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A master programme thesis from Aalborg University

Automated Satellite Communication Testbed for Complex Interference Signal Separation Using Real-Time AI-Driven Data: Satellite communication interference mitigation testbed using AI driven data

[Automated Satellite Communication Testbed for Complex Interference Signal Separation Using Real-Time AI-Driven Data]

Author(s)

Term

4. semester

Education

Publication year

2025

Submitted on

2025-06-04

Pages

83 pages

Abstract

This master’s thesis develops a flexible, reprogrammable testbed for emulating a satellite communication system, including a ground station, satellite transponder, and interference source. The platform that is presented enables automated measurement campaigns to collect high-quality data for AI-based interference mitigation. The thesis also includes system validation across QPSK, BPSK, and 8PSK modulation schemes, which has an error vector magnitude of 0.22% ±0.005% and modulation error rate up to 51.87%, which indicates and confirms an excellent signal integrity in both low and highly increased interference settings. Furthermore, a U-Net implementation separates the interference from real-time raw (no preprocessing) mixed IQ signals. The U-Net is trained on extensive, large real-world data sets of over 200,000 data samples per gain and frequency settings. The U-Net achieved near reference level denoised signal, reflecting correlation values over 98% for QPSK and BPSK 96% and up to 98.45% for 8PSK, even at the highest interference levels. The results demonstrate robust interference suppression, high reconstruction fidelity, and strong generalization capability. The validated automated testbed and U-Net architecture successfully fulfill the thesis objective of enabling real-time AI-driven signal separation of complex interference in satellite communication links.

Keywords

Documents


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