{"ID":2833000,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2512.04802","arxiv_id":"2512.04802","title":"Movable Antenna Assisted Flexible Beamforming for Integrated Sensing and Communication in Vehicular Networks","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 Cramér-Rao lower bound of motion parameter estimation, validating the effectiveness of MA-assisted beamforming in dynamic V2I ISAC networks.","short_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...","url_abs":"https://arxiv.org/abs/2512.04802","url_pdf":"https://arxiv.org/pdf/2512.04802v1","authors":"[\"Luyang Sun\",\"Zhiqing Wei\",\"Haotian Liu\",\"Kan Yu\",\"Zhendong Li\",\"Zhiyong Feng\"]","published":"2025-12-04T13:54:37Z","proceeding":"eess.SP","tasks":"[\"eess.SP\"]","methods":"[]","has_code":false}