Precoding and Trajectory Design of Unmanned Aerial Vehicle Based on Joint Communication and Sensing

CHAI Rong; CUI Xianglin; SUN Ruijin; CHEN Qianbin

doi:10.11999/JEIT230515

Volume 46 Issue 4

Apr. 2024

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CHAI Rong, CUI Xianglin, SUN Ruijin, CHEN Qianbin. Precoding and Trajectory Design of Unmanned Aerial Vehicle Based on Joint Communication and Sensing[J]. Journal of Electronics & Information Technology, 2024, 46(4): 1266-1275. doi: 10.11999/JEIT230515

Citation:

CHAI Rong, CUI Xianglin, SUN Ruijin, CHEN Qianbin. Precoding and Trajectory Design of Unmanned Aerial Vehicle Based on Joint Communication and Sensing[J]. Journal of Electronics & Information Technology, 2024, 46(4): 1266-1275. doi: 10.11999/JEIT230515

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Precoding and Trajectory Design of Unmanned Aerial Vehicle Based on Joint Communication and Sensing

doi: 10.11999/JEIT230515

1.
School of Communications and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
2.
State Key Laboratory of Integrated Services Networks, Xidian University, Xi’an 710126, China

Funds: The National Natural Science Foundation of China (62271097)

Received Date: 2023-05-30
Rev Recd Date: 2023-12-01

Available Online: 2023-12-06

Publish Date: 2024-04-24

Abstract

Abstract

Benefited from the characteristics of high mobility, low cost and convenient deployment, by deploying communication and sensing equipment and supporting efficient resource sharing of communication and sensing technologies, Unmanned Aerial Vehicles (UAVs) are expected to act as high-performance aerial platforms which integrate communication and sensing technologies. In this paper, Multiple-Input-Multiple-Output (MIMO) UAV-enabled joint communication and sensing scenario is examined, the constraints of the flight energy of the UAV, multi-antenna transmission and user service requirement are jointly considered, the problem of UAV communication, sensing precoding and flight trajectory is formulated as a multi-objective optimization problem which jointly maximizes the minimum data rate of communication users and the minimum discovery probability of targets. Since the minimum rate maximization problem of communication users is a non-convex optimization problem, which is difficult to solve directly, the original optimization problem is decomposed into communication precoding design subproblem and UAV trajectory design subproblem. The two subproblems are solved successively by applying alternate iteration method until the algorithm reaches convergence. Specifically, a Zero-Forcing (ZF) algorithm is put forward for solving the communication precoding design subproblem. A Successive Convex Approximation (SCA) algorithm is applied to determine the optimal trajectory of the UAV. Based on the optimal trajectory of UAV, the sensing location selection problem is modeled as a weighted distance minimization problem, and then the extensive search algorithm is applied to obtain the optimal locations. Finally, a ZF algorithm-based joint communication and sensing precoding is presented. The effectiveness of the proposed algorithm is verified by simulations.
- Unmanned Aerial Vehicle (UAV),
- Joint communication and sensing,
- Trajectory optimization,
- Precoder design

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References(16)

References

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