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The traditional communications transmit all the source data represented by bits, regardless of the content of source and the semantic information required by the receiver.
C. E. Shannon and W. Weaver, The Mathematical Theory of Communication . Champaign, Il, USA: Univ. Illinois Press, 1949
1949
Earlier work this paper cites.
R. Carnap and Y. Bar-Hillel, “An outline of a theory of semantic information,” Res. Lab. Electron., Massachusetts Inst. Technol., Cambridge, MA, USA, RLE Tech. Rep. 247, Oct. 1952
1952
Earlier work this paper cites.
D. A. Huffman, “A method for the construction of minimum-redundancy codes,” Proc. the IRE , vol. 40, no. 9, pp. 1098–1101, Sept. 1952
1952
Earlier work this paper cites.
M. Schuster and K. Paliwal, “Bidirectional recurrent neural networks,” IEEE Trans. Signal Process. , vol. 45, no. 11, pp. 2673–2681, Nov. 1997
1997
Earlier work this paper cites.
B. Bessette, R. Salami, R. Lefebvre, M. Jelinek, J. Rotola-Pukkila, J. Vainio, H. Mikkola, and K. Jarvinen, “The adaptive multirate wideband speech codec (AMR-WB),” IEEE Trans. Speech, Audio Process. , vol. 10, no. 8, pp. 620–636, Nov. 2002
2002
Earlier work this paper cites.
A. Graves, S. Fernández, F. Gomez, and J. Schmidhuber, “Connectionist temporal classification: Labelling unsegmented sequence data with recurrent neural networks,” in Proc. 23rd Int. Conf. Mach. Learning (ICML) , Pittsburgh, USA, Jun. 2006, pp. 369–376
2006
Earlier work this paper cites.
P. Basu, J. Bao, M. Dean, and J. Hendler, “Preserving quality of information by using semantic relationships,” Pervasive Mob. Comput. , vol. 11, pp. 188–202, Apr. 2014
2014
Earlier work this paper cites.
A. Balatsoukas-Stimming, M. B. Parizi, and A. Burg, “LLR-based successive cancellation list decoding of polar codes,” IEEE Trans. Signal Process. , vol. 63, no. 19, pp. 5165–5179, Jun. 2015
2015
Earlier work this paper cites.
D. Amodei, S. Ananthanarayanan, R. Anubhai, and etc., “Deep speech 2 : End-to-end speech recognition in english and mandarin,” in Proc. 33rd Int. Conf. Mach. Learning (ICML) , New York, New York, USA, Jun. 2016, pp. 173–182
2016
Cited alongside, same era.
T. O’shea and J. Hoydis, “An introduction to deep learning for the physical layer,” IEEE Trans. Cogn. Commun. Netw. , vol. 3, no. 4, pp. 563–575, Dec. 2017
2017
Cited alongside, same era.
S. Dörner, S. Cammerer, J. Hoydis, and S. t. Brink, “Deep learning based communication over the air,” IEEE J. Sel. Topics Signal Process. , vol. 12, no. 1, pp. 132–143, Feb. 2018
2018
Cited alongside, same era.
H. Ye, G. Y. Li, and B.-H. F. Juang, “Power of deep learning for channel estimation and signal detection in OFDM systems,” IEEE Wireless Commun. Lett. , vol. 7, no. 1, pp. 114–117, Feb. 2018
2018
Cited alongside, same era.
E. Bourtsoulatze, D. B. Kurka, and D. Gündüz, “Deep joint source-channel coding for wireless image transmission,” IEEE Trans. Cogn. Commun. Netw. , vol. 5, no. 3, pp. 567–579, Sept. 2019
2019
Later among the works it cites.
C.-H. Lee, J.-W. Lin, P.-H. Chen, and Y.-C. Chang, “Deep learning-constructed joint transmission-recognition for Internet of Things,” IEEE Access , vol. 7, pp. 76 547–76 561, Jun. 2019
2019
Later among the works it cites.
H. Ye, L. Liang, G. Y. Li, and B.-H. Juang, “Deep learning-based end-to-end wireless communication systems with conditional gans as unknown channels,” IEEE Trans. Wireless Commun. , vol. 19, no. 5, pp. 3133–3143, May. 2020
2020
Later among the works it cites.
D. B. Kurka and D. Gündüz, “DeepJSCC-f: Deep joint source-channel coding of images with feedback,” IEEE J. Sel. Areas Inf. Theory , vol. 1, no. 1, pp. 178–193, May. 2020
2020
Later among the works it cites.
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H. Sun, X. Chen, Q. Shi, M. Hong, X. Fu, and N. D. Sidiropoulos, “Learning to optimize: Training deep neural networks for interference management,” IEEE Trans. Signal Process. , vol. 66, no. 20, pp. 5438–5453, Oct. 2018
2018
Cited alongside, same era.
B. Güler, A. Yener, and A. Swami, “The semantic communication game,” IEEE Trans. Cogn. Commun. Netw. , vol. 4, no. 4, pp. 787–802, Dec. 2018
2018
Cited alongside, same era.
Z. Qin, H. Ye, G. Y. Li, and B.-H. F. Juang, “Deep learning in physical layer communications,” IEEE Wireless Commun. , vol. 26, no. 2, pp. 93–99, Apr. 2019
2019
Cited alongside, same era.
H. Ye, G. Y. Li, and B.-H. F. Juang, “Deep reinforcement learning based resource allocation for V2V communications,” IEEE Trans. Vehicular Technol. , vol. 68, no. 4, pp. 3163–3173, Apr. 2019
2019
Cited alongside, same era.
M. Jankowski, D. Gündüz, and K. Mikolajczyk, “Joint device-edge inference over wireless links with pruning,” in Proc. IEEE 21st Int. Workshop Signal Process. Adv. Wireless Commun. (SPAWC) , Atlanta, GA, USA, May. 2020, pp. 1–5
2020
Later among the works it cites.
H. Xie, Z. Qin, G. Y. Li, and B.-H. Juang, “Deep learning enabled semantic communication systems,” IEEE Trans. Signal Process. , vol. 69, pp. 2663–2675, Apr. 2021
2021
Closest in time.
H. Xie and Z. Qin, “A lite distributed semantic communication system for Internet of Things,” IEEE J. Sel. Areas Commun. , vol. 39, no. 1, pp. 142–153, Jan. 2021
2021
Closest in time.
Z. Weng and Z. Qin, “Semantic communication systems for speech transmission,” IEEE J. Sel. Areas Commun. , vol. 39, no. 8, pp. 2434–2444, Aug. 2021
2021
Closest in time.