A mean field game-theoretic cross-layer optimization for multi-hop swarm UAV communications

Unmanned aerial vehicle (UAV) multi-hop communicationnetworks are foreseen to be widely employed inboth 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 andallocation of frequency resources and power resources. A crosslayerresource management dynamic source routing (CLRMDSR)protocol is designed based on that which adds link qualitymeasurement. The simulation results show that the presentedCLRM-DSR with the proposed resource management schemecan improve the data packet transmission rate, reduce end-toenddelay, and lower routing overhead for the multi-hop swarmUAV communication network. KCI Citation Count: 0