Phase Noise and Polarization Effects in Fiber-Optic Communication Systems: Modeling, Compensation, Capacity, and Sensing
Doctoral thesis, 2024

High data rate optical communications are susceptible to phase noise and state of polarization (SOP) perturbations. The dynamic nature of phase noise and SOP fluctuations requires a comprehensive investigation of their effects on the channel capacity and the development of robust and efficient communication technologies. This thesis unravels phase and polarization challenges in optical communication systems by characterizing polarization drift channels, introducing polarization tracking algorithms, utilizing polarization data for fiber sensing, and investigating capacity implications. 

The SOP drifts at a much slower rate than typical transmission rates in buried or underwater fibers. Thus, we first characterize the capacity of the block-constant polarization drift channel under an average power constraint and imperfect channel knowledge. An achievable information rate is derived, showing strong dependence on the channel estimation technique. A novel data-aided channel estimator is proposed, enforcing the unitary constraint, and its superior performance is validated through Monte Carlo simulations. However, in aerial fibers, the SOP drift does not follow the block-constant assumption and can drift quickly over time. Hence, the next contribution involves investigating the robustness of polarization tracking algorithms in the presence of fast SOP drift and polarization-dependent loss. Novel tracking algorithms are proposed, showing a higher tolerance to SOP drift compared to the gradient descent-based algorithms without the need for parameter tuning. Thereafter, we explore the application of polarization for fiber sensing by proposing a physics-based learning approach. The proposed approach shows lower sensitivity to additive noise compared to previous inverse scattering methods.

Next, we turn our attention to phase noise and investigate the capacity of a discrete-time multiple-input-multiple-output channel with correlated phase noises originating from electro-optic frequency combs (EO-comb). We derive capacity bounds and show that the multiplexing gain is M - 1 where M is the number of channels. Moreover, a constant gap between the bounds is observed in the high signal-to-noise ratio regime, which vanishes for the special case of =2. Finally, we study optimal pilot placement for channels impaired by phase noise from EO-combs. Contrary to regular multichannel systems, it is demonstrated that allocating the first and last channels for pilots is optimal under a fixed pilot overhead.

electro-optic frequency comb

Capacity

mismatched decoding

duality bound

phase noise

polarization dependent loss

fiber sensing

polarization drift

EA lecture hall, Hörsalsvägen 11, staircase C, floor 4.
Opponent: Prof. Gerhard Kramer, Department of Computation, Information and Technology, Technical University of Munich, Germany.

Author

Mohammad Farsi

Chalmers, Electrical Engineering, Communication, Antennas and Optical Networks

Capacity Bounds under Imperfect Polarization Tracking

IEEE Transactions on Communications,; Vol. 70(2022)p. 7240-7249

Journal article

Polarization Tracking in the Presence of PDL and Fast Temporal Drift

Journal of Lightwave Technology,; Vol. 40(2022)p. 6408-6416

Journal article

Farsi, M., Joudeh, H., Liga, G., Alvarado, A., Karlsson, M., and Agrell, E., ``On the Capacity of Correlated MIMO Phase-Noise Channels: An Electro-Optic Frequency Comb Example'', Submitted to IEEE Transactions on Information Theory, May 2024.

Pilot distributions for phase noise estimation in electro-optic frequency comb systems

European Conference on Optical Communication, ECOC,; (2023)

Paper in proceeding

Learning to Extract Distributed Polarization Sensing Data from Noisy Jones Matrices

2024 Optical Fiber Communication Conference and Exhibition, OFC 2024 - Proceeding,; (2024)

Paper in proceeding

When we talk about ``Channel Capacity," think of it like a pipe's ability to handle water flow. Just as a pipe can only transfer a certain flow of water, different communication mediums like wires, radio waves, or fiber optics have limits on how many bits of information they can transfer per time unit. The capacity of a channel is not about what goes in, but about how the channel is formed. For example, trying to fill a pipe with rocks will not achieve the pipe's capacity, but using water will. The channel capacity depends on the inherent properties of the channel, just like the pipe's capacity, which depends on its diameter, shape, and material.

When using optical fiber as a communication medium, many inherent impairments in a fiber can potentially limit its capacity. These impairments can be imagined as obstacles that jam into the pipe or physical phenomena that change the shape of the pipe and limit the water flow.


This thesis dives into the phase and polarization impairments within optical fiber communication systems and examines how these flaws affect the channel's capacity. It also proposes new methods to mitigate these impairments. Additionally, it explores machine-learning techniques to analyze polarization data, helping to detect physical changes in the environment surrounding a fiber optic cable.

Unlocking the Full-dimensional Fiber Capacity

Knut and Alice Wallenberg Foundation (KAW 2018.0090), 2019-07-01 -- 2024-06-30.

Areas of Advance

Information and Communication Technology

Nanoscience and Nanotechnology

Subject Categories

Telecommunications

Communication Systems

Probability Theory and Statistics

Other Electrical Engineering, Electronic Engineering, Information Engineering

Roots

Basic sciences

Infrastructure

C3SE (Chalmers Centre for Computational Science and Engineering)

ISBN

978-91-8103-051-8

Doktorsavhandlingar vid Chalmers tekniska högskola. Ny serie: 5509

Publisher

Chalmers

EA lecture hall, Hörsalsvägen 11, staircase C, floor 4.

Opponent: Prof. Gerhard Kramer, Department of Computation, Information and Technology, Technical University of Munich, Germany.

More information

Latest update

5/13/2024