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Semantic-Forward Relaying: A Novel Framework Towards 6G Cooperative Communications
Published 12 Oct 2023 in cs.NI, cs.IT, cs.LG, eess.SP, and math.IT | (2310.07987v2)
Abstract: This letter proposes a novel relaying framework, semantic-forward (SF), for cooperative communications towards the sixth-generation (6G) wireless networks. The SF relay extracts and transmits the semantic features, which reduces forwarding payload, and also improves the network robustness against intra-link errors. Based on the theoretical basis for cooperative communications with side information and the turbo principle, we design a joint source-channel coding algorithm to iteratively exchange the extrinsic information for enhancing the decoding gains at the destination. Surprisingly, simulation results indicate that even in bad channel conditions, SF relaying can still effectively improve the recovered information quality.
- C.-X. Wang, X. You, X. Gao, X. Zhu, Z. Li, C. Zhang, H. Wang, Y. Huang, Y. Chen, H. Haas, J. S. Thompson, E. G. Larsson, M. D. Renzo, W. Tong, P. Zhu, X. Shen, H. V. Poor, and L. Hanzo, “On the road to 6G: Visions, requirements, key technologies, and testbeds,” IEEE Communications Surveys & Tutorials, vol. 25, no. 2, pp. 905–974, Second quarter 2023.
- W. Yang, H. Du, Z. Q. Liew, W. Y. B. Lim, Z. Xiong, D. Niyato, X. Chi, X. Shen, and C. Miao, “Semantic communications for future internet: Fundamentals, applications, and challenges,” IEEE Communications Surveys & Tutorials, vol. 25, no. 1, pp. 213–250, First quarter 2023.
- H. Zhang, S. Shao, M. Tao, X. Bi, and K. B. Letaief, “Deep learning-enabled semantic communication systems with task-unaware transmitter and dynamic data,” IEEE Journal on Selected Areas in Communications, vol. 41, no. 1, pp. 170–185, Jan. 2023.
- H. Feng, Y. Yang, and Z. Han, “SCAI: Scalable AI generative content for enhanced semantic communication,” in IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Seoul, Korea, Apr. 2024, invited.
- G. Kramer, M. Gastpar, and P. Gupta, “Cooperative strategies and capacity theorems for relay networks,” IEEE Transactions on Information Theory, vol. 51, no. 9, pp. 3037–3063, Sep. 2005.
- T. Cover and A. El Gamal, “Capacity theorems for the relay channel,” IEEE Transactions on Information Theory, vol. 25, no. 5, pp. 572–584, Sep. 1979.
- W. Lin, S. Qian, and T. Matsumoto, “Lossy-forward relaying for lossy communications: Rate-distortion and outage probability analyses,” IEEE Transactions on Wireless Communications, vol. 18, no. 8, pp. 3974–3986, Aug. 2019.
- X. Luo, B. Yin, Z. Chen, B. Xia, and J. Wang, “Autoencoder-based semantic communication systems with relay channels,” in IEEE International Conference on Communications (ICC) Workshops, Seoul, Republic of Korea, May 2022, pp. 711–716.
- C. Berrou and A. Glavieux, “Near optimum error correcting coding and decoding: Turbo-codes,” IEEE Transactions on Communications, vol. 44, no. 10, pp. 1261–1271, Oct. 1996.
- A. Wyner and J. Ziv, “The rate-distortion function for source coding with side information at the decoder,” IEEE Transactions on information Theory, vol. 22, no. 1, pp. 1–10, Jan. 1976.
- G. Xin, P. Fan, and K. B. Letaief, “Semantic information theory: Recent advances and future challenges,” Preprints, October 2023. [Online]. Available: https://doi.org/10.20944/preprints202310.1208.v1
- J. Garcia-Frias and Y. Zhao, “Near-Shannon/Slepian-Wolf performance for unknown correlated sources over AWGN channels,” IEEE Transactions on Communications, vol. 53, no. 4, pp. 555–559, Apr. 2005.
- X. Zhou, X. He, K. Anwar, and T. Matsumoto, “GREAT-CEO: larGe scale distRibuted dEcision mAking Technique for wireless Chief Executive Officer problems,” IEICE Transactions on Communications, vol. 95, no. 12, pp. 3654–3662, Dec. 2012.
- “Semantic-forward relaying,” GitHub, Oct. 2023. [Online]. Available: https://github.com/linwest/Semantic_Forward
- A. Krizhevsky, “Learning multiple layers of features from tiny images,” Toronto, ON, Canada, 2009. [Online]. Available: https://www.cs.toronto.edu/~kriz/learning-features-2009-TR.pdf
- R. Gallager, “Low-density parity-check codes,” IRE Transactions on Information Theory, vol. 8, no. 1, pp. 21–28, Jan. 1962.
- D. P. Kingma and J. Ba, “Adam: A method for stochastic optimization,” arXiv preprint arXiv:1412.6980, 2014.
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