Saved in:
| Main Authors: | , , , , , , |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2511.13006 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866913074462588928 |
|---|---|
| author | Li, Fangzhi Ren, Zhichu Pan, Cunhua Ren, Hong Jin, Jing Wang, Qixing Wang, Jiangzhou |
| author_facet | Li, Fangzhi Ren, Zhichu Pan, Cunhua Ren, Hong Jin, Jing Wang, Qixing Wang, Jiangzhou |
| contents | To enhance the performance of aerial-ground networks, this paper proposes an integrated sensing and communication (ISAC) framework for multi-UAV systems. In our model, ground base stations (BSs) cooperatively serve multiple unmanned aerial vehicles (UAVs), employing a dynamic time-division strategy where beam scanning for sensing precedes data communication in each time slot. To maximize the sum communication rate while satisfying a mission-level cumulative radar mutual information (MI) requirement, we jointly optimize the UAV trajectories, communication and sensing power allocation, and the time-division ratio. The resulting highly coupled non-convex optimization problem is efficiently solved using an alternating optimization (AO) and successive convex approximation (SCA) framework, which yields a non-decreasing objective sequence and convergence to a finite objective value under the adopted surrogate-based iterative procedure. Extensive simulation results demonstrate that our proposed joint design significantly outperforms benchmark schemes with static trajectories, partially optimized resources, or non-cooperative single-BS transmission. Furthermore, a comprehensive sensitivity analysis reveals the distinct mechanisms by which sensing thresholds and the number of UAVs influence resource allocation and spatial organization, highlighting the critical importance of dynamic, multi-dimensional resource management for effectively navigating the sensing-communication trade-off in low-altitude economies. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2511_13006 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Cooperative ISAC for LAE: Joint Trajectory Planning, Power allocation, and Dynamic Time Division Li, Fangzhi Ren, Zhichu Pan, Cunhua Ren, Hong Jin, Jing Wang, Qixing Wang, Jiangzhou Systems and Control To enhance the performance of aerial-ground networks, this paper proposes an integrated sensing and communication (ISAC) framework for multi-UAV systems. In our model, ground base stations (BSs) cooperatively serve multiple unmanned aerial vehicles (UAVs), employing a dynamic time-division strategy where beam scanning for sensing precedes data communication in each time slot. To maximize the sum communication rate while satisfying a mission-level cumulative radar mutual information (MI) requirement, we jointly optimize the UAV trajectories, communication and sensing power allocation, and the time-division ratio. The resulting highly coupled non-convex optimization problem is efficiently solved using an alternating optimization (AO) and successive convex approximation (SCA) framework, which yields a non-decreasing objective sequence and convergence to a finite objective value under the adopted surrogate-based iterative procedure. Extensive simulation results demonstrate that our proposed joint design significantly outperforms benchmark schemes with static trajectories, partially optimized resources, or non-cooperative single-BS transmission. Furthermore, a comprehensive sensitivity analysis reveals the distinct mechanisms by which sensing thresholds and the number of UAVs influence resource allocation and spatial organization, highlighting the critical importance of dynamic, multi-dimensional resource management for effectively navigating the sensing-communication trade-off in low-altitude economies. |
| title | Cooperative ISAC for LAE: Joint Trajectory Planning, Power allocation, and Dynamic Time Division |
| topic | Systems and Control |
| url | https://arxiv.org/abs/2511.13006 |