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Journal articles on the topic 'Gilbert-Elliott channel'

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Author: Grafiati
Published: 4 June 2021
Last updated: 19 February 2022

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1

Polyanskiy, Yury, H. Vincent Poor, and Sergio Verdú. "Dispersion of the Gilbert-Elliott Channel." IEEE Transactions on Information Theory 57, no. 4 (April 2011): 1829–48. http://dx.doi.org/10.1109/tit.2011.2111070.

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2

Chen, J., and R. M. Tanner. "A Hybrid Coding Scheme for the Gilbert–Elliott Channel." IEEE Transactions on Communications 54, no. 9 (September 2006): 1703. http://dx.doi.org/10.1109/tcomm.2006.881270.

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3

Jinghu Chen and R. M. Tanner. "A hybrid coding scheme for the Gilbert-Elliott channel." IEEE Transactions on Communications 54, no. 10 (October 2006): 1787–96. http://dx.doi.org/10.1109/tcomm.2006.881365.

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4

Wilhelmsson, L., and L. B. Milstein. "On the effect of imperfect interleaving for the Gilbert-Elliott channel." IEEE Transactions on Communications 47, no. 5 (May 1999): 681–88. http://dx.doi.org/10.1109/26.768760.

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5

Sharma, G., A. A. Hassan, and A. Dholakia. "Performance evaluation of burst-error-correcting codes on a Gilbert-Elliott channel." IEEE Transactions on Communications 46, no. 7 (July 1998): 846–49. http://dx.doi.org/10.1109/26.701297.

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6

Eckford, A. W., F. R. Kschischang, and S. Pasupathy. "Analysis of Low-Density Parity-Check Codes for the Gilbert–Elliott Channel." IEEE Transactions on Information Theory 51, no. 11 (November 2005): 3872–89. http://dx.doi.org/10.1109/tit.2005.856934.

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7

Chen, Wentao, Junzheng Wang, Dawei Shi, and Ling Shi. "Event-Based State Estimation of Hidden Markov Models Through a Gilbert–Elliott Channel." IEEE Transactions on Automatic Control 62, no. 7 (July 2017): 3626–33. http://dx.doi.org/10.1109/tac.2017.2671037.

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8

KOBAYASHI, M., H. YAGI, T. MATSUSHIMA, and S. HIRASAWA. "Density Evolution Analysis of Robustness for LDPC Codes over the Gilbert-Elliott Channel." IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences E91-A, no. 10 (October 1, 2008): 2754–64. http://dx.doi.org/10.1093/ietfec/e91-a.10.2754.

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9

Hochwald, B. M., and P. R. Jelenkovic. "State learning and mixing in entropy of hidden Markov processes and the Gilbert-Elliott channel." IEEE Transactions on Information Theory 45, no. 1 (1999): 128–38. http://dx.doi.org/10.1109/18.746777.

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10

Chakraborty, S. S., M. Liinaharja, and P. Lindroos. "Analysis of adaptive GBN schemes in a Gilbert–Elliott channel and optimisation of system parameters." Computer Networks 48, no. 4 (July 2005): 683–95. http://dx.doi.org/10.1016/j.comnet.2004.11.007.

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11

Mushkin, M., and I. Bar-David. "Capacity and coding for the gilbert-elliott channels." IEEE Transactions on Information Theory 35, no. 6 (November 1989): 1277–90. http://dx.doi.org/10.1109/18.45284.

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12

Wu, Junfeng, Guodong Shi, Brian D. O. Anderson, and Karl Henrik Johansson. "Kalman Filtering Over Gilbert–Elliott Channels: Stability Conditions and Critical Curve." IEEE Transactions on Automatic Control 63, no. 4 (April 2018): 1003–17. http://dx.doi.org/10.1109/tac.2017.2732821.

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13

Sakakibara, K. "Performance analysis of the error-forecasting decoding for interleaved block codes on Gilbert-Elliott channels." IEEE Transactions on Communications 48, no. 3 (March 2000): 386–95. http://dx.doi.org/10.1109/26.837042.

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14

Li, Qi, Bo Shen, Zidong Wang, and Weiguo Sheng. "Recursive distributed filtering over sensor networks on Gilbert–Elliott channels: A dynamic event-triggered approach." Automatica 113 (March 2020): 108681. http://dx.doi.org/10.1016/j.automatica.2019.108681.

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15

Fang, Yong, and Jun Chen. "Decoding Polar Codes for a Generalized Gilbert-Elliott Channel with Unknown Parameter." IEEE Transactions on Communications, 2021, 1. http://dx.doi.org/10.1109/tcomm.2021.3095195.

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16

Donevski, Igor, Israel Leyva-Mayorga, Jimmy Jessen Nielsen, and Petar Popovski. "Performance Trade-Offs in Cyber–Physical Control Applications With Multi-Connectivity." Frontiers in Communications and Networks 2 (August 16, 2021). http://dx.doi.org/10.3389/frcmn.2021.712973.

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Abstract:
Modern communication devices are often equipped with multiple wireless communication interfaces with diverse characteristics. This enables exploiting a form of multi-connectivity known as interface diversity to provide path diversity with multiple communication interfaces. Interface diversity helps to combat the problems suffered by single-interface systems due to error bursts in the link, which are a consequence of temporal correlation in the wireless channel. The length of an error burst is an essential performance indicator for cyber–physical control applications with periodic traffic, as this defines the period in which the control link is unavailable. However, the available interfaces must be correctly orchestrated to achieve an adequate trade-off between latency, reliability, and energy consumption. This work investigates how the packet error statistics from different interfaces impact the overall latency–reliability characteristics and explores mechanisms to derive adequate interface diversity policies. For this, we model the optimization problem as a partially observable Markov decision process (POMDP), where the state of each interface is determined by a Gilbert–Elliott model whose parameters are estimated based on experimental measurement traces from LTE and Wi-Fi. Our results show that the POMDP approach provides an all-round adaptable solution, whose performance is only 0.1% below the absolute upper bound, dictated by the optimal policy under the impractical assumption of full observability.
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17

Mazumdar, Abhijit, Srinivasan Krishnaswamy, and Somanath Majhi. "H∞ optimal control over multiple Gilbert-Elliott type communication channels." IFAC Journal of Systems and Control, December 2020, 100134. http://dx.doi.org/10.1016/j.ifacsc.2020.100134.

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18

Ding, Derui, Zidong Wang, Qing-Long Han, and Xian-Ming Zhang. "Recursive Secure Filtering over Gilbert-Elliott Channels in Sensor Networks: The Distributed Case." IEEE Transactions on Signal and Information Processing over Networks, 2020, 1. http://dx.doi.org/10.1109/tsipn.2020.3046220.

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19

"Packet Switching Network in Throughput Rate Less Code." International Journal of Innovative Technology and Exploring Engineering 8, no. 9S3 (August 23, 2019): 818–21. http://dx.doi.org/10.35940/ijitee.i3171.0789s319.

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We consider show movement and a discrete-time lining model, where the quantities of bundle landings over various timeslots are autonomous and indistinguishably disseminated and the parcel length is an altered worth. The transmission begins when there are more than bundles holding up in the approaching line proposed for every one of the collectors. The telecast stations are displayed by Markov balanced bundle eradication stations, where the parcel can either be deleted or effectively gotten and for every beneficiary the present station state circulation relies on upon the station states in past parcel transmissions. Gilbert–Elliott deletion channels, we can give a lower bound on the greatest achievable throughput
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