An Enhanced Resilience and Throughput BBV-based Method for UAV Networks

In harsh environments such as battlefield operations and emergency communications, communication rate and network resilience significantly impact the performance of UAV swarm networks. This paper proposes a scalable UAV network construction scheme named UMBTO, which aims to maximize communication rates while enhancing network resilience. By considering the communication range of UAVs and introducing triangular linking methods to improve the Barrat, Barthelemy, and Vespignani (BBV) model, suitable links are established for each new UAV, endowing the network with stronger resilience against random failures. Furthermore, considering the existing links and relative positions between UAVs, we formulate a system-wide link communication rate (SLCR) maximization problem. By dynamically adjusting the deployment positions of UAVs to maximize SLCR, the scheme ensures effective information exchange within the swarm, enhancing collaborative efficiency. The constructed network is scalable, allowing new UAVs to be seamlessly integrated without the need for cumbersome steps to rebuild the network topology. Evaluation and simulation results demonstrate that the proposed scheme constructs UAV networks with stronger resilience and better link communication rates compared to traditional BBV networks.