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Joint optimization of SNR and motion energy consumption for UAV-enabled collaborative beamforming

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Abstract

Unmanned aerial vehicles (UAVs) are usually resource constrained, and have the limited communication and energy storage capacity. Collaborative beamforming (CB) in UAV networks based on a virtual node antenna array (VNAA) can enhance the signal-to-noise-ratio (SNR) and energy efficiency of a single UAV node. The UAV nodes can move to better locations for constructing the VNAA to achieve a maximum SNR of CB. However, this will result in an extra motion energy consumption. In this paper, we formulate a joint optimization problem to simultaneously optimize the received SNR and motion energy consumption for UAV-enabled CB. Then, a mended particle swarm optimization with weed optimization mechanism algorithm is proposed to solve the formulated joint optimization problem. Simulation results verify the effectiveness of the proposed algorithm.

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Acknowledgements

This study is supported in part by the National Natural Science Foundation of China (62172186, 62002133, 61872158, 61806083), in part by the Science and Technology Development Plan Project of Jilin Province (20190701019GH, 20190701002GH, 20210101183JC, 20210201072GX), in part by the Young Science and Technology Talent Lift Project of Jilin Province (QT202013), and in part by Graduate Innovation Fund of Jilin University (101832020CX176, 101832020CX177).

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Correspondence to Geng Sun.

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Zheng, T., Liu, Y., Sun, G. et al. Joint optimization of SNR and motion energy consumption for UAV-enabled collaborative beamforming. Wireless Netw 28, 2001–2016 (2022). https://doi.org/10.1007/s11276-022-02954-6

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