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arXiv 2302.14702eess.SPcs.AIcs.ITmath.IT
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干扰下深度学习赋能的文本语义通信的性能极限

Performance Limits of a Deep Learning-Enabled Text Semantic Communication under Interference

École de Technologie Supérieure (ETS)(高等技术学院);National Institute of Standards and Technology (NIST)(美国国家标准与技术研究院);Virginia Tech(弗吉尼亚理工大学);Lebanese American University(黎巴嫩美国大学);University of Oulu(奥卢大学)

Tilahun M. Getu, Walid Saad, Georges Kaddoum, Mehdi Bennis

AI总结:

本文研究多干扰源射频干扰下DeepSC文本语义通信的性能极限,推导其中断概率下界,并提出基于终身深度学习的抗干扰鲁棒语义通信系统。

摘要:

尽管深度学习(DL)赋能的语义通信(SemCom)通过最小化无关信息传输——从而最小化功耗、带宽消耗和传输时延——已成为6G的关键使能技术,但其优势可能受到射频干扰(RFI)的限制,因为RFI会产生显著的语义噪声。这种语义噪声的影响可以通过抗干扰且鲁棒的(IR$^2$)SemCom设计来缓解,但目前尚无此类设计。为促进IR$^2$ SemCom的基础研究,本文在(多干扰源)RFI存在的情况下,研究了名为DeepSC的主流文本SemCom系统的性能极限。通过引入一个有原则的SemCom概率框架,我们证明当(多干扰源)RFI的功率变得非常大时,DeepSC会产生语义上不相关的句子。我们还推导了DeepSC在多干扰源RFI下的实际极限及其中断概率的下界,并提出了一种(通用的)基于终身DL的IR$^2$ SemCom系统。我们通过仿真和计算机实验验证了所推导的极限,实验结果也证实了DeepSC在面对使用RFI的无线攻击时的脆弱性。

英文摘要:

Although deep learning (DL)-enabled semantic communication (SemCom) has emerged as a 6G enabler by minimizing irrelevant information transmission -- minimizing power usage, bandwidth consumption, and transmission delay, its benefits can be limited by radio frequency interference (RFI) that causes substantial semantic noise. Such semantic noise's impact can be alleviated using an interference-resistant and robust (IR$^2$) SemCom design, though no such design exists yet. To stimulate fundamental research on IR2 SemCom, the performance limits of a popular text SemCom system named DeepSC are studied in the presence of (multi-interferer) RFI. By introducing a principled probabilistic framework for SemCom, we show that DeepSC produces semantically irrelevant sentences as the power of (multi-interferer) RFI gets very large. We also derive DeepSC's practical limits and a lower bound on its outage probability under multi-interferer RFI, and propose a (generic) lifelong DL-based IR$^2$ SemCom system. We corroborate the derived limits with simulations and computer experiments, which also affirm the vulnerability of DeepSC to a wireless attack using RFI.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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