AI-Driven Integration of Terrestrial and Non-Terrestrial Networks (AITNTN)

The evolution of communication networks is entering a pivotal era, marked by 3GPP Release 17, which has empowered 5G operators to extend their services beyond terrestrial boundaries. This expansion reaches far beyond traditional communication networks, impacting not only remote communities but also maritime, airborne, and other isolated environments. The introduction of Non-Terrestrial Networks (NTN), which includes Uncrewed Aerial Vehicles (UAVs), High Altitude Platform Stations (HAPS), and satellites, brings unprecedented coverage capabilities to the telecommunications industry. This enables a wide array of applications—such as Machine-to-Machine (M2M) communication, emergency response, and enhanced connectivity for high-speed platforms (airplanes, trains, ships)—across various sectors like agriculture, transportation, environmental monitoring, and asset tracking. However, the integration of NTN into Terrestrial Networks (TN) presents unique technical and regulatory challenges. Unlike traditional TN base stations, satellites, especially those in Low Earth Orbit (LEO), move at high velocities, introducing complexities like Doppler shift and frequency variations. Addressing these issues requires compensating for satellite mobility and ensuring the reliability of user devices. Moreover, NTN systems face challenges related to higher path loss due to extended signal paths through the atmosphere, which affects latency and network capacity. These networks must carefully balance resource allocation based on real-time system dynamics and user demand, and spectrum-sharing between NTN and TN demands efficient dynamic spectrum access strategies. Collaboration among satellite operators, mobile network providers, government agencies, and standards bodies will be essential to overcoming these regulatory and technical hurdles.
 
One of the most exciting developments in this space is the direct-to-device communication paradigm, especially the prospect of direct-to-smartphone connectivity. Historically, the NTN narrative focused on providing coverage for rural and remote areas, but recent advancements in satellite mega constellations and HAPS networks have expanded its potential dramatically. By the 2030s, these systems could be powerful enough to communicate directly with 6G smartphones, smart glasses, and other consumer devices, enabling high-end use cases like video streaming across a global $10 trillion market. With an estimated 10 billion smartphones and 100 billion Internet of Things (IoT) devices globally, this shift will impact everyone, far beyond rural and remote areas. The direct-to-device approach has transformative potential and poses a significant challenge to traditional Mobile Network Operators (MNOs), potentially disrupting the current telecom business model.
 
Achieving seamless integration of NTN into TN for such advanced use cases requires more than just overcoming physical and regulatory challenges. Wireless devices that were initially designed for TN will require new architectures to establish stable and efficient links with satellite systems. Here, Artificial Intelligence (AI) becomes a critical enabler. AI-supported methods can optimize future 6G networks, allowing them to function effectively in dynamic, unpredictable environments. By analyzing large datasets and making real-time decisions, AI can help manage the complexities of TN-NTN integration, ensuring the networks adapt to changing conditions and user demands. The effectiveness of these AI models, however, relies on the availability of high-quality training data.
 
This Special Interest Group (SIG) will serve as a platform for researchers, engineers, and professionals to explore the role of AI in bridging TN and NTN, overcoming the technical challenges of integration, and examining the disruptive potential of direct-to-device satellite communications. Together, we aim to shape the future of global telecommunications by facilitating discussions, research, and innovation in these transformative technologies.

 


Orthogonal Time Frequency Space-Special Interest Group (OTFS-SIG)

Over the past few years, communication technologies for emerging high-mobility applications are much less understood and significantly under-developed. The recently developed OTFS has been recognized globally for its great potential to achieve high-speed and high-reliable communications in a high-mobility environment. While some initial works on the concepts and the implementations of OTFS have been investigated, there are still several challenges and open problems to be addressed.
 
This SIG is to provide a platform to bring together academic and industrial researchers in an effort to identify and discuss the major technical challenges, recent breakthroughs, and new applications related to OTFS.
 

Satellite Mega-constellations: Communications and Networking

There is rejuvenated interest in satellite communications and networking. Both the satellite and cellular (3GPP) industries aim at developing a seamlessly integrated one network with both terrestrial and satellite components. One main difference between the legacy satellite systems and the mega-constellations of the 6G era (next-generation) satellite system is the networking aspect. The next-generation satellite networks are expected to have very high-speed inter-satellite links. For efficient operation, the network will have to be autonomous, intelligent, resilient, self-organizing & self-controlling as much as possible to reduce the cost and risk of human intervention in such highly complicated settings. Distributed decision making, fault recovery, resilience, and scalability are among the important features of the envisioned satellite networks. These networks will rely on artificial intelligence (AI) techniques as much as possible, at all levels: Ground operations, on-board operations, as well as inter-satellite (FSO) and satellite-to-ground links (RF and/or FSO). In addition to networking, the scope of the SIG includes the communications aspects as well for AI-enabled channel prediction and optimized physical layer; grouping them in a single project is envisioned to provide synergy. High altitude platform station (HAPS) systems and HAPS constellations are also expected to play a significant role in the seamless integration of the mega-constellations with the terrestrial networks. Clearly, the satellite mega-constellations in the 6G era will create unprecedented opportunities once the unprecedented challenges are addressed by the research community.