Optimal Movable Antenna Placement for Near-Field Wireless Sensing
This work addresses wireless sensing accuracy for near-field applications, presenting an incremental improvement with a computationally efficient solution.
This paper tackles the problem of optimal movable antenna placement for near-field wireless sensing by minimizing the worst-case squared position error bound, resulting in a three-point deployment strategy that outperforms conventional fixed arrays and matches exhaustive search benchmarks with negligible computational complexity.
Movable antennas (MAs) have emerged as a promising technology for wireless sensing by reconfiguring antenna positions to exploit additional spatial degrees of freedom (DoFs). This paper investigates a robust movable antenna placement strategy for near-field wireless sensing to minimize the worst-case squared position error bound (SPEB). By temporarily relaxing the minimum inter-element spacing constraint, we first establish the optimality of centro-symmetric antenna position distribution, which simplifies the identification of the worst-case source, locating it at the array broadside on the Rayleigh boundary. Moreover, by leveraging moment-based analysis with the Richter-Tchakaloff theorem, we derive a closed-form optimal solution with three points supported on the center and two edges of the array. Guided by this structural insight, we finally develop an efficient three-point discrete deployment strategy to ensure the minimum inter-element spacing. Simulations demonstrate that the proposed design consistently outperforms conventional fixed antenna arrays and matches the exhaustive search benchmark at negligible computational complexity.