The objective of the ESA project AIComS is to develop AI/ML-based SW/HW platforms for future products of an integrated satellite and 5G&beyond communication network. It focusses on the development of ML-based 5G NR physical layer components and investigates different functional splits. Furthermore, 5G&beyond compliant ML-based routing, network slicing, and security components will be investigated. The 3GPP 5G specifications are tracked for these developments.

In particular, AIComS focuses on the development of ML-based 5G NR PHY-Layer components of (v)LEO satellites and the gNB to provide communication between terrestrial UE- and IoT-terminals (service link) and the gNB (feeder link) via (v)LEO satellites. In addition, AIComS will develop 5G&beyond compliant ML-based routing, network slicing, and security components for (v)LEO satellites that are connected via Inter-Satellite-Links (ISLs) to form a satellite backhaul network. Thus, AIComS is on regenerative satellites based 3GPP Next Generation-Radio Access Network (NG-RAN) architectures facilitating different payload options like gNB processed payload with or without ISLs or options that allow for NG-RAN logical architectures with different functional splits by means of Remote Units (RUs), Central Units (CUs) and Distributed Units (DUs).

Objective

The overall goal of the project AIComS is to develop AI/ML-based SW/HW platforms for future products of an integrated satellite and 5G&beyond communication network. It focusses on the development of ML-based 5G NR PHY-Layer components and 5G&beyond compliant ML-based routing, network slicing, and security components.

The following developments are targeted by the project activities:

• 5G NTN Baseband Processing Platform: Development of data driven baseband technologies for 5G-NTN RAN with different functional splits
• 5G AI Satellite Packet Router: Development of data-driven network and service technologies
• 5G AI Satellite Packet Router: Development of data-driven IT security concepts
• AI based Fault Detection, Identification and Recovery (AI-FDIR) Software: Development of data driven prediction methods
• AI based Formation Control (AI-FC) Algorithms: Development of data driven formation control algorithms
• AI based VLEO Orbit Control (AI-VLEO-OC): Communication aware development of data driven antenna beam pointing, navigation and AOCS algorithms as well as drag compensatio

It will be an outcome of the project to gain knowledge about the appropriate degree of autonomy by means of AI or how much control is still required.

Further Information

Project webpage       AIComS | ESA CSC

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