Spatial Deployment and Beamforming for Design Multi-Unmanned Aerial Vehicle-Integrated Sensing and Communication Based on Transmission Fairness

SHI Tongzhi; LI Bo; YANG Hongjuan; ZHANG Tong; WANG Gang

doi:10.11999/JEIT240590

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SHI Tongzhi, LI Bo, YANG Hongjuan, ZHANG Tong, WANG Gang. Spatial Deployment and Beamforming for Design Multi-Unmanned Aerial Vehicle-Integrated Sensing and Communication Based on Transmission Fairness[J]. Journal of Electronics & Information Technology. doi: 10.11999/JEIT240590

Citation:

SHI Tongzhi, LI Bo, YANG Hongjuan, ZHANG Tong, WANG Gang. Spatial Deployment and Beamforming for Design Multi-Unmanned Aerial Vehicle-Integrated Sensing and Communication Based on Transmission Fairness[J]. Journal of Electronics & Information Technology. doi: 10.11999/JEIT240590

Citation:

SHI Tongzhi, LI Bo, YANG Hongjuan, ZHANG Tong, WANG Gang. Spatial Deployment and Beamforming for Design Multi-Unmanned Aerial Vehicle-Integrated Sensing and Communication Based on Transmission Fairness[J]. Journal of Electronics & Information Technology. doi: 10.11999/JEIT240590

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Spatial Deployment and Beamforming for Design Multi-Unmanned Aerial Vehicle-Integrated Sensing and Communication Based on Transmission Fairness

doi: 10.11999/JEIT240590

1.
School of Electronics and Information Engineering, Harbin Institute of Technology, Harbin 150001, China
2.
School of Information Science and Engineering, Harbin Institute of Technology at Weihai, Weihai 264209, China

Funds: The National Natural Science Foundation of China (62171154, 62171163), The Fundamental Research Funds for the Central Universities (HIT.OCEF.2023030)

Received Date: 2024-07-11
Rev Recd Date: 2024-09-13

Available Online: 2024-09-19

Abstract

Abstract

In response to the temporary and emergent issue of poor communication in rural and remote areas, an adaptive multi-Unmanned Aerial Vehicle (UAV)-assisted Integrated Sensing And Communication (ISAC) mechanism is proposed in this paper. In scenarios where ground users and sensing targets are randomly distributed in clusters, the mechanism achieves comprehensive communication coverage by rationally scheduling multiple UAVs, providing a novel solution and scheme for UAV-enabled ISAC systems. The spatial deployment of UAVs and their beamforming directed towards ground equipment are primarily addressed in this paper. Under the constraints of the air-ground association policy, the system can maximize the lower bound of the users’ transmission reachable rate by optimizing the set of communication and sensing beamforming variables for the UAVs, while ensuring the basic requirements of ISAC. To solve the considered non-convex optimization problems, the Mean Shift (MS) algorithm based on Gaussian kernels to manage the mixed-integer linear issues within the association strategy is first employed. Additionally, combining the quadratic transformation and Successive Convex Approximation (SCA), the optimization of beamforming is conducted via the Block Coordinate Descent (BCD) method, thereby securing a suboptimal solution. Numerical results validate the effectiveness of the adaptive mechanism.
- Unmanned Aerial Vehicle (UAV),
- Integrated Sensing And Communication (ISAC),
- Spatial deployment,
- Beamforming

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References(15)

References

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