Abstract:This research paper delves into interference mitigation within Low Earth Orbit (LEO) satellite constellations, particularly when operating under constraints of limited radio environment information. Leveraging cognitive capabilities facilitated by the Radio Environment Map (REM), we explore strategies to mitigate the impact of both intentional and unintentional interference using planar antenna array (PAA) beamforming techniques. We address the complexities encountered in the design of beamforming weights, a challenge exacerbated by the array size and the increasing number of directions of interest and avoidance. Furthermore, we conduct an extensive analysis of beamforming performance from various perspectives associated with limited REM information: static versus dynamic, partial versus full, and perfect versus imperfect. To substantiate our findings, we provide simulation results and offer conclusions based on the outcomes of our investigation.
Abstract:Devices authentication is one crucial aspect of any communication system. Recently, the physical layer approach radio frequency (RF) fingerprinting has gained increased interest as it provides an extra layer of security without requiring additional components. In this work, we propose an RF fingerprinting based transmitter authentication approach density trace plot (DTP) to exploit device-identifiable fingerprints. By considering IQ imbalance solely as the feature source, DTP can efficiently extract device-identifiable fingerprints from symbol transition trajectories and density center drifts. In total, three DTP modalities based on constellation, eye and phase traces are respectively generated and tested against three deep learning classifiers: the 2D-CNN, 2D-CNN+biLSTM and 3D-CNN. The feasibility of these DTP and classifier pairs is verified using a practical dataset collected from the ADALM-PLUTO software-defined radios (SDRs).