Open Datasets for Satellite Radio Resource Control

TL;DR

This paper introduces open datasets for satellite radio resource control in Non-Terrestrial Networks, aiming to facilitate research and development of AI-driven resource management solutions in dynamic satellite environments.

Contribution

It provides realistic open datasets for satellite communication research, enabling benchmarking and development of advanced resource management techniques.

Findings

Datasets incorporate realistic traffic flow data.

Application example demonstrates beam placement optimization.

Facilitates adaptive beamforming for dynamic traffic demands.

Abstract

In Non-Terrestrial Networks (NTN), achieving effective radio resource allocation across multi-satellite system, encompassing efficient channel and bandwidth allocation, effective beam management, power control and interference mitigation, poses significant challenges due to the varying satellite links and highly dynamic nature of user traffic. This calls for the development of an intelligent decision-making controller using Artificial Intelligence (AI) to efficiently manage resources in this complex environment. In this context, open datasets can play a crucial role in driving new advancement and facilitating research. Recognizing the significance, this paper aims to contribute the satellite communication research community by providing various open datasets that incorporate realistic traffic flow enabling a variety of uses cases. The primary objective of sharing these datasets is to facilitate the development and benchmarking of advanced resource management solutions, thereby improving the overall satellite communication systems. Furthermore, an application example focused on beam placement optimization via terminal clustering is provided. This assists in optimizing beam allocation task, enabling adaptive beamforming to effectively meet spatiotemporally varying user traffic demands and optimize resource utilization.