Revolutionizing Future Connectivity: A Contemporary Survey on AI-empowered Satellite-based Non-Terrestrial Networks in 6G

Non-Terrestrial Networks (NTN) are expected to be a critical component of 6th Generation (6G) networks, providing ubiquitous, continuous, and scalable services. Satellites emerge as the primary enabler for NTN, leveraging their extensive coverage, stable orbits, scalability, and adherence to international regulations. However, satellite-based NTN presents unique challenges, including long propagation delay, high Doppler shift, frequent handovers, spectrum sharing complexities, and intricate beam and resource allocation, among others. The integration of NTNs into existing terrestrial networks in 6G introduces a range of novel challenges, including task offloading, network routing, network slicing, and many more. To tackle all these obstacles, this paper proposes Artificial Intelligence (AI) as a promising solution, harnessing its ability to capture intricate correlations among diverse network parameters. We begin by providing a comprehensive background on NTN and AI, highlighting the potential of AI techniques in addressing various NTN challenges. Next, we present an overview of existing works, emphasizing AI as an enabling tool for satellite-based NTN, and explore potential research directions. Furthermore, we discuss ongoing research efforts that aim to enable AI in satellite-based NTN through software-defined implementations, while also discussing the associated challenges. Finally, we conclude by providing insights and recommendations for enabling AI-driven satellite-based NTN in future 6G networks.Comment: 40 pages, 19 Figure, 10 Tables, Surve

Congestion Control for Adaptive Satellite Communication Systems with Intelligent Systems

With the advent of life critical and real-time services such as remote operations over satellite, e-health etc, providing the guaranteed minimum level of services at every ground terminal of the satellite communication system has gained utmost priority. Ground terminals and the hub are not equipped with the required intelligence to predict and react to inclement and dynamic weather conditions on its own. The focus of this thesis is to develop intelligent algorithms that would aid in adaptive management of the quality of service at the ground terminal and the gateway level. This is done to adapt both the ground terminal and gateway to changing weather conditions and to attempt to maintain a steady throughput level and Quality of Service (QoS) requirements on queue delay, jitter, and probability of loss of packets. The existing satellite system employs the First-In-First-Out routing algorithm to control congestion in their networks. This mechanism is not equipped with adequate ability to contend with changing link capacities, a common result due to bad weather and faults and to provide different levels of prioritized service to the customers that satisfies QoS requirements. This research proposes to use the reported strength of fuzzy logic in controlling highly non-linear and complex system such as the satellite communication network. The proposed fuzzy based model when integrated into the satellite gateway provides the needed robustness to the ground terminals to comprehend with varying levels of traffic and dynamic impacts of weather