Radar Probing Optimization for Joint Beamforming and UAV Trajectory Design in UAV-Enabled Integrated Sensing and Communication
Unmanned aerial vehicle (UAV)-enabled massive multiple-input-multiple-output (MIMO) integrated sensing and communication (ISAC) is an emerging platform to perform communication and sensing efficiently and flexibly. However, the existing works barely consider the radar probing tasks and neglect the benefits of the dedicated sensing signal. In this paper, we focus on joint optimizations in radar probing tasks, and a novel indicator is introduced, namely radar probing error. Two optimizations in radar probing tasks are established: i) joint transmit beamforming design for large-scale regional radar probing and communication task; ii) joint transmit beamforming and UAV trajectory design for communication enhancement and radar probing task. For the former task, we adopt both communication and novel sensing precoders to further support the MIMO radar. A semidefinite relaxation is utilized to relax the original non-convex problem, which is proven to be tight. For the latter task, we adopt block coordinate descent to alternately optimize the precoders and UAV trajectory where the fractional programming approach and successive convex approximation are further adopted. Experiment results testify the validation of the proposed methods for radar probing tasks in UAV-enabled MIMO ISAC. Moreover, results show the fundamental trade-off between the dual functions and reveal the effectiveness of the introduced sensing precoder.
Authors
- Wei Huangfu (ORCID: https://orcid.org/0000-0003-2887-8395)
- Boxin He (ORCID: https://orcid.org/0009-0000-8926-8238)
- Keping Long
- Wenzhe Mao (ORCID: https://orcid.org/0000-0002-0676-8462)
- Tianyao Huang (ORCID: https://orcid.org/0000-0002-9043-6814)
- Haijun Zhang (ORCID: https://orcid.org/0000-0002-0236-6482)
- Yaxi Liu (ORCID: https://orcid.org/0000-0001-5012-8502)
Institutions
- National Institute of Informatics (JP)
- Beijing Advanced Sciences and Innovation Center (CN)
- University of Science and Technology Beijing (CN)
Publication Details
- Journal
- IEEE Transactions on Communications
- Published
- 2024-11-27
- DOI
- https://doi.org/10.1109/tcomm.2024.3506917
- Citations
- 11
- Primary Topic
- Radar Systems and Signal Processing
- Type
- article
- Field-Weighted Citation Impact
- 14.29
Funders
- National Natural Science Foundation of China
- Natural Science Foundation for Young Scientists of Shanxi Province