Intelligent Flexible Position Antenna Systems for Networking: A Survey
Artikel i vetenskaplig tidskrift, 2025

Flexible position antenna (FLA) is a promising technology which can reconstruct the channel mapping by adjusting the parameters of antennas such as position, pattern and polarization, thereby adapting to the time-varying environments. Such a paradigm shift in antenna technology is expected to enable next generation networks to achieve multiple enhancements in data transmission rate, latency, and connectivity density, which supports a plethora of emerging applications. However, conventional FLA systems rely on accurate mathematical models, which suffer from high computational complexity. Thus, it is difficult to adapt to the dynamic environments due to the computation delay. Thanks to its powerful feature extraction and decision-making capabilities, artificial intelligence (AI) has emerged as an effective solution to these challenges. Thus, intelligent FLA has attracted widespread academic attention. This paper provides a comprehensive review of intelligent FLA systems for networking. We first review the fundamental principle and implementation architectures of FLA, including reconfigurable antenna, movable antenna, fluid antenna and pinching antenna, and then we introduce some key AI techniques. Building on this, we discuss the motivation and advantages of introducing AI into FLA systems and investigate the applications of intelligent FLA in various types of networks. Finally, we delineate the challenges and future directions of intelligent FLA systems for networking.

pinching antenna

movable antenna

reconfigurable antenna

Artificial intelligence

networking

fluid antenna

flexible position antenna

Författare

Xianglin Yu

Dalian University of Technology

Jiacheng Wang

School of Computer Science and Engineering

Rose Qingyang Hu

College of Engineering

Dong In Kim

Sungkyunkwan University

Naofal Al-Dhahir

University of Texas at Dallas

Henk Wymeersch

Chalmers, Elektroteknik, Kommunikation, Antenner och Optiska Nätverk

Nan Zhao

Dalian University of Technology

IEEE Transactions on Network Science and Engineering

23274697 (eISSN)

Vol. In Press

Ämneskategorier (SSIF 2025)

Kommunikationssystem

DOI

10.1109/TNSE.2025.3626312

Mer information

Senast uppdaterat

2025-11-21