Resource Allocation Schemes Based on Improved Beetle Antennae Search Algorithm for Collaborative Communication of the Unmanned Aerial Vehicle Network

In this paper, the resource allocation problem for collaborative communication of unmanned aerial vehicle network is formulated and analyzed. In our scenario, the unmanned aerial vehicles (UAVs) are uniformly distributed in the network. We consider that multiple UAVs can share one channel resource. First, a system model is established and the resource allocation problem is formulated. Then a resource allocation scheme based on the improved beetle antennae search algorithm is proposed, which finds the optimum solution efficiently. Finally, the simulation results show that the performance of the proposed the improved beetle antennae search algorithm is better than that of random algorithm. This scheme provides an efficient optimization for resource allocation of collaborative communication of UAVs.

[1]  Debasish Ghose,et al.  Resource allocation and coalition formation for UAVs: A cooperative game approach , 2013, 2013 IEEE International Conference on Control Applications (CCA).

[2]  Dong-Hee Lee,et al.  Performance of UAV(Unmanned Aerial Vehicle) communication system adapting WiBro with array antenna , 2009, 2009 11th International Conference on Advanced Communication Technology.

[3]  Liu Kai,et al.  Research on UAV communication network topology based on small world network model , 2017, 2017 IEEE International Conference on Unmanned Systems (ICUS).

[4]  Yuichi Kawamoto,et al.  On OFDM-Based Resource Allocation in LTE Radio Management System for Unmanned Aerial Vehicles (UAVs) , 2017, 2017 IEEE 86th Vehicular Technology Conference (VTC-Fall).

[5]  Jae-Hyun Kim,et al.  Dynamic resource allocation algorithm of UAS by network environment and data requirement , 2017, 2017 International Conference on Information and Communication Technology Convergence (ICTC).

[6]  Walid Saad,et al.  Unmanned Aerial Vehicle With Underlaid Device-to-Device Communications: Performance and Tradeoffs , 2015, IEEE Transactions on Wireless Communications.

[7]  Xujie Li,et al.  A combining call admission control and power control scheme for D2D communications underlaying cellular networks , 2016, China Communications.

[8]  Hao Jiang,et al.  Three-Dimensional Geometry-Based UAV-MIMO Channel Modeling for A2G Communication Environments , 2018, IEEE Communications Letters.

[9]  Yan Gu,et al.  Mathematical Characteristics of Uplink and Downlink Interference Regions in D2D Communications Underlaying Cellular Networks , 2017, Wirel. Pers. Commun..

[10]  Fangfang Li,et al.  A new beetle antennae search algorithm for multi-objective energy management in microgrid , 2018, 2018 13th IEEE Conference on Industrial Electronics and Applications (ICIEA).