Scalable FAS: A New Paradigm for Array Signal Processing

TL;DR

This paper presents a scalable fluid antenna system that dynamically adjusts its aperture to improve source localization accuracy in complex environments, eliminating the need for traditional assumptions and signal separation.

Contribution

It introduces a novel SFAS framework with a two-stage ESG-based localization strategy, enabling high-precision localization without field-specific assumptions or signal isolation.

Findings

Superior localization accuracy in simulations

Enhanced robustness to various source types

Improved computational efficiency

Abstract

Most existing antenna array-based source localization methods rely on fixed-position arrays (FPAs) and strict assumptions about source field conditions (near-field or far-field), which limits their effectiveness in complex, dynamic real-world scenarios where high-precision localization is required. In contrast, this paper introduces a novel scalable fluid antenna system (SFAS) that can dynamically adjust its aperture configuration to optimize performance for different localization tasks. Within this framework, we develop a two-stage source localization strategy based on the exact spatial geometry (ESG) model: the first stage uses a compact aperture configuration for initial direction-of-arrival (DOA) estimation, while the second stage employs an expanded aperture for enhanced DOA and range estimation. The proposed approach eliminates the traditional need for signal separation or isolation to classify source types and enables a single SFAS array to achieve high localization accuracy without field-specific assumptions, model simplifications, or approximations, representing a new paradigm in array-based source localization. Extensive simulations demonstrate the superiority of the proposed method in terms of localization accuracy, computational efficiency, and robustness to different source types.