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Auteurs principaux: Guo, Jijin, Li, Lixin, Zheng, Yufeng, Zhao, Dongwei, Lin, Wensheng, Han, Zhu
Format: Preprint
Publié: 2026
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Accès en ligne:https://arxiv.org/abs/2605.04623
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author Guo, Jijin
Li, Lixin
Zheng, Yufeng
Zhao, Dongwei
Lin, Wensheng
Han, Zhu
author_facet Guo, Jijin
Li, Lixin
Zheng, Yufeng
Zhao, Dongwei
Lin, Wensheng
Han, Zhu
contents Cell-free integrated sensing and communication (ISAC) systems are facing the resource allocation challenges due to the deployment of access points (APs) and conflicting beamforming requirements between the communication and sensing functions. Unlike traditional ISAC architectures, the geographic distribution of APs introduces coordination complexity and resource-sharing conflicts that existing single-objective methods cannot adequately address. To address this challenge, we formulate an optimization problem for multi-AP cooperative beamforming that maximizes the sensing signal-to-clutter-plus-noise ratio (SCNR) under the communication rate constraints. The non-convex quadratically constrained quadratic program is transformed into a tractable convex semidefinite program via semidefinite relaxation, enabling efficient polynomial-time solutions and overcoming the local convergence limitations of traditional alternating optimization approaches. Simulation results demonstrate that the proposed approach achieves superior performance in both communication signal-to-interference-plus-noise ratio (SINR) and SCNR compared to existing schemes, confirming its effectiveness for balancing dual-functional objectives.
format Preprint
id arxiv_https___arxiv_org_abs_2605_04623
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Multi-AP Cooperative Beamforming for Cell-Free ISAC Networks: Balancing Communication SINR and Sensing SCNR
Guo, Jijin
Li, Lixin
Zheng, Yufeng
Zhao, Dongwei
Lin, Wensheng
Han, Zhu
Signal Processing
Cell-free integrated sensing and communication (ISAC) systems are facing the resource allocation challenges due to the deployment of access points (APs) and conflicting beamforming requirements between the communication and sensing functions. Unlike traditional ISAC architectures, the geographic distribution of APs introduces coordination complexity and resource-sharing conflicts that existing single-objective methods cannot adequately address. To address this challenge, we formulate an optimization problem for multi-AP cooperative beamforming that maximizes the sensing signal-to-clutter-plus-noise ratio (SCNR) under the communication rate constraints. The non-convex quadratically constrained quadratic program is transformed into a tractable convex semidefinite program via semidefinite relaxation, enabling efficient polynomial-time solutions and overcoming the local convergence limitations of traditional alternating optimization approaches. Simulation results demonstrate that the proposed approach achieves superior performance in both communication signal-to-interference-plus-noise ratio (SINR) and SCNR compared to existing schemes, confirming its effectiveness for balancing dual-functional objectives.
title Multi-AP Cooperative Beamforming for Cell-Free ISAC Networks: Balancing Communication SINR and Sensing SCNR
topic Signal Processing
url https://arxiv.org/abs/2605.04623