4.7 Article

UAV-Assisted Time-Efficient Data Collection via Uplink NOMA

期刊

IEEE TRANSACTIONS ON COMMUNICATIONS
卷 69, 期 11, 页码 7851-7863

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TCOMM.2021.3106134

关键词

Data collection; non-orthogonal multiple access; successive convex approximation; trajectory optimization; unmanned aerial vehicle

资金

  1. National Key R&D Program of China [2020YFB1807002]
  2. National Natural Science Foundation of China (NSFC) [61871065]
  3. open research fund of State Key Laboratory of Integrated Services Networks [ISN22-22]

向作者/读者索取更多资源

In this paper, a time-efficient data collection scheme is proposed, where multiple ground devices upload their data to the UAV via uplink non-orthogonal multiple access (NOMA) to ensure timely information delivery. The scheme divides the total flight time of the UAV into N time slots and minimizes the duration of each slot through joint optimization. By decomposing the problem into two steps and using an iterative algorithm based on alternating optimization, the proposed scheme effectively optimizes data collection with UAV assistance.
Due to the mobility and line-of-sight conditions, unmanned aerial vehicle (UAV) is deemed as a promising solution to sensor data collection. On the other hand, it is vital to guarantee the timeliness of information for UAV-assisted data collection. In this paper, we propose a time-efficient data collection scheme, in which multiple ground devices upload their data to the UAV via uplink non-orthogonal multiple access (NOMA). The total flight time of the UAV is equally divided into N time slots. The duration of each time slot is minimized by jointly optimizing the straight-line trajectory, device scheduling, and transmit power. To solve this mixed integer non-convex optimization problem, we decompose it into two steps. In the first step, we study the device scheduling strategy based on the UAV trajectory and the channel gains between the UAV and ground devices, through which the original problem can be greatly simplified. In the second step, the duration of each time slot is minimized by optimizing the transmit power and the UAV trajectory. An iterative algorithm based on alternating optimization is proposed, where each subproblem can be alternatively solved by applying successive convex approximation with the device scheduling updated at the end of each iteration. Numerical results are presented to evaluate the effectiveness of the proposed scheme.

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