Research on UAV-assisted maritime communication method based on K-means algorithm

As wireless communication technology continues to evolve and 6G mobile communication networks strive to create a fully connected communication world, the use of drones in wireless communication networks is becoming more prevalent. Compared with traditional terrestrial communication infrastructure The use of UAVs to assist offshore communication has great advantages, such as UAVs can provide line-of-sight links to improve the quality and capacity of the signal, the high mobility and flexibility of UAVs make them adaptable to complex wireless communication environments at sea, and UAV communication is more cost-effective with a wider coverage range. By obtaining the position information of a UAV node in a UAV cluster communication group network as a data set. Calculate the distance between the position information of the initial cluster head UAV and the position information of the UAV nodes based on the dataset to obtain the internal cluster distance set, and determine the new cluster of the UAV cluster based on the internal cluster distance set. The k -means algorithm is used to average the position information of the UAV nodes in the new cluster of UAV clusters, and iterative clustering by clusters is carried out to obtain the center position information, and the UAV cluster communication group network is reconstructed according to the center position information. This method can realize flexible self-organized network clustering and cluster head selection and reconstruction of UAV clusters under high dynamic environment, and improve the quality of large-scale UAV cluster communication and the number of communication service people under emergency rescue environment.