ESA SHINE Project – ESA CSC: Connectivity & Secure Communications

Objectives

Benefits

Machine Learning (ML) solutions to aid the handover decision-making between NTN and TN 5G network can improve the handover success rate and decrease the handover signalling load and the service interruption time to a minimum. Hence, UEs, such as handheld and vehicle devices, can seamlessly connect to NTN and TN 5G networks.

Features

The following software products are the output of the SHINE project:

• SW-based HO Engine: That includes different handover engine options (ML-based and non-ML-based, for comparison purposes).
• SW-based System-Level Testbed: that simulates/emulates the end-to-end performance of multiple 5G networks (e.g. integrated TN-NTN system) and is used to test the newly developed handover engine.

Challenges

Integrating satellite non-terrestrial (NTN) and terrestrial (TN) networks enables ubiquitous network access, requiring 5G user equipment (UE), such as handheld devices or vehicle devices, to connect to both networks directly. In this scenario, UEs may need to perform handovers between TN and NTN networks. Optimizing the number of handovers and the success rate of switching between networks is critical to minimize service interruption. Conventionally, handover can be triggered by signal strength measurements, location information, and other parameters such as elevation angle, Timing Advance (TA) values or Doppler values exceeding a predefined threshold. However, the handover decision is also impacted by the high mobility of UEs and satellites, strict Quality of Service (QoS) requirements such as reliability and latency, and the Quality of Experience (QoE) in terms of UE service satisfaction. Additionally, the different architecture between the NTN and TN networks, the changing communication environment, and the end-user requirements may lead the conventional handover to make late/early decisions and switch to the wrong network/cell. For this, ML-aided handover decisions can be a solution for the TN-NTN integrated network to deal with the network’s partial information, uncertainty, rapidly changing environment, and strict time constraints.

System Architecture

The SHINE project focuses on 5G-based handover between different 5G-networks, from which at least one is a satellite-based NTN. Considering the simple case of two 5G-networks, the following scenarios are considered.

Scenario 1: Handover occurs between a TN and an NTN network with certain overlapping coverage over the region of interest.
Scenario 2: Handover occurs between two different NTN networks (operated by different operators), both with complementary coverage.