peer reviewed

peer reviewed

The latest Satellite Communication (SatCom) missions are characterized by a fully reconfigurable on-board software-defined payload, capable of adapting radio resources to the temporal and spatial variations of the system traffic. As pure optimization-based solutions have shown to be computationally tedious and to lack flexibility, Machine Learning (ML)-based methods have emerged as promising alternatives. We investigate the application of energy-efficient brain-inspired ML models for on-board radio resource manage…

Spiking neural networks (SNNs) implemented on neuromorphic processors (NPs) can enhance the energy efficiency of deployments of artificial intelligence (AI) for specific workloads. As such, NP represents an interesting opportunity for implementing AI tasks on board power-limited satellite communication spacecraft. In this article, we disseminate the findings of a recently completed study which targeted the comparison in terms of performance and power-consumption of different satellite communication use cases imple…

Recently, non-geostationary orbit (NGSO) satellite communication constellations have regained popularity due to their ability to provide global coverage and lower-latency connectivity. However, the new wave of Low Earth Orbit (LEO) satellite constellations operate on the same spectral bands as legacy satellites in geosynchronous orbit (GSO), which concurrently access the electromagnetic spectrum. Even if international regulations are in place, such increased spectral congestion will result in interference events. …