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Cellular Assisted UAV Sensing

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Unmanned Aerial Vehicle Applications over Cellular Networks for 5G and Beyond

Part of the book series: Wireless Networks ((WN))

Abstract

In this chapter, we first study the energy efficiency maximization problem when the UAV serve as an aerial user in Sect. 4.1, and then discuss the task completion time minimization problem in a cooperative cellular Internet of UAVs in Sect. 4.2. To improve the communication quality in the cellular Internet of UAVs, we propose UAV-to-everything (U2X) communications in Sect. 4.3. In Sect. 4.4, we investigate the decentralized trajectory design problem for cellular Internet of UAVs. Finally, we present an application of cellular Internet of UAVs for air quality index (AQI) monitoring.

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Notes

  1. 1.

    The multiple cell scenario is an extension of the single cell scenario, and will be studied in the future.

  2. 2.

    An example of tasks in this model is the geological detection. Specifically, each UAV is arranged to perform a series of tasks, and the geological information of each task is sensed by multiple UAVs.

  3. 3.

    If the UAV trajectory does not detour to the BS, the start point can be considered as the turning point.

  4. 4.

    We consider the UAVs as rotary wing UAVs which can hover in the air for some time slots. The rotary wing UAVs can move with the speed of [0, v max] in any time slot.

  5. 5.

    The value of γ th is set according to the QoS in the specific network.

  6. 6.

    The uplink sum-rate is the sum of U2N and CU transmission rate, and U2U transmission is not included in the uplink sum-rate. Therefore, the objective function does not contain the U2U rate. Instead, we set a minimum threshold for each U2U link to guarantee the success of the U2U transmissions.

  7. 7.

    We assume that the collected sensory data of each UAV in a cycle can be converted into a single sensory data frame with the same length.

  8. 8.

    For example, the UAV’s transmission will interfere with its sensing if the UAV tries to sense electromagnetic signals in the frequency bands which are adjacent to its transmission frequency.

  9. 9.

    Dataset can be found at https://github.com/YyzHarry/AQI_Dataset.

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Authors and Affiliations

  1. School of Electrical Engineering and Computer Science, Peking University, Beijing, China

    Hongliang Zhang & Lingyang Song

  2. Department of Electrical and Computer Engineering, University of Houston, Houston, TX, USA

    Zhu Han

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  1. Hongliang Zhang
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Zhang, H., Song, L., Han, Z. (2020). Cellular Assisted UAV Sensing. In: Unmanned Aerial Vehicle Applications over Cellular Networks for 5G and Beyond. Wireless Networks. Springer, Cham. https://doi.org/10.1007/978-3-030-33039-2_4

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