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arXiv · 2512.04802

Movable Antenna Assisted Flexible Beamforming for Integrated Sensing and Communication in Vehicular Networks

Luyang Sun·Zhiqing Wei·Haotian Liu·Kan Yu·Zhendong Li·Zhiyong Feng
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Abstract

Integrated sensing and communication (ISAC) has been recognized as a key technology in sixth-generation wireless networks, and the additional spatial degrees of freedom obtained by movable antenna (MA) technology can significantly improve the performance of ISAC systems. This paper considers an ISAC-assisted vehicle-to-infrastructure (V2I) network, where extended kalman filter-based prediction is combined with real-time optimization to jointly optimize transmit antenna positions and beamforming and power allocation vectors in dynamic environments. We propose two algorithms: a preprocessing-schur complement-projected gradient ascent algorithm for scenarios without sensing quality of service (QoS) constraints, which explores the potential range of sensing performance to provide reference and warm-starting for subsequent constrained optimization; and a heuristic reflective projected dynamic particle swarm optimization algorithm for sensing QoS-constrained scenarios, which achieves substantial performance gains under non-convex constraints with a small number of iterations. Simulation results demonstrate that these approaches enhance both the communication sum-rate and the lower of the Cram\'er-Rao lower bound of motion parameter estimation, validating the effectiveness of MA-assisted beamforming in dynamic V2I ISAC networks.

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Luyang Sun, Zhiqing Wei, Haotian Liu, Kan Yu, Zhendong Li, Zhiyong Feng. 2025-12-04. Movable Antenna Assisted Flexible Beamforming for Integrated Sensing and Communication in Vehicular Networks. https://arxiv.org/abs/2512.04802

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