Independent Component Analysis (ICA) is a computational technique used in signal processing and data analysis to separate a multivariate signal into additive, independent components. The goal of ICA is to find a linear transformation of the observed data such that the resulting components are statistically independent from each other. In other words, ICA aims to uncover the underlying sources or factors that contribute to the observed data by assuming that the sources are statistically independent.


Real-Time Blind Source Separation with Integrated Photonics for Wireless Signals

We demonstrate, for the first time, real-time blind source separation of interfering GHz transmitters using photonic weights controlled by an RF-System-on-Chip FPGA. This analog system achieves multi-antenna signal separation with millisecond execution latency.