Phase Noise and Polarization Effects in Fiber-Optic Communication Systems: Modeling, Compensation, Capacity, and Sensing
Doctoral thesis, 2024
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 M =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
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
IET Conference Proceedings,;Vol. 2023(2023)p. 1270 -1273
Journal article
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 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.