Centralized Spectrum Sharing and Coordination Between Terrestrial and Aerial Base Stations of 3GPP-Based 5G Networks

The objective of this paper is to estimate performance of a new approach for spectrum sharing and coordination between terrestrial base stations (BS) and On-board radio access nodes (UxNB) carried by Unmanned Aerial Vehicles (UAV). This approach employs an artificial intelligence (AI) based algorithm implemented in a centralized controller. According to the assessment based on the latest specifications of 3rd Generation Partnership Project (3GPP) the newly defined Unmanned Aerial System Traffic Management (UTM) is feasible to implement and utilize an algorithm for dynamic and efficient distribution of available radio resources between all radio nodes involved in process of optimization. An example of proprietary algorithm has been described, which is based on the principles of Kohonen neural networks. The algorithm has been used in simulation scenario to illustrate the performance of the novel approach of centralized radio channels allocation between terrestrial BSs and UxNBs deployed in 3GPP-defined rural macro (RMa) environment. Simulation results indicate that at least 85% of simulated downlink (DL) transmissions are gaining additional channel bandwidth if presented algorithm is used for spectrum distribution between terrestrial BSs and UxNBs instead of baseline soft frequency re-use (SFR) approach.