High-Capacity Space-Division Multiplexing Communications with Silicon Photonic Blind Source Separation

Chaoran Huang, Dongliang Wang, Weipeng Zhang, Benshan Wang, Alexander N. Tait, Thomas Ferreira De Lima, Bhavin J. Shastri, Paul R. Prucnal

Research output: Contribution to journalArticlepeer-review

Abstract

Space-division multiplexing is a widely used technique to improve data-carrying capacities in both wireless and optical communication systems. However, tightly packed spatial channels cause severe crosstalk. High data rates and large channel counts impose severe constraints on resolving the crosstalk using traditional digital signal processing algorithms and electronic circuits. In order to solve these issues, this paper presents a silicon photonic system combining high-speed silicon photonic devices with a novel blind source separation (BSS) algorithm. We first demonstrate using photonic BSS to undo modal crosstalk in a short-reach multimode optical fiber interconnect for intra-data-center communications. The proposed photonic BSS system inherits the advantages of photonic matrix processor and the 'blindness' of BSS, leading to superior energy and cost efficiency and reduced latency, while allowing to recover the signals using a sub-Nyquist sampling rate and in a free-running mode, and offering unmatched agility in signal format and data rate. The feasibility of using photonic processors for mode crosstalk equalization has been recently demonstrated, assisted with training sequences. Our approach, photonic BSS, in contrast, can tackle the more difficult problem of making the receiver transparent to any data rate and modulation format, and workable with slow and cost-effective electronics. In addition, we find that photonic BSS has a much better scaling law for space-division multiplexing (SDM)-based communication systems than digital signal processing (DSP). When compared to state-of-the-art DSP, photonic BSS can reduce system power consumption, speed, and latency by several orders of magnitude, particularly for high-capacity communications with high data rates per channel and a large number of channels. Photonic BSS has the added advantages of being agnostic to transmission content, making it exceptional at protecting communication privacy. This paper also discusses our previous work in demonstrating photonic BSS for privacy protection in wireless multiple-in multiple-out (MIMO) communications using silicon photonic micoring resonator (MRR) weight banks.

Original languageEnglish (US)
Pages (from-to)1617-1632
Number of pages16
JournalJournal of Lightwave Technology
Volume40
Issue number6
DOIs
StatePublished - Mar 15 2022

All Science Journal Classification (ASJC) codes

  • Atomic and Molecular Physics, and Optics

Keywords

  • Machine learning
  • optical signal processing
  • silicon photonics
  • space-division multiplexing

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