User Clustering Scheme for NOMA in Aviation Data Link

This study presents a user clustering methodology tailored to military aviation data links, predicated on Non-Orthogonal Multiple Access (NOMA). The approach initially applies K-means algorithm for initial user clustering, grounded in spatial distribution attributes. Following this preliminary phase, a genetic algorithm is deployed to further refine pairing optimization within each pre-existing user cluster, thereby finalizing the user clustering configuration. In the final stages, a series of comparative simulation experiments are conducted to affirm that the proposed algorithm not only showcases lower complexity but also outperforms traditional methods.