Earticle

초록

영어

This paper presents an AI-empowered fluid antenna system (FAS) framework to enhance the robustness of positioning, navigation, and timing (PNT) in future sixthgeneration (6G) satellite terrestrial networks. The FAS employs movable or reconfigurable liquid-metal antennas that dynamically alter geometry and port position to exploit spatial diversity and mitigate multipath fading. Building on verified FAS fundamentals, exposure-constrained optimization, and a fluid-antenna multiple access (FAMA) model, a lightweight AI controller is proposed for real-time port selection using carrierto- noise ratio, signal-to-noise ratio, and Doppler-shift features. The proposed framework integrates safety constraints and enables adaptive port hopping for seamless hybrid global navigation satellite system (GNSS) and 6G PNT operation. Recent research on movable-antenna integrated sensing and communication (ISAC) and received-signal-strength-indicatorbased (RSSI-based) FAS positioning demonstrates the feasibility of AI-driven FAS for high-precision timing and localization in next-generation networks.

목차

Abstract
I. INTRODUCTION
II. BACKGROUND AND RELATED WORK
A. Modeling and Correlation Characteristics
B. Maintaining the Integrity of the Specifications
C. AI-Driven Selection and Access
D. FAS in ISAC and PNT Domains
III. SYSTEM MODEL AND AI CONTROL
A. Two-Stage Selection Process
B. Timing Error and Correlation
C. Computation and Power Budget
IV. PERFORMANCE INSIGHTS AND DISCUSSION
V. IMPLEMENTATION AND FUTURE WORK
VI. CONCLUSION
REFERENCES

저자

• Mim Md Mahdir [ School of Computer Science and Engineering Chung-Ang University Seoul, South Korea ]
• Bumshik Lee [ Department of Energy Engineering KENTECH Naju, South Korea ]
• Wooyeol Choi [ School of Computer Science and Engineering Chung-Ang University Seoul, South Korea ]

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