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Journal articles on the topic 'Binary erasure channel'

Author: Grafiati

Published: 4 June 2021

Last updated: 16 February 2022

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1

Andrievsky, Boris, Alexander L. Fradkov, and Elena V. Kudryashova. "Control of Two Satellites Relative Motion over the Packet Erasure Communication Channel with Limited Transmission Rate Based on Adaptive Coder." Electronics 9, no. 12 (December 1, 2020): 2032. http://dx.doi.org/10.3390/electronics9122032.

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The paper deals with the navigation data exchange between two satellites moving in a swarm. It is focused on the reduction of the inter-satellite demanded communication channel capacity taking into account the dynamics of the satellites relative motion and possible erasures in the channel navigation data. The feedback control law is designed ensuring the regulation of the relative satellites motion. The adaptive binary coding/decoding procedure for the satellites navigation data transmission over the limited capacity communication channel is proposed and studied for the cases of ideal and erasure channels. Results of the numerical study of the closed-loop system performance and accuracy of the data transmission algorithm on the communication channel bitrate and erasure probability are obtained by extensive simulations. It is shown that both data transmission error and regulation time depend approximately inversely proportionally on the communication rate. In addition the erasure of data in the channel with probability up to 0.3 does not influence the regulation time for sufficiently high data transmission rate.

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2

Lee, Jeong W., RÜdiger L. Urbanke, and Richard E. Blahut. "Turbo Codes in Binary Erasure Channel." IEEE Transactions on Information Theory 54, no. 4 (April 2008): 1765–73. http://dx.doi.org/10.1109/tit.2008.917723.

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3

Drăgoi, Vlad-Florin, and Gabriela Cristescu. "Bhattacharyya Parameter of Monomial Codes for the Binary Erasure Channel: From Pointwise to Average Reliability." Sensors 21, no. 9 (April 23, 2021): 2976. http://dx.doi.org/10.3390/s21092976.

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Monomial codes were recently equipped with partial order relations, a fact that allowed researchers to discover structural properties and efficient algorithm for constructing polar codes. Here, we refine the existing order relations in the particular case of the binary erasure channel. The new order relation takes us closer to the ultimate order relation induced by the pointwise evaluation of the Bhattacharyya parameter of the synthetic channels, which is still a partial order relation. To overcome this issue, we appeal to a related technique from network theory. Reliability network theory was recently used in the context of polar coding and more generally in connection with decreasing monomial codes. In this article, we investigate how the concept of average reliability is applied for polar codes designed for the binary erasure channel. Instead of minimizing the error probability of the synthetic channels, for a particular value of the erasure parameter p, our codes minimize the average error probability of the synthetic channels. By means of basic network theory results, we determine a closed formula for the average reliability of a particular synthetic channel, that recently gain the attention of researchers.

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4

Kuribayashi, Minoru. "Bias-Based Binary Fingerprinting Code Under Erasure Channel." IEEE Signal Processing Letters 25, no. 9 (September 2018): 1423–27. http://dx.doi.org/10.1109/lsp.2018.2863034.

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5

I Amat, Alexandre, and Eirik Rosnes. "Good concatenated code ensembles for the binary erasure channel." IEEE Journal on Selected Areas in Communications 27, no. 6 (August 2009): 928–43. http://dx.doi.org/10.1109/jsac.2009.090811.

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6

Thomas, Eldho K., Vincent Y. F. Tan, Alexander Vardy, and Mehul Motani. "Polar Coding for the Binary Erasure Channel With Deletions." IEEE Communications Letters 21, no. 4 (April 2017): 710–13. http://dx.doi.org/10.1109/lcomm.2017.2650918.

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7

Rashidpour, M., A. Shokrollahi, and S. H. Jamali. "Optimal regular LDPC codes for the binary erasure channel." IEEE Communications Letters 9, no. 6 (June 2005): 546–48. http://dx.doi.org/10.1109/lcomm.2005.1437366.

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8

Changuel, S., R. Le Bidan, and R. Pyndiah. "Iterative decoding of product codes over binary erasure channel." Electronics Letters 46, no. 7 (2010): 503. http://dx.doi.org/10.1049/el.2010.0411.

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9

Saberi, Amir, Farhad Farokhi, and Girish Nair. "Estimation and Control over a Nonstochastic Binary Erasure Channel." IFAC-PapersOnLine 51, no. 23 (2018): 265–70. http://dx.doi.org/10.1016/j.ifacol.2018.12.046.

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10

Dall’Arno, Michele, Sarah Brandsen, and Francesco Buscemi. "Device-independent tests of quantum channels." Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences 473, no. 2199 (March 2017): 20160721. http://dx.doi.org/10.1098/rspa.2016.0721.

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We develop a device-independent framework for testing quantum channels. That is, we falsify a hypothesis about a quantum channel based only on an observed set of input–output correlations. Formally, the problem consists of characterizing the set of input–output correlations compatible with any arbitrary given quantum channel. For binary (i.e. two input symbols, two output symbols) correlations, we show that extremal correlations are always achieved by orthogonal encodings and measurements, irrespective of whether or not the channel preserves commutativity. We further provide a full, closed-form characterization of the sets of binary correlations in the case of: (i) any dihedrally covariant qubit channel (such as any Pauli and amplitude-damping channels) and (ii) any universally-covariant commutativity-preserving channel in an arbitrary dimension (such as any erasure, depolarizing, universal cloning and universal transposition channels).

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11

Yu, Yang, Wen Chen, and Lili Wei. "Design of Convergence-Optimized Non-Binary LDPC Codes over Binary Erasure Channel." IEEE Wireless Communications Letters 1, no. 4 (August 2012): 336–39. http://dx.doi.org/10.1109/wcl.2012.050112.120297.

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12

LEE, J. W., and S. YU. "Scaling Law of Turbo Codes over the Binary Erasure Channel." IEICE Transactions on Communications E90-B, no. 2 (February 1, 2007): 338–41. http://dx.doi.org/10.1093/ietcom/e90-b.2.338.

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13

Song, Won Taek, Jinho Choi, and Jeongseok Ha. "Perfect Secrecy Over Binary Erasure Wiretap Channel of Type II." IEEE Transactions on Information Forensics and Security 7, no. 4 (August 2012): 1414–18. http://dx.doi.org/10.1109/tifs.2012.2199629.

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14

Kraidy, Ghassan M., and Valentin Savin. "Capacity-Approaching Irregular Turbo Codes for the Binary Erasure Channel." IEEE Transactions on Communications 58, no. 9 (September 2010): 2516–24. http://dx.doi.org/10.1109/tcomm.2010.09.080325.

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15

Zeng, Meng, Robert Calderbank, and Shuguang Cui. "On Design of Rateless Codes over Dying Binary Erasure Channel." IEEE Transactions on Communications 60, no. 4 (April 2012): 889–94. http://dx.doi.org/10.1109/tcomm.2012.022712.110038.

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16

Hayajneh, Khaled F., Mehrdad Valipour, and Shahram Yousefi. "Improved finite-length Luby-transform codes in the binary erasure channel." IET Communications 9, no. 8 (May 21, 2015): 1122–30. http://dx.doi.org/10.1049/iet-com.2014.0658.

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17

Hayajneh, Khaled F., and Shahram Yousefi. "Overlapped LT codes over the binary erasure channel: analysis and design." IET Communications 13, no. 16 (October 8, 2019): 2567–72. http://dx.doi.org/10.1049/iet-com.2018.5273.

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18

Lin, Hsuan-Yin, Stefan M. Moser, and Po-Ning Chen. "Weak Flip Codes and their Optimality on the Binary Erasure Channel." IEEE Transactions on Information Theory 64, no. 7 (July 2018): 5191–218. http://dx.doi.org/10.1109/tit.2018.2834924.

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19

Lee, Jeong, Rudiger Urbanke, and Richard Blahut. "On the performance of turbo codes over the binary erasure channel." IEEE Communications Letters 11, no. 1 (January 2007): 67–69. http://dx.doi.org/10.1109/lcomm.2007.061206.

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20

Pfister, H. D., I. Sason, and R. Urbanke. "Capacity-Achieving Ensembles for the Binary Erasure Channel With Bounded Complexity." IEEE Transactions on Information Theory 51, no. 7 (July 2005): 2352–79. http://dx.doi.org/10.1109/tit.2005.850079.

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21

Mirrezaei, S. M. "Towards systematic Luby transform codes: optimisation design over binary erasure channel." Electronics Letters 56, no. 11 (May 2020): 550–53. http://dx.doi.org/10.1049/el.2019.4258.

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22

Johnny, Milad, and Mohammad Reza Aref. "A Multi-Layer Encoding and Decoding Strategy for Binary Erasure Channel." IEEE Transactions on Information Theory 65, no. 7 (July 2019): 4143–51. http://dx.doi.org/10.1109/tit.2019.2893930.

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23

Yuan, Zhenhua, Chen Chen, and Ye Jin. "Erasure channel modelling–based secure bit allocation schemes for multipath routing in wireless sensor networks." International Journal of Distributed Sensor Networks 12, no. 12 (December 2016): 155014771668360. http://dx.doi.org/10.1177/1550147716683605.

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In this article, we study secure multipath routing with energy efficiency for a wireless sensor network in the presence of eavesdroppers. We consider two objectives: (1) the multipath routing scheme for maximising the energy efficiency with security constraints and (2) the multipath routing scheme for maximising the secrecy capacity. The binary erasure channel model is adopted to describe the wireless channel states among neighbouring nodes. Based on the binary erasure channel model, the problem of multipath routing degrades to a problem of bit allocation for each path. We formulate the problems and find that the problems are both quasi-convex. For the first one, it is a linear fractional optimisation problem. The optimal solution is obtained by the Charnes–Cooper transformation. For the second one, we propose an iterative algorithm to obtain the [Formula: see text]-optimal solution. The performance analysis shows that the probability of the secure bit allocation increases along with the number of multipaths and decreases along with the number of hops per path and eavesdroppers. Simulation results are presented to illustrate the proposed algorithms.

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24

Alabady, Salah Abdulghani, and Mohd Fadzli Mohd Salleh. "Binary Joint Network-Channel Coding for Reliable Multi-Hop Wireless Networks." ECTI Transactions on Electrical Engineering, Electronics, and Communications 19, no. 1 (February 28, 2021): 23–33. http://dx.doi.org/10.37936/ecti-eec.2021191.222590.

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The high and variable packet loss in wireless networks due to the unreliable nature of wireless channels, interference, link or router failure, fading, and shadowing wireless link are the main problems and challenges in implementing a reliable wireless network. Packet loss probability is the most important performance measure for real-time applications. Packet loss is due to errors, congestion in the queue because of high traffic, collision, hidden nodes, and link failures. In this paper, we focus on the links failure problem. To address this problem, improve the performance of wireless networks, and enhance and make the network survivability and availability more reliable, a new efficient binary joint network and channel coding (B-JNCC) technique is proposed. B-JNCC combines low-complexity parity-check (LCPC) channel coding and the wireless network erasure correcting with router code to detect lost packets to reduce the bit error rate and increase the packet delivery ratio over a wireless multi-access channel. B-JNCC is applied at the receiver node. Simulation results show that the proposed B-JNCC outperforms the binary symbol-wise JNCC, non-binary JNCC (NB-JNCC), and NB separate network-channel coding.

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25

Pan, Jeng-Shyang, Yao Zhao, Kang K. Yen, and Yi-Chih Hsin. "Index assignment for MDVQ over memoryless binary symmetric channel with packet erasure." IEICE Electronics Express 3, no. 1 (2006): 1–4. http://dx.doi.org/10.1587/elex.3.1.

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26

Balatsoukas-Stimming, Alexios, and Andreas Burg. "Faulty Successive Cancellation Decoding of Polar Codes for the Binary Erasure Channel." IEEE Transactions on Communications 66, no. 6 (June 2018): 2322–32. http://dx.doi.org/10.1109/tcomm.2017.2771243.

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27

Tavakoli, H., M. Ahmadian, and M. R. Peyghami. "Optimal rate irregular low-density parity-check codes in binary erasure channel." IET Communications 6, no. 13 (September 5, 2012): 2000–2006. http://dx.doi.org/10.1049/iet-com.2011.0915.

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28

Andriyanova, Iryna, and Alexandre Graell i Amat. "Threshold Saturation for Nonbinary SC-LDPC Codes on the Binary Erasure Channel." IEEE Transactions on Information Theory 62, no. 5 (May 2016): 2622–38. http://dx.doi.org/10.1109/tit.2016.2540800.

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29

Andriyanova, Iryna. "Finite-length scaling of turbo-like code ensembles on the binary erasure channel." IEEE Journal on Selected Areas in Communications 27, no. 6 (August 2009): 918–27. http://dx.doi.org/10.1109/jsac.2009.090810.

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30

Subramanian, Arunkumar, Andrew Thangaraj, Matthieu Bloch, and Steven W. McLaughlin. "Strong Secrecy on the Binary Erasure Wiretap Channel Using Large-Girth LDPC Codes." IEEE Transactions on Information Forensics and Security 6, no. 3 (September 2011): 585–94. http://dx.doi.org/10.1109/tifs.2011.2148715.

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31

Mu, Jianjun, Xiaopeng Jiao, and Xinmei Wang. "Exact thresholds for low-density parity-check codes over the binary erasure channel." Progress in Natural Science 19, no. 7 (July 2009): 897–900. http://dx.doi.org/10.1016/j.pnsc.2008.12.003.

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32

Saeedi, Hamid, and Amir H. Banihashemi. "New Sequences of Capacity Achieving LDPC Code Ensembles Over the Binary Erasure Channel." IEEE Transactions on Information Theory 56, no. 12 (December 2010): 6332–46. http://dx.doi.org/10.1109/tit.2010.2053874.

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33

Pishro-Nik, H., and F. Fekri. "On Decoding of Low-Density Parity-Check Codes Over the Binary Erasure Channel." IEEE Transactions on Information Theory 50, no. 3 (March 2004): 439–54. http://dx.doi.org/10.1109/tit.2004.824918.

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34

Barak, O., D. Burshtein, and M. Feder. "Bounds on Achievable Rates of LDPC Codes Used Over the Binary Erasure Channel." IEEE Transactions on Information Theory 50, no. 10 (October 2004): 2483–89. http://dx.doi.org/10.1109/tit.2004.834845.

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35

Burshtein, D., and G. Miller. "An Efficient Maximum-Likelihood Decoding of LDPC Codes Over the Binary Erasure Channel." IEEE Transactions on Information Theory 50, no. 11 (November 2004): 2837–44. http://dx.doi.org/10.1109/tit.2004.836694.

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36

Weinberger, Nir, and Ofer Shayevitz. "Guessing with a Bit of Help." Entropy 22, no. 1 (December 26, 2019): 39. http://dx.doi.org/10.3390/e22010039.

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What is the value of just a few bits to a guesser? We study this problem in a setup where Alice wishes to guess an independent and identically distributed (i.i.d.) random vector and can procure a fixed number of k information bits from Bob, who has observed this vector through a memoryless channel. We are interested in the guessing ratio, which we define as the ratio of Alice’s guessing-moments with and without observing Bob’s bits. For the case of a uniform binary vector observed through a binary symmetric channel, we provide two upper bounds on the guessing ratio by analyzing the performance of the dictator (for general k ≥ 1 ) and majority functions (for k = 1 ). We further provide a lower bound via maximum entropy (for general k ≥ 1 ) and a lower bound based on Fourier-analytic/hypercontractivity arguments (for k = 1 ). We then extend our maximum entropy argument to give a lower bound on the guessing ratio for a general channel with a binary uniform input that is expressed using the strong data-processing inequality constant of the reverse channel. We compute this bound for the binary erasure channel and conjecture that greedy dictator functions achieve the optimal guessing ratio.

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37

KIM, Saejoon, Seunghyuk LEE, Jun HEO, and Jongho NANG. "On-the-Fly Maximum-Likelihood Decoding of Raptor Codes over the Binary Erasure Channel." IEICE Transactions on Communications E94-B, no. 4 (2011): 1062–65. http://dx.doi.org/10.1587/transcom.e94.b.1062.

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38

HOSOYA, Gou, Hideki YAGI, Manabu KOBAYASHI, and Shigeichi HIRASAWA. "Adaptive Decoding Algorithms for Low-Density Parity-Check Codes over the Binary Erasure Channel." IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences E92-A, no. 10 (2009): 2418–30. http://dx.doi.org/10.1587/transfun.e92.a.2418.

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39

Saejoon Kim, Seunghyuk Lee, and Sae-Young Chung. "An efficient algorithm for ML decoding of raptor codes over the binary erasure channel." IEEE Communications Letters 12, no. 8 (August 2008): 578–80. http://dx.doi.org/10.1109/lcomm.2008.080599.

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40

Rosnes, Eirik, and Oyvind Ytrehus. "Turbo Decoding on the Binary Erasure Channel: Finite-Length Analysis and Turbo Stopping Sets." IEEE Transactions on Information Theory 53, no. 11 (November 2007): 4059–75. http://dx.doi.org/10.1109/tit.2007.907496.

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41

Changyan Di, D. Proietti, I. E. Telatar, T. J. Richardson, and R. L. Urbanke. "Finite-length analysis of low-density parity-check codes on the binary erasure channel." IEEE Transactions on Information Theory 48, no. 6 (June 2002): 1570–79. http://dx.doi.org/10.1109/tit.2002.1003839.

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42

Lauri, J., and C. J. Tjhai. "Coset graphs for low-density parity check codes: performance on the binary erasure channel." IET Communications 5, no. 5 (March 25, 2011): 719–27. http://dx.doi.org/10.1049/iet-com.2010.0220.

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43

Farooq, Muhammad Umar, Alexandre Graell i Amat, and Michael Lentmaier. "Threshold Computation for Spatially Coupled Turbo-Like Codes on the AWGN Channel." Entropy 23, no. 2 (February 19, 2021): 240. http://dx.doi.org/10.3390/e23020240.

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In this paper, we perform a belief propagation (BP) decoding threshold analysis of spatially coupled (SC) turbo-like codes (TCs) (SC-TCs) on the additive white Gaussian noise (AWGN) channel. We review Monte-Carlo density evolution (MC-DE) and efficient prediction methods, which determine the BP thresholds of SC-TCs over the AWGN channel. We demonstrate that instead of performing time-consuming MC-DE computations, the BP threshold of SC-TCs over the AWGN channel can be predicted very efficiently from their binary erasure channel (BEC) thresholds. From threshold results, we conjecture that the similarity of MC-DE and predicted thresholds is related to the threshold saturation capability as well as capacity-approaching maximum a posteriori (MAP) performance of an SC-TC ensemble.

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44

ZHAO, YULI, FRANCIS C. M. LAU, ZHILIANG ZHU, and HAI YU. "SCALE-FREE LUBY TRANSFORM CODES." International Journal of Bifurcation and Chaos 22, no. 04 (April 2012): 1250094. http://dx.doi.org/10.1142/s0218127412500940.

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This paper reports the characteristics and performance of a new type of Luby Transform codes, namely scale-free Luby Transform (SF-LT) codes. In the SF-LT codes, the degree of the encoded symbol follows a modified power-law distribution. Moreover, the complexity and decoding performance of SF-LT codes are compared with LT codes based on robust soliton degree distribution and LT codes based on suboptimal degree distribution. The results show that SF-LT codes outperform other LT codes in terms of the probability of successful decoding over an ideal channel and a binary erasure channel. Moreover, the encoding/decoding complexity for the SF-LT codes is superior.

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45

LEE, J. W. "Study of Turbo Codes and Decoding in Binary Erasure Channel Based on Stopping Set Analysis." IEICE Transactions on Communications E89-B, no. 4 (April 1, 2006): 1178–86. http://dx.doi.org/10.1093/ietcom/e89-b.4.1178.

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46

Sabag, Oron, Haim H. Permuter, and Navin Kashyap. "The Feedback Capacity of the Binary Erasure Channel With a No-Consecutive-Ones Input Constraint." IEEE Transactions on Information Theory 62, no. 1 (January 2016): 8–22. http://dx.doi.org/10.1109/tit.2015.2495239.

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47

Hager, Christian, Henry D. Pfister, Alexandre Graell i Amat, and Fredrik Brannstrom. "Density Evolution for Deterministic Generalized Product Codes on the Binary Erasure Channel at High Rates." IEEE Transactions on Information Theory 63, no. 7 (July 2017): 4357–78. http://dx.doi.org/10.1109/tit.2017.2689783.

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48

Johnson, Sarah J. "A Finite-Length Algorithm for LDPC Codes Without Repeated Edges on the Binary Erasure Channel." IEEE Transactions on Information Theory 55, no. 1 (January 2009): 27–32. http://dx.doi.org/10.1109/tit.2008.2008118.

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49

Sason, Igal, and Gil Wiechman. "Bounds on the Number of Iterations for Turbo-Like Ensembles Over the Binary Erasure Channel." IEEE Transactions on Information Theory 55, no. 6 (June 2009): 2602–17. http://dx.doi.org/10.1109/tit.2009.2018342.

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50

Paolini, Enrico, Marc P. C. Fossorier, and Marco Chiani. "Generalized and Doubly Generalized LDPC Codes With Random Component Codes for the Binary Erasure Channel." IEEE Transactions on Information Theory 56, no. 4 (April 2010): 1651–72. http://dx.doi.org/10.1109/tit.2010.2040938.

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