Polarization-aware fiber optic transmisson
Fiber-optic communications forms the basis of the Internet and is such of utmost importance in our society. This project aims at demonstrating novel groundbreaking signaling schemes for such links, that have the potential to dramatically simplify coherent receivers.
Today’s fiber optic transmission links are based on coherent transmission, which transmits data via modulating the two in- phase and quadrature components (I/Q quadratures) in each of the two (horizontal and vertical) transverse polarization components. This gives a four-dimensional (4d) signal space, in which the modulation levels are embedded. One then has an option if one wants to describe this signal via either a complextwo-dimensional (2d) signal (also known as Jones vector) space, or a real 4d signal space. Recent research has shown that the two descriptions are not equivalent, and that the 4d model is richer and allows for more flexible signal transformations. The difference between the 2d complexand the real 4d models originates in the fundamental quantum theory of light, according to which the I/Q quadratures in each polarization component cannot be separated during propagation, in contrast with the two polarization components. Therefore the 2d Jones vector model is sufficient to describe the propagation of the signal (the channel model), but the full 4d model can be taken advantage of in the transmitter and receiver digital signal processing (DSP). An additional difference between the phase quadratures and the polarization components is that the latter drift much slower than the laser phase (milliseconds vs microseconds) in coherent links, making polarization drift much easier to track.
The underlying idea in this project is then to use the full 4d signal space in the transmitter and receiver to create and demonstrate new optical transmission schemes that exploits this known channel difference between, on one hand, the I/Q quadratures, and on the other hand, the polarization components. We chose to call this polarization-aware transmission.
This new approach will enable us to solve a couple of outstanding problems in coherent fiber transmission; one related to signaling ambiguities and one related to differential 4d modulation.
The ambiguity problem deals with the symmetry of the signal constellation, and the problem of determining its correct orientation at the receiver. The four-fold phase ambiguity of quadrature phase-shift keying (QPSK), which gives rise to disastrous cycle-slips during the phase recovery, is the canonical example. The known schemes to deal with this problem either utilize differential modulation (which has not yet been realized for 4d signals) or pilot signals, or trial-and-error schemes. All have the drawback of leading to penalties on the spectral- or power efficiency. We propose that polarization- aware transmission can solve these problems with much less, or even no penalties. A differential 4d modulation scheme would be resilient to both phase and polarization drifts, and can potentially greatly simplify coherent receiver DSP and even eliminate the need for a local oscillator I the receiver.
This project aims to show both ambiguity-free fiber optical transmission as well as differential 4d transmission in fiber optic links via theoretical simulations, as well as via experimental demonstrations in long-distance transmission experiments. Along the way we expect to contribute with novel channel models for optical links. The 4d signal model will also lead to a generalized (and yet unpublished) Stokes-Muller calculus that can account for the common (joint) phase of the two polarization components, with potential applications also in other areas of photonics.
Magnus Karlsson (contact)
Full Professor at Chalmers, Microtechnology and Nanoscience (MC2), Photonics
Full Professor at Chalmers, Electrical Engineering, Communication and Antenna Systems, Communication Systems
Fibre Optic Communications Research Centre (FORCE)
Swedish Research Council (VR)
Project ID: 2015-04239
Funding Chalmers participation during 2016–2019
Related Areas of Advance and Infrastructure
Information and Communication Technology
Areas of Advance