Average Consensus Based Channel Rendezvous for Multi-UAV Networks

Multi-UAV networks have become increasingly popular in many fields. However, UAVs lack a reliable common control channel and have a limited sensing range in a crowded electromagnetic environment. Therefore, achieving distributed and adaptive channel rendezvous for multi-UAV networks become an urgent challenge. To address this issue, this paper proposes a class of channel rendezvous algorithms for multi-UAV networks based on average consensus. After the multi-UAV network has been disconnected from the communication link due to interference, the objective is to adjust the communication channel of each UAV to rendezvous at the same one. The proposed Memory-based Average Consensus (MAC) algorithm exploits the network adjacency matrix as a priori information. In addition, for the case where the adjacency matrix is unknown, this paper also proposes Multi-Radio Average Consensus (MRAC) algorithm, which achieves a beneficial tradeoff between rendezvous performance and hardware cost. Simulation results show that the proposed MAC and MRAC algorithms provide superior network rendezvous time and scalability in networks of varying densities. the MAC and MRAC algorithms require only 164 and 104 time slots to complete channel rendezvous in a 100-UAV network, respectively.