Data-Driven Next-Generation Wireless Networking: Embracing AI for Performance and Security
Data-Driven Next-Generation Wireless Networking: Embracing AI for Performance and Security
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DOI：
10.1109/icccn58024.2023.10230189
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发表时间：
2023-06
期刊：
影响因子：
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通讯作者：
Jiahao Xue;Zhe Qu;Shangqing Zhao;Yao-Hong Liu;Zhuo Lu
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文献类型：
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作者：
Jiahao Xue;Zhe Qu;Shangqing Zhao;Yao-Hong Liu;Zhuo Lu
物联网（IoT）、5G和下一代蜂窝系统等新型网络架构对未来无线网络的设计提出了新的挑战，这些挑战包括超高数据速率、海量数据处理、智能设计、低成本部署、动态环境下的可靠性和安全性。作为当今最有前途的技术之一，人工智能（AI）被提倡为无线网络设计提供数据驱动的范例。在本文中，我们有动机回顾现有的人工智能技术及其在全无线网络协议栈中的应用，以提高网络性能和安全性。我们的目标是总结当前使用人工智能从物理层到应用层增强无线网络的动机、挑战和方法，并为未来数据驱动的无线网络创建新的支持人工智能的算法、机制、协议和系统设计。
New network architectures, such as the Internet of Things (IoT), 5G, and next-generation (NextG) cellular systems, put forward emerging challenges to the design of future wireless networks toward ultra-high data rate, massive data processing, smart designs, low-cost deployment, reliability and security in dynamic environments. As one of the most promising techniques today, artificial intelligence (AI) is advocated to enable a data-driven paradigm for wireless network design. In this paper, we are motivated to review existing AI techniques and their applications for the full wireless network protocol stack toward improving network performance and security. Our goal is to summarize the current motivation, challenges, and methodology of using AI to enhance wireless networking from the physical to the application layer, and shed light on creating new AI-enabled algorithms, mechanisms, protocols, and system designs for future data-driven wireless networking.