Advancing Fluid Antenna-Assisted Non-Terrestrial Networks in 6G and Beyond: Fundamentals, State of the Art, and Future Directions
Tianheng Xu, Runke Fan, Jie Zhu, Pei Peng, Xianfu Chen, Qingqing Wu, Ming Jiang, Celimuge Wu, Dusit Niyato, Kai-Kit Wong
TL;DR
This paper offers a comprehensive review of fluid antenna (FA) technology integrated with non-terrestrial networks (NTNs) for 6G and beyond. It analyzes NTN fundamentals, FA hardware implementations (liquid-based, pixel-array, and mechanically movable antennas), and FA-driven channel modeling and CSI estimation, emphasizing AI-based approaches to cope with dynamic channels. The work surveys joint FA–NTN optimizations across hovering/mobile UAVs and satellites, and discusses compatibility with CF-mMIMO, FD, NGMA, and RIS, as well as intelligent function integration (MEC, AirComp/FL, ISAC) and security (PLS, covert) considerations. It also outlines future directions, including AI-driven management, high-frequency and near-field operations, and ISCC, aiming to unlock broader NTN applications with FA-enabled adaptability and efficiency.
Abstract
With the surging demand for ultra-reliable, low-latency, and ubiquitous connectivity in Sixth-Generation (6G) networks, Non-Terrestrial Networks (NTNs) emerge as a key complement to terrestrial networks by offering flexible access and global coverage. Despite the significant potential, NTNs still face critical challenges, including dynamic propagation environments, energy constraints, and dense interference. As a key 6G technology, Fluid Antennas (FAs) can reshape wireless channels by reconfiguring radiating elements within a limited space, such as their positions and rotations, to provide higher channel diversity and multiplexing gains. Compared to fixed-position antennas, FAs can present a promising integration path for NTNs to mitigate dynamic channel fading and optimize resource allocation. This paper provides a comprehensive review of FA-assisted NTNs. We begin with a brief overview of the classical structure and limitations of existing NTNs, the fundamentals and advantages of FAs, and the basic principles of FA-assisted NTNs. We then investigate the joint optimization solutions, detailing the adjustments of FA configurations, NTN platform motion modes, and resource allocations. We also discuss the combination with other emerging technologies and explore FA-assisted NTNs as a novel network architecture for intelligent function integrations. Furthermore, we delve into the physical layer security and covert communication in FA-assisted NTNs. Finally, we highlight the potential future directions to empower broader applications of FA-assisted NTNs.
