Work

RL based Beamforming Optimization for 3D Pinching Antenna assisted ISAC Systems

Year: 2026

Type: preprint

Abstract: In this paper, a three-dimensional (3D) deployment scheme of pinching antenna array is proposed, aiming to enhances the performance of integrated sensing and communication (ISAC) systems. To fully realize the potential of 3D deployment, a joint antenna positioning, time allocation and transmit power optimization problem is formulated to maximize the sum communication rate with the constraints of target sensing rates and system energy. To solve the sum rate maximization problem, we propose a heterogeneous graph neural network based reinforcement learning (HGRL) algorithm. Simulation results prove that 3D deployment of pinching antenna array outperforms 1D and 2D counterparts in ISAC systems. Moreover, the proposed HGRL algorithm surpasses other baselines in both performance and convergence speed due to the advanced observation construction of the environment.

Source: arXiv (Cornell University)

DOI: 10.48550/arxiv.2601.20654

Authors: Gao, Qian, Zhong, Ruikang, Liu, Yue, Shin, Hyundong, Liu, Yuanwei

Institutions: Queen Mary University of London, Kyung Hee University, Macao Polytechnic University, University of Hong Kong

Topic: Radar Systems and Signal Processing

Subfield: Aerospace Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W7126089154

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