoding of linear block codes based on ordered statistics ». Thesis, 1994. http://hdl.handle.net/10125/9751.

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Hsieh, Shentai, et 謝昇泰. « Performance Evaluation of Ordered-Statistics Soft Decision Decoding for Hybrid ARQ Protocols and Adaptive Error Control ». Thesis, 2004. http://ndltd.ncl.edu.tw/handle/29921195438087772589.

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碩士
國立臺灣大學
電信工程學研究所
92
For data transmission on wireless channel, because of the higher error probability, we need some more efficiency error control protocols to make sure the QoS of communication. We use soft-decision error correcting codes to improve the system performance of traditional error control mechanism; further more, we design an adaptive error control mechanism using channel condition. We aims the system performance of Throughput and Reliability.
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Wang, Rui-Ming, et 王瑞銘. « A Study on Nonbinary Order Statistic Decoding Algorithm for RS Codes under Jamming Environment ». Thesis, 2012. http://ndltd.ncl.edu.tw/handle/37177768784901625601.

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碩士
中原大學
電子工程研究所
100
Soft-decision decoding of Reed-Solomon (RS) code can improve the decoding performance significantly, but the complexity of the system also increases. Therefore, most of the communication systems use the hard-decision decoder because of low complexity. Order statistic decoding algorithm (OSD) is an effective decoding algorithm which can reduce the complexity of the system. In this thesis, we propose a non-binary OSD algorithm that can be applied to non-binary RS code. There are two methods of computing reliability and decoding metric in the proposed algorithm. We also analyze the performance of the algorithm under partial band noise jamming (PBNJ) environment. Furthermore, in order to reduce the complexity of the system further, we proposed two schemes to achieve the requirement. Finally, we compare the performance of various methods under different environments.
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Chapitres de livres sur le sujet "Ordered Statistic Decoding"

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Osipov, Dmitry. « Inner Convolutional Codes and Ordered Statistics Decoding in a Multiple Access System Enabling Wireless Coexistence ». Dans Multiple Access Communcations, 33–38. Cham : Springer International Publishing, 2013. http://dx.doi.org/10.1007/978-3-319-03871-1_4.

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Hunziker, Thomas. « On the Employment of SMI Beamforming for Cochannel Interference Mitigation in Digital Radio ». Dans Handbook on Advancements in Smart Antenna Technologies for Wireless Networks, 82–93. IGI Global, 2009. http://dx.doi.org/10.4018/978-1-59904-988-5.ch004.

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Many common adaptive beamforming methods are based on a sample matrix inversion (SMI). The schemes can be applied in two ways. The sample covariance matrices are either computed over preambles, or the sample basis for the SMI and the target of the beamforming are identical. A vector space representation provides insight into the classic SMI-based beamforming variants, and enables elegant derivations of the well-known second-order statistical properties of the output signals. Moreover, the vector space representation is helpful in the definition of appropriate interfaces between beamfoming and soft-decision signal decoding in receivers aiming at adaptive cochannel interference mitigation. It turns out that the performance of standard receivers incorporating SMI-based beamforming on short signal intervals and decoding of BICM (bit-interleaved coded modulation) signals can be significantly improved by proper interface design.
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Richmond, Barry J., et Matthew C. Wiener. « Combining Order Statistics with Bayes Theorem for Millisecond-by-Millisecond Decoding of Spike Trains ». Dans Bayesian Brain, 71–91. The MIT Press, 2006. http://dx.doi.org/10.7551/mitpress/9780262042383.003.0004.

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« Combining Order Statistics with Bayes Theorem for Millisecond-by-Millisecond Decoding of Spike Trains ». Dans Bayesian Brain. The MIT Press, 2006. http://dx.doi.org/10.7551/mitpress/1535.003.0008.

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Actes de conférences sur le sujet "Ordered Statistic Decoding"

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Yue, Chentao, Mahyar Shirvanimoghaddam, Yonghui Li et Branka Vucetic. « Segmentation-Discarding Ordered-Statistic Decoding for Linear Block Codes ». Dans GLOBECOM 2019 - 2019 IEEE Global Communications Conference. IEEE, 2019. http://dx.doi.org/10.1109/globecom38437.2019.9014173.

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Zijian, Dong, Liu Fei et Song Yaolian. « Improved syndrome-based ordered statistic decoding algorithm for LDPC codes ». Dans 2010 2nd International Conference on Signal Processing Systems (ICSPS). IEEE, 2010. http://dx.doi.org/10.1109/icsps.2010.5555626.

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Qin, Kangjian, et Zhaoyang Zhang. « Adaptive Ordered Statistic Decoding of Polar Codes for URLLC Systems ». Dans 2018 IEEE Globecom Workshops (GC Wkshps). IEEE, 2018. http://dx.doi.org/10.1109/glocomw.2018.8644298.

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Kawauchi, Yuki, Kohtaro Watanabe et Seiji Kataoka. « An improvement of decoding time of ordered statistic decoding for medium length LDPC codes ». Dans 2017 Fourth Asian Conference on Defence Technology - Japan (ACDT). IEEE, 2017. http://dx.doi.org/10.1109/acdtj.2017.8259607.

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Kim, Changhyeon, Dongyoung Rim, Jeongwon Choe, Dongyun Kam, Giyoon Park, Seokki Kim et Youngjoo Lee. « FPGA-Based Ordered Statistic Decoding Architecture for B5G/6G URLLC IIOT Networks ». Dans 2021 IEEE Asian Solid-State Circuits Conference (A-SSCC). IEEE, 2021. http://dx.doi.org/10.1109/a-sscc53895.2021.9634714.

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Zhou, Wei, et Michael Lentmaier. « Improving Short-Length LDPC Codes with a CRC and Iterative Ordered Statistic Decoding : (Invited Paper) ». Dans 2019 53rd Annual Conference on Information Sciences and Systems (CISS). IEEE, 2019. http://dx.doi.org/10.1109/ciss.2019.8693053.

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Yang, Lijia, et Li Chen. « Low-Latency Ordered Statistics Decoding of BCH Codes ». Dans 2022 IEEE Information Theory Workshop (ITW). IEEE, 2022. http://dx.doi.org/10.1109/itw54588.2022.9965799.

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Yang, Lijia, Wenhao Chen et Li Chen. « Reduced Complexity Ordered Statistics Decoding of Linear Block Codes ». Dans 2022 IEEE/CIC International Conference on Communications in China (ICCC Workshops). IEEE, 2022. http://dx.doi.org/10.1109/icccworkshops55477.2022.9896679.

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Park, Ok-Sun, Gi Yoon Park et Young Ha Lee. « Improvement of ordered statistics decoding for low-rate BCH codes ». Dans 2019 International Conference on Information and Communication Technology Convergence (ICTC). IEEE, 2019. http://dx.doi.org/10.1109/ictc46691.2019.8939997.

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Wang, Yiwen, Jifan Liang et Xiao Ma. « Local Constraint-Based Ordered Statistics Decoding for Short Block Codes ». Dans 2022 IEEE Information Theory Workshop (ITW). IEEE, 2022. http://dx.doi.org/10.1109/itw54588.2022.9965916.

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