Abstract
Flying ad hoc networks (FANETs) formed with unmanned aerial vehicles (UAVs) have wide applications in military and civilian fields, including patrolling, search and rescue operations, monitoring. Due to limited bandwidths and the fragility of wireless communication, channel and power allocation has become a key issue which significantly affects the performance of a FANET. This problem is usually formulated as a mixed-integer nonlinear programming problem and some intelligent approximation algorithms like particle swarm optimization algorithms have been proposed in wireless mesh network (WMN) and D2D (Device-to-Device) network scenarios. In order to improve the overall network throughput and spectrum utilization ratio, a joint channel selection and power allocation algorithm based on Bayesian Optimization is proposed, which uses the conjugacy property of Beta distribution to obtain approximate optimal allocation results. Simulation experiment results have shown that the proposed algorithm has better performance in network throughput and normalized network satisfaction ratio than the compared algorithms.
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Acknowledgments
This work was supported in part by the National Natural Science Foundation of China (No. 61601483), Hunan Young Talents Grant (No. 2020RC3027) and the Training Program for Excellent Young Innovators of Changsha (No. kq2009027).
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Wang, P., Peng, W., Zhang, W., Lv, G. (2021). Joint Channel and Power Allocation Algorithm for Flying Ad Hoc Networks Based on Bayesian Optimization. In: Barolli, L., Woungang, I., Enokido, T. (eds) Advanced Information Networking and Applications. AINA 2021. Lecture Notes in Networks and Systems, vol 225. Springer, Cham. https://doi.org/10.1007/978-3-030-75100-5_28
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DOI: https://doi.org/10.1007/978-3-030-75100-5_28
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