Scalable Wideband Principal Component Analysis via Microwave Photonics

Abstract

Microwave photonics (MWP) provides advantages in bandwidth performance and fan-in scalability that are far superior to electronic counterparts. Processing of many channels at high bandwidths is not easily achievable in any electronic implementation. We consider an MWP system that iteratively performs principal component analysis (PCA) on partially correlated, eight-channel, and 13-GBd signals. The system that is presented is able to adapt to oscillations in interchannel correlations and follow changing principal components. Wideband multidimensional techniques are relevant to > 10-GHz radio systems and could bring solutions for intelligent radio communications and information sensing.

Keywords

• Microwave photonics signal processing
• Optical neural systems
• Information processing