Artificial Intelligence Satellite Telecommunication Testbed using Commercial Off-The-Shelf Chipsets

The Artificial Intelligence Satellite Telecommunications Testbed (AISTT), part of the ESA project SPAICE, is focused on the transformation of the satellite payload by using artificial intelligence (AI) and machine learning (ML) methodologies over available commercial off-the-shelf (COTS) AI chips for on-board processing. The objectives include validating artificial intelligence-driven SATCOM scenarios such as interference detection, spectrum sharing, radio resource management, decoding, and beamforming. The study highlights hardware selection and payload architecture. Preliminary results show that ML models significantly improve signal quality, spectral efficiency, and throughput compared to conventional payload. Moreover, the testbed aims to evaluate the performance and application of AI-capable COTS chips in onboard SATCOM contexts.

A Deep-NN Beamforming Approach for Dual Function Radar-Communication THz UAV

In this paper, we consider a scenario with one UAV equipped with a ULA, which sends combined information and sensing signals to communicate with multiple GBS and, at the same time, senses potential targets placed within an interested area on the ground. We aim to jointly design the transmit beamforming with the GBS association to optimize communication performance while ensuring high sensing accuracy. We propose a predictive beamforming framework based on a dual DNN solution to solve the formulated nonconvex optimization problem. A first DNN is trained to produce the required beamforming matrix for any point of the UAV flying area in a reduced time compared to state-of-the-art beamforming optimizers. A second DNN is trained to learn the optimal mapping from the input features, power, and EIRP constraints to the GBS association decision. Finally, we provide an extensive simulation analysis to corroborate the proposed approach and show the benefits of EIRP, SINR performance and computational speed.

Satellite Swarms for Narrow Beamwidth Applications

Satellite swarms have recently gained attention in the space industry due to their ability to provide extremely narrow beamwidths at a lower cost than single satellite systems. This paper proposes a concept for a satellite swarm using a distributed subarray configuration based on a 2D normal probability distribution. The swarm comprises multiple small satellites acting as subarrays of a big aperture array limited by a radius of 20000 wavelengths working at a central frequency of 19 GHz. The main advantage of this approach is that the distributed subarrays can provide extremely directive beams and beamforming capabilities that are not possible using a conventional antenna and satellite design. The proposed swarm concept is analyzed, and the simulation results show that the radiation pattern achieves a beamwidth as narrow as 0.0015-degrees with a maximum side lobe level of 18.8 dB and a grating lobe level of 14.8 dB. This concept can be used for high data rates applications or emergency systems.