In the wireless communication, there are many cases where the transmission path is obstructed by unknown objects. With the rapid development of the drone technology in recent years, the drones are advocated to serve as mobile relays to forward data streams. However, the challenges are that data transmission may suffer severe signal attenuation due to the existence of the obstructions and it is challenging to find the best location for mobile relays due to the dynamic environment and unpredictable interference. To address the problem, this paper proposes an approach that a drone can automatically find the location with the optimal link quality. We design a novel algorithm, named Path-sampling Online Tensor Update (POTU), to estimate the link quality in the space and find the optimal location. Furthermore, the algorithm is practical to the real applications due to the simplicity of implementation. In the experiment, we construct a realistic scene and compare the performance of our algorithm with the classic and the state-of-the-art algorithms. As a result, POTU outperforms existing methods in achieving the trade-off between time cost and estimation accuracy.
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Xie et al. (2016) studied this question.
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