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arXiv · 2507.19837

Feature Engineering for Wireless Communications and Networking: Concepts, Methodologies, and Applications

Jiacheng Wang·Changyuan Zhao·Zehui Xiong·Tao Xiang·Dusit Niyato·Xianbin Wang·Shiwen Mao·Dong In Kim
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Abstract

AI-enabled wireless communications have attracted tremendous research interest in recent years, particularly with the rise of novel paradigms such as low-altitude integrated sensing and communication (ISAC) networks. Within these systems, feature engineering plays a pivotal role by transforming raw wireless data into structured representations suitable for AI models. Hence, this paper offers a comprehensive investigation of feature engineering techniques in AI-driven wireless communications. Specifically, we begin with a detailed analysis of fundamental principles and methodologies of feature engineering. Next, we present its applications in wireless communication systems, with special emphasis on ISAC networks. Finally, we introduce a generative AI-based framework, which can reconstruct signal feature spectrum under malicious attacks in low-altitude ISAC networks. The case study shows that it can effectively reconstruct the signal spectrum, achieving an average structural similarity index improvement of 4%, thereby supporting downstream sensing and communication applications.

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Jiacheng Wang, Changyuan Zhao, Zehui Xiong, Tao Xiang, Dusit Niyato, Xianbin Wang, Shiwen Mao, Dong In Kim. 2025-07-26. Feature Engineering for Wireless Communications and Networking: Concepts, Methodologies, and Applications. https://arxiv.org/abs/2507.19837

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