Cell-Free Joint Beamforming and AP–User/Target AssociationOptimization for Integrated Sensing and Communication

FANG Zhiyu; XIA Xiaochen; XU Kui; WEI Chen; XIE Wei; YE Zilü

doi:10.11999/JEIT250574

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FANG Zhiyu, XIA Xiaochen, XU Kui, WEI Chen, XIE Wei, YE Zilü. Cell-Free Joint Beamforming and AP–User/Target AssociationOptimization for Integrated Sensing and Communication[J]. Journal of Electronics & Information Technology. doi: 10.11999/JEIT250574

Citation:

FANG Zhiyu, XIA Xiaochen, XU Kui, WEI Chen, XIE Wei, YE Zilü. Cell-Free Joint Beamforming and AP–User/Target AssociationOptimization for Integrated Sensing and Communication[J]. Journal of Electronics & Information Technology. doi: 10.11999/JEIT250574

Citation:

FANG Zhiyu, XIA Xiaochen, XU Kui, WEI Chen, XIE Wei, YE Zilü. Cell-Free Joint Beamforming and AP–User/Target AssociationOptimization for Integrated Sensing and Communication[J]. Journal of Electronics & Information Technology. doi: 10.11999/JEIT250574

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Cell-Free Joint Beamforming and AP–User/Target AssociationOptimization for Integrated Sensing and Communication

doi: 10.11999/JEIT250574 cstr: 32379.14.JEIT250574

College of Communication Engineering, Army Engineering University of PLA, Nanjing 210007, China

Funds: The National Natural Science Foundation of China(62271503, 62071485), The Natural Science Foundation of Jiangsu Province of China (BK20231485, BK20201334, BK20200579)

Received Date: 2025-06-20
Accepted Date: 2026-03-16
Rev Recd Date: 2026-03-13

Available Online: 2026-04-06

Abstract

Abstract

Objective Integrated Sensing And Communication (ISAC) is a key technology for Sixth-Generation (6G) networks. The cell-free architecture is a promising regional coverage paradigm for 6G. Cooperation among Access Points (APs) mitigates coverage imbalance, interference, and capacity limitations in conventional cellular systems, while enabling communication and sensing services for low-altitude targets with wide-area continuous coverage. However, existing studies on cell-free systems often rely on statistical channel models, which fail to capture realistic propagation characteristics in complex environments. The global Channel State Information (CSI) required for transmission optimization is difficult to obtain, and instantaneous CSI cannot be guaranteed due to the high mobility of low-altitude targets. To address these issues, a joint beamforming and AP–user/target association optimization method based on a Binary Radio Map (BRM) is proposed. The environmental information provided by the BRM is used to predict channels between APs and users/targets, thereby providing global channel information for joint optimization. On this basis, an ISAC satisfaction-based optimization model is constructed, and an iterative optimization algorithm for beamforming design and AP–user/target association is developed using a genetic algorithm. Methods First, the channels between APs and users/targets are predicted using environmental information derived from the BRM. An ISAC satisfaction-based optimization model is then established to unify communication and sensing performance. Due to the coupling between communication and sensing and the non-convex nature of the problem, the optimization problem is decomposed into two subproblems corresponding to communication and sensing beamforming. In each iteration, the beamforming design is reformulated as a Second-Order Cone Program (SOCP) to obtain beamforming matrices that maximize the satisfaction function. An iterative solution algorithm is applied to compute the communication and sensing beamforming matrices efficiently. Subsequently, based on the optimized satisfaction function, an AP–user/target association optimization method is designed using a genetic algorithm. Results and Discussions Simulation results verify the effectiveness of the BRM-assisted channel prediction and association optimization method. Compared with the conventional AP association method based on the shortest path, the proposed approach reduces the required transmission power by approximately 5 dBm while achieving higher user/target satisfaction (Fig. 7). As the transmission power increases, the satisfaction of users/targets gradually improves and approaches 1. In contrast, under the conventional scheme, a large gap remains between the maximum and minimum satisfaction values at the same transmission power (Fig. 8). When the transmission power is 40 dBm, the proposed method effectively reduces this disparity and balances performance among different users/targets. Although the null-space projection scheme leads to some degradation in sensing performance, the minimum received sensing power remains stable. This indicates that the overall system satisfaction is not affected and that sensing requirements are still satisfied (Fig. 9). Conclusions This study addresses the AP–user/target association problem in low-altitude airspace. The BRM is used to predict channels between APs and users/targets and to provide global channel information for joint optimization. By maximizing the minimum user/target satisfaction, ISAC beamforming is optimized, and AP–user/target association is iteratively refined using a genetic algorithm. Simulation results show that the proposed method effectively improves AP–user/target association and enhances integrated communication and sensing performance compared with existing approaches.
- Cell-free architecture,
- Integrated Sensing And Communication (ISAC),
- Beamforming,
- AP-user/target association,
- Binary Radio Map (BRM)

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References(22)

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