Networked ISAC for Low-Altitude Economy: Transmit Beamforming and UAV Trajectory Design
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arXiv
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| Auteurs principaux: | , , , |
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| Format: | Preprint |
| Publié: |
2024
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| _version_ | 1866914793896542208 |
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| author | Cheng, Gaoyuan Song, Xianxin Lyu, Zhonghao Xu, Jie |
| author_facet | Cheng, Gaoyuan Song, Xianxin Lyu, Zhonghao Xu, Jie |
| contents | This paper studies the exploitation of networked integrated sensing and communications (ISAC) to support low-altitude economy (LAE), in which a set of networked ground base stations (GBSs) transmit wireless signals to cooperatively communicate with multiple authorized unmanned aerial vehicles (UAVs) and concurrently use the echo signals to detect the invasion of unauthorized objects in interested airspace. Under this setup, we jointly design the cooperative transmit beamforming at multiple GBSs together with the trajectory control of authorized UAVs and their GBS associations, for enhancing the authorized UAVs' communication performance while ensuring the sensing requirements for airspace monitoring. In particular, our objective is to maximize the average sum rate of authorized UAVs over a particular flight period, subject to the minimum illumination power constraints for sensing over the interested airspace, the maximum transmit power constraints at individual GBSs, and the flight constraints at UAVs. This problem is non-convex and challenging to solve, due to the involvement of integer variables and the coupling of optimization variables. To solve this non-convex problem, we propose an efficient algorithm by using the techniques of alternating optimization (AO), successive convex approximation (SCA), and semi-definite relaxation (SDR). Numerical results show that the obtained transmit beamforming and UAV trajectory designs in the proposed algorithm efficiently balance the tradeoff between the sensing and communication performances, thus significantly outperforming various benchmarks. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2405_07568 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Networked ISAC for Low-Altitude Economy: Transmit Beamforming and UAV Trajectory Design Cheng, Gaoyuan Song, Xianxin Lyu, Zhonghao Xu, Jie Signal Processing This paper studies the exploitation of networked integrated sensing and communications (ISAC) to support low-altitude economy (LAE), in which a set of networked ground base stations (GBSs) transmit wireless signals to cooperatively communicate with multiple authorized unmanned aerial vehicles (UAVs) and concurrently use the echo signals to detect the invasion of unauthorized objects in interested airspace. Under this setup, we jointly design the cooperative transmit beamforming at multiple GBSs together with the trajectory control of authorized UAVs and their GBS associations, for enhancing the authorized UAVs' communication performance while ensuring the sensing requirements for airspace monitoring. In particular, our objective is to maximize the average sum rate of authorized UAVs over a particular flight period, subject to the minimum illumination power constraints for sensing over the interested airspace, the maximum transmit power constraints at individual GBSs, and the flight constraints at UAVs. This problem is non-convex and challenging to solve, due to the involvement of integer variables and the coupling of optimization variables. To solve this non-convex problem, we propose an efficient algorithm by using the techniques of alternating optimization (AO), successive convex approximation (SCA), and semi-definite relaxation (SDR). Numerical results show that the obtained transmit beamforming and UAV trajectory designs in the proposed algorithm efficiently balance the tradeoff between the sensing and communication performances, thus significantly outperforming various benchmarks. |
| title | Networked ISAC for Low-Altitude Economy: Transmit Beamforming and UAV Trajectory Design |
| topic | Signal Processing |
| url | https://arxiv.org/abs/2405.07568 |