A Mean Field Game-Theoretic Cross-Layer Optimization for Multi-Hop Swarm UAV Communications

Tong Li, Cong Li, Chungang Yang, Junqi Shao, Yue Zhang, Lei Pang, Lizhong Chang, Lingli Yang, and Zhu Han

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10.23919/JCN.2021.000035

Abstract :Unmanned aerial vehicle (UAV) multi-hop com-munication networks are foreseen to be widely employed in both military and civilian scenarios. However, in ultra-densescenarios with swarm UAVs, nodes are highly dynamic mobile,ultra-dense deployment and non-centralized distribution. Thesecharacteristics make the centralized resource management policynot apply. Meanwhile, existing routing protocols can’t meetthe performance challenges of high dynamic, topology and linkfrequency changes of ultra-dense scenarios with swarm UAVs. Tosolve the above challenges of resource management and routingprotocol, a cross-layer optimization method is presented witha novel mean field game (MFG) in this paper. It is based onthe cross-layer design method of the MFG theory and jointlyconsiders the power resources in the physical layer, frequencyresources in the medium access control (MAC) layer, and routingresources in the network layer. By dividing into subproblems,the original problem is solved. Meanwhile, the optimal datatransmission path can be selected through the management and allocation of frequency resources and power resources. A cross-layer resource management dynamic source routing (CLRM-DSR) protocol is designed based on that which adds link quality measurement. The simulation results show that the presentedCLRM-DSR with the proposed resource management scheme can improve the data packet transmission rate, reduce end-to-end delay, and lower routing overhead for the multi-hop swarm UAV communication network.​ 

Index terms :Cross-layer optimization, MFG, multi-hop com- munications, UAV