Joint Design of Transmit Waveform and Altitude for Unmanned Aerial Vehicle-Enabled Integrated Sensing and Wireless Power Transfer Systemsopen access
- Authors
- Kang, Jinho
- Issue Date
- Nov-2024
- Publisher
- MDPI AG
- Keywords
- UAV; wireless power transfer; MIMO radar; sensing; transmit waveform; altitude; optimization
- Citation
- Electronics (Basel), v.13, no.21
- Indexed
- SCIE
SCOPUS
- Journal Title
- Electronics (Basel)
- Volume
- 13
- Number
- 21
- URI
- https://scholarworks.gnu.ac.kr/handle/sw.gnu/74762
- DOI
- 10.3390/electronics13214237
- ISSN
- 2079-9292
2079-9292
- Abstract
- Recently, unmanned aerial vehicle (UAV)-enabled wireless power transfer (WPT) has received great attention as a promising technology for providing stable power to energy-constrained devices by navigating three-dimensional (3D) space, particularly in challenging environments such as maritime networks and smart cities. Additionally, UAV-enabled radar sensing has gained significant attention as a key technology for future 6G networks, as it enables high-accuracy sensing for various applications, such as target detection and tracking, surveillance, and environmental monitoring, as well as autonomous UAV operation. In this regard, we investigated UAV-enabled integrated sensing and wireless power transfer (ISWPT) systems that combine radar sensing and WPT operations on a unified hardware platform, sharing the same spectrum of resources. In order to accurately sense multiple targets and efficiently transfer power to multiple devices at the same time, we propose a method for jointly designing the transmit waveform and UAV altitude, taking into account the fundamental trade-off between radar sensing performance with the desired beam pattern and WPT performance with the desired harvested power of the devices. We first developed an effective method to obtain the optimal waveform and altitude by solving a challenging non-convex optimization problem. Based on this, we developed another efficient, low-complexity method by exploring a novel transmit waveform and optimizing its parameters to reduce computational complexity and thereby lower power consumption in UAVs. The numerical results verify that the proposed method significantly improves both radar sensing and WPT performance, as well as substantially reduces computational complexity.
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