Fluid antenna arrays improve combined communication and sensing accuracy
Fluid Antenna Array-Enabled Near-Field ISAC: Joint Port Position Optimization and Transmit Beamforming Design
Information Theory
Summary
Wireless systems can use special antennas that change shape and position to better communicate and sense their surroundings at the same time. The authors show how to arrange these antennas and send signals to make it easier to find objects and their movements near the antennas while keeping good communication with users. They use math tools to measure the best accuracy possible and create a method to find the antenna positions and signal patterns that work best together. Their tests show this system improves sensing accuracy without making the process too complex.
What this means in practice
- •For wireless network engineers: Improve near-field target detection in communication systems by jointly optimizing antenna element positions and signal patterns in fluid antenna arrays.
- •For automotive radar system designers: Enhance vehicle sensing accuracy for range and angle estimation with adaptable antenna configurations supporting integrated communication and sensing.
Authors
Wangqi Shi, Zhentian Zhang, Hao Jiang, Zaichen Zhang, Kin-Fai Tong
Abstract
Fluid antenna systems (FASs) have shown that activating a single port from a densely packed antenna array can yield spatial diversity comparable to that of tens of independent antennas, a property that has substantially improved communication reliability and efficiency. The fluid antenna array (FAA) extends this concept to multi-port configurations while avoiding complex multi-dimensional spatial correlation, and offers significant geometrical flexibility under a finite aperture and a limited port budget. These attributes motivate environment-adaptive array geometry for sensing in integrated sensing and communication (ISAC) systems. Although this flexibility enables adaptive array geometries that exploit near-field distance-angle information, improving multi-parameter target estimation under communication and deployment constraints remains challenging. In this paper, we propose a planar FAA-assisted near-field ISAC framework for multiuser communication and target sensing. Specifically, we derive the Fisher information matrix (FIM) and the corresponding Cramér-Rao bound (CRB) for the joint estimation of target range, zenith angle, azimuth angle, and radial velocity. Based on the derived CRB, we jointly optimize the FAA port positions and transmit beamforming to improve sensing accuracy while satisfying communication signal-to-interference-plus-noise ratio (SINR), transmit power, and physical deployment constraints. To solve the resulting non-convex problem, we develop a two-stage alternating optimization algorithm, in which transmit beamforming is optimized through semidefinite relaxation (SDR), while FAA port positions are successively optimized through discrete search and continuous refinement. Simulation results indicate that the proposed algorithm achieves favorable sensing performance while maintaining a reasonable computational cost.