Low-Altitude Communication Networks Planning for Air Routes Coverage Based on Semi-Supervised GCN

Low-altitude economy is poised to become a new economic form, influencing the next-generation wireless communications. It is essential to develop low-altitude communication networks (LACNs) capable of providing wireless coverage for aircrafts, whose planning methodologies are still not well-defined. To tackle this issue, a LACNs planning scheme to support air routes communication coverage is studied. Specifically, an extended semi-supervised graph convolutional network (ESemi-GCN) algorithm is proposed to select which existing ground base stations (BSs) should be upgraded to low-altitude BSs. Simulation results exhibit the efficiency and cost-effectiveness of the proposed ESemi-GCN algorithm to establish the LACNs.