Satellite Adaptive Onboard Beamforming Using Neuromorphic Processors

The demand for improved satellite communication (SatCom)-based broadband connectivity has led to significant technological advancements, particularly in non-geostationary orbit (NGSO) satellites. The new SatCom systems are expected to have flexible beam footprints with fully adaptable payloads while being energy-efficient. With this in mind, this paper explores using neuromorphic processors (NPs) for the in-orbit receive digital beamforming design. We specifically address the beamsteering challenges of high-speed user mobility by means of beamforming adaptation. Inspired by thinned antenna arrays, the proposed beamforming solutions are based on the least absolute shrinkage and selection operator (LASSO) and are adapted to NPs using spiking locally competitive algorithms, namely S-LCA and S-LCA with graded spikes. The proposed approaches can benefit from the energy efficiency of NPs and further reduce the SatCom payload’s power consumption by turning off as many radio frequency chains as possible without compromising the beamforming performance. Numerical experiments conducted on a real-world aeronautical dataset demonstrate that the proposed NP-oriented solutions offer performance on par with conventional optimization algorithms, with the promise of a lower energy expenditure after future implementation on dedicated hardware.