Demonstration of Multivariate Photonics: Blind Dimensionality Reduction with Integrated Photonics

Alexander N. Tait, Philip Y. Ma, Thomas Ferreira De Lima, Eric C. Blow, Matthew P. Chang, Mitchell A. Nahmias, Bhavin J. Shastri, Paul R. Prucnal

Research output: Contribution to journalArticle

1 Scopus citations

Abstract

Multi-antenna radio front-ends generate a multi-dimensional flood of information, most of which is partially redundant. Redundancy is eliminated by dimensionality reduction. This class of operations presents harsh fundamental tradeoffs to contemporary digital processing techniques. These tradeoffs can be broken in the analog domain, in which the performance of optical technologies greatly exceeds that of electronic counterparts. Here, we present concepts, methods, and a first demonstration of multivariate photonics: a combination of integrated photonic hardware, analog dimensionality reduction, and blind algorithmic techniques. We experimentally demonstrate 2-channel, 1.0 GHz principal component analysis in a photonic weight bank using recently proposed algorithms for synthesizing the multivariate properties of signals to which the receiver is blind. Novel methods are introduced for controlling blindness conditions in a laboratory context. This work provides a foundation for further research in multivariate photonic information processing, which is poised to play a role in future generations of wireless technology.

Original languageEnglish (US)
Article number8854109
Pages (from-to)5996-6006
Number of pages11
JournalJournal of Lightwave Technology
Volume37
Issue number24
DOIs
StatePublished - Dec 15 2019

All Science Journal Classification (ASJC) codes

  • Atomic and Molecular Physics, and Optics

Keywords

  • Adaptive estimation
  • analog integrated circuits
  • microwave photonics
  • multidimensional signal processing
  • silicon photonics

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