References
[1] KHAN W Z, REHMAN M H, ZANGOTI H M, et al. Industrial
Internet of things: Recent advances, enabling technologies and
open challenges. Computers and Electrical Engineering, 2020,
81(1): Article 106522.
[2] SISINNI E, SAIFULLAH A, HAN S, et al. Industrial Internet of
things: Challenges, opportunities, and directions. IEEE
Transactions on Industrial Informatics, 2018, 14(11): 4724 -
4734.
[3] QIU T, ZHANG Y S, QIAO D J, et al. A robust time
synchronization scheme for industrial Internet of things. IEEE
Transactions on Industrial Informatics, 2018, 14(8): 3570 -
3580.
[4] GUNGOR V C, HANCKE G P. Industrial wireless sensor
networks: Challenges, design principles, and technical
approaches. IEEE Transactions on Industrial Electronics, 2009,
56(10): 4258 - 4265.
[5] CHENG J F, CHEN W H, TAO F, et al. Industrial IoT in 5G
environment towards smart manufacturing. Journal of Industrial
Information Integration, 2018, 10(2): 10 - 19.
[6] ZHANG P, NIU K, TIAN H, et al. Technology prospect of 6G
mobile communications. Journal on Communications, 2019,
40(1): 141 - 148 (in Chinese).
[7] ZHANG P, ZHANG J H, QI Q, et al. Ubiquitous-X:
Constructing the future 6G networks. Scientia Sinica:
Informationis, 2020, 50(6): 913 - 930 (in Chinese).
[8] CHEN B T, WAN J F, CELESTI A, et al. Edge computing in
IoT-based manufacturing. IEEE Communications Magazine, 2018,
56(9): 103 - 109.
[9] AAZAM M, ZEADALLY S, HARRAS K A. Deploying fog
computing in industrial Internet of things and industry 4. 0. IEEE
Transactions on Industrial Informatics, 2018, 14(10): 4674 -
4682.
[10] ZHANG P, XU W, GAO H, et al. Toward wisdom-evolutionary
and primitive-concise 6G: A new paradigm of semantic
communication networks. Engineering, 2021, DOI: 10.1016/j.eng.2021.11.003.
[11] NILSSON J, SANDIN F. Semantic interoperability in industry
4. 0: Survey of recent developments and outlook. Proceeding of
the IEEE 16th International Conference on Industrial Informatics
(INDIN'18), 2018, Jul 18 - 20, Porto, Portugal. Piscataway,
NJ, USA: IEEE, 2018: 127 - 132.
[12] SHANNON C E. A mathematical theory of communication. The
Bell System Technical Journal, 1948, 27(3): 379 - 423.
[13] WEAVER W. Recent contributions to the mathematical theory of
communication. ETC: A Review of General Semantics, 1953,
10(4): 261 - 281.
[14] WU W L. Generalized information source and generalized
entropy. Journal of Beijing University of Posts and
Telecommunications, 1982, 5(1): 29 - 41 (in Chinese).
[15] ZHONG Y X. A theory of semantic information. China
Communications, 2017, 14(1): 1 - 17.
[16] DE LUCA A, TERMINI S. A definition of a non-probabilistic
entropy in the setting of fuzzy sets. Information and Control,
1972, 20(4): 301 - 312.
[17] DE LUCA A, TERMINI S. Entropy of L-fuzzy sets. Information
and Control, 1974, 24(1): 55 - 73.
[18] LI T, SAHU A K, TALWALKAR A, et al. Federated learning:
Challenges, methods, and future directions. IEEE Signal
Processing Magazine, 2020, 37(3): 50 - 60.
[19] XIE H Q, QIN Z J, LI G Y, et al. Deep learning enabled
semantic communication systems. IEEE Transactions on Signal
Processing, 2021, 69: 2663 - 2675.
[20] XIE H Q, QIN Z J. A lite distributed semantic communication
system for Internet of things. IEEE Journal on Selected Areas in
Communications, 2021, 39(1): 142 - 153.
[21] ZHANG G P. Time series forecasting using a hybrid ARIMA and
neural network model. Neurocomputing, 2003, 50(1): 159 -
175.
[22] WEI W W S. Time series analysis. The Oxford Handbook of
Quantitative Methods in Psychology. Oxford, UK: Oxford
University Press, 2006: 458 - 485.
[23] BOURTSOULATZE E, KURKA D B, GUNDUZ D. Deep joint
source-channel coding for wireless image transmission. IEEE
Transactions on Cognitive Communications and Networking,
2019, 5(3): 567 - 579.
[24] KURKA D B, GUNDUZ D. DeepJSCC-f: Deep joint source-channel coding of images with feedback. IEEE Journal on
Selected Areas in Information Theory, 2020, 1(1): 178 - 193.
[25] ZHAI F, EISENBERG Y, KATSAGGELOS A K. Joint source-channel coding for video communications. BOVIK A ed.
Handbook of Image and Video Processing, 2nd ed. Amsterdam,
Netherlands: Elsevier Science, 2005: 1065 - 1082.
[26] BALLE J, LAPARRA V, SIMONCELLI E P. End-to-end
optimized image compression. Proceeding of the 5th International
Conference on Learning Representations (ICLR'17), 2017, Apr
24 - 26, Toulon, France. 2017.
[27] WANG Z, SIMONCELLI E P, BOVIK A C. Multiscale structural
similarity for image quality assessment. Proceeding of the 37th
Asilomar Conference on Signals, Systems and Computers, 2003,
Nov 9 - 12, Pacific Grove, CA, USA. Piscataway, NJ, USA:
IEEE, 2003: 1398 - 1402.
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