Robust Resource Allocation for Pinching-Antenna Systems under Imperfect CSI

TL;DR

This paper proposes a robust resource allocation method for pinching-antenna systems that accounts for uncertain user locations, optimizing antenna placement and power allocation to improve performance in high-frequency wireless systems.

Contribution

It introduces a novel robust resource allocation framework for pinching-antenna systems with uncertain user positions, including an optimal placement strategy and power control.

Findings

The proposed scheme reduces total transmit power compared to fixed-antenna systems.

The PSO-based antenna placement effectively handles location uncertainty.

Simulation results confirm improved system performance under uncertain conditions.

Abstract

Pinching-antenna technology has lately showcased its promising capability for reconfiguring wireless propagation environments, especially in high-frequency communication systems like millimeter-wave and terahertz bands. By dynamically placing the antenna over a dielectric waveguide, line-of-sight (LoS) connections can be made to significantly improve system performance. Although recent research have illustrated the advantages of pinching-antenna-assisted designs, they mainly presuppose complete knowledge of user locations -- an impractical assumption in real-world systems. To address this issue, the robust resource allocation in a multi-user pinching antenna downlink system with uncertain user positions is investigated, aiming to minimize total transmit power while satisfying individual outage probability constraints. First, we address the single-user case, deriving the optimal pinching antenna position and obtaining the corresponding power allocation using a bisection method combined with geometric analysis. We then extend this solution to the multi-user case. In this case, we optimize the pinching antenna position using a particle swarm optimization (PSO) algorithm to handle the resulting non-convex and non-differentiable optimization problem. Simulation results demonstrate that the proposed scheme outperforms conventional fixed-antenna systems and validate the effectiveness of the PSO-based antenna placement strategy under location uncertainty.