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Polina Bayvel

Publications and source records attributed to Polina Bayvel.

At least 19 recordsLinked to original sources
arXiv2026

Energy-Efficient Hollow-Core Fibre Transmission

Hollow-core fibres (HCFs) are a promising means of increasing the throughput of coherent transmission systems. In addition to their advantages in terms of low latency, nonlinearity and attenuation, HCFs can potentially improve the energy efficiency of coherent transmission systems by reducing the number of repeaters and enabling more efficient modulation formats than SMF links. However, the relationship between the link parameters (e.g. launch power, amplifier efficiency and transceiver noise) and the energy efficiency has not been explored. In this work, we investigate energy-efficient operating regimes in HCF transmission systems. We show that the optimum energy per bit in SMF systems is ultimately throughput-limited - maximising throughput will minimise energy per bit. In contrast, the transceiver-limited throughput of HCF leads to two separate launch power optima - minimum-energy-per-bit and maximum-throughput. We derive a closed-form equation for the minimum-energy-per-bit launch power for HCF links in terms of the link parameters, including the amplifier efficiency, transceiver power consumption and link gain. We use our model to explore the impact of span length and fibre attenuation in both operating regimes, showing how energy per bit considerations significantly impact the optimum span length. Optimising for energy efficiency can lead to 50% reduction in link energy per bit for only a 3% throughput penalty at 3000 km, whilst also reducing the required amplifier launch power from >33 dBm to <23 dBm. This work highlights the importance of including physical layer energy considerations in HCF link design.

eess.SP↗
arXiv2026

One Terahertz Full-Field Digital Back-Propagation over 3000 km

We implement full-field digital back-propagation with a 1-THz receiver using 20 synchronous frequency-adjacent coherent receivers with digital stitching and a frequency-comb local oscillator. Relative to electronic dispersion compensation, per-channel DBP and full-field DBP achieve throughput gains of 2.2\% and 5.4\%, respectively.

eess.SP↗
arXiv2026

423.7 + 426.5 Tb/s GMI Bi-Directional HCF Transmission

We demonstrate OESCL-band same-wavelength bi-directional transmission over 60 km HCF with 42.5 THz bandwidth, achieving GMIs comparable with the highest unidirectional SMF data-rates in both directions, with an aggregate of 423.7 + 426.5 Tb/s.

eess.SP↗
arXiv2025

Single-Step Digital Backpropagation for O-band Coherent Transmission Systems

We demonstrate digital backpropagation-based compensation of fibre nonlinearities in the near-zero dispersion regime of the O-band. Single-step DBP effectively mitigates self-phase modulation, achieving SNR gains of up to 1.6 dB for 50 Gbaud PDM-256QAM transmission over a 2-span 151 km SMF-28 ULL fibre link.

eess.SP↗
arXiv2025

A Closed-form Expression of the Gaussian Noise Model Supporting O-Band Transmission

We present a novel closed-form model for nonlinear interference (NLI) estimation in low-dispersion O-band transmission systems. The formulation incorporates the four-wave mixing (FWM) efficiency term as well as the coherent contributions of self- and cross-phase modulation (SPM/XPM) across multiple identical spans. This extension enables accurate evaluation of the NLI in scenarios where conventional closed-form Gaussian Noise (GN) models are limited. The proposed model is validated against split-step Fourier method (SSFM) simulations and numerical integration across 41-161 channels, with a 96 GBaud symbol rate, bandwidths of up to 16.1 THz, and transmission distances from 80 to 800 km. Results show a mean absolute error of the NLI signal-to-noise ratio (SNR) below 0.22 dB. The proposed closed-form model offers an efficient and accurate tool for system optimisation in O-band coherent transmission.

eess.SP↗
arXiv2025

On the Feasibility of SCL-Band Transmission over G.654.E-Compliant Long-Haul Fibre Links

We demonstrate the first SCL-band long-haul transmission using G.654.E-compliant fibre, achieving 100.8 Tb/s (GMI) over 1552 km, despite its 1520 nm cutoff wavelength. Due to the fibre's ultra-low loss and low nonlinearity, the achievable-information-rate with lumped amplification is comparable to that of G.652.D-compliant fibre links with distributed-Raman-amplification.

physics.optics↗
arXiv2025

Reinforcement Learning for Dynamic Resource Allocation in Optical Networks: Hype or Hope?

The application of reinforcement learning (RL) to dynamic resource allocation in optical networks has been the focus of intense research activity in recent years, with almost 100 peer-reviewed papers. We present a review of progress in the field, and identify significant gaps in benchmarking practices and reproducibility. To determine the strongest benchmark algorithms, we systematically evaluate several heuristics across diverse network topologies. We find that path count and sort criteria for path selection significantly affect the benchmark performance. We meticulously recreate the problems from five landmark papers and apply the improved benchmarks. Our comparisons demonstrate that simple heuristics consistently match or outperform the published RL solutions, often with an order of magnitude lower blocking probability. Furthermore, we present empirical lower bounds on network blocking using a novel defragmentation-based method, revealing that potential improvements over the benchmark heuristics are limited to 19-36% increased traffic load for the same blocking performance in our examples. We make our simulation framework and results publicly available to promote reproducible research and standardized evaluation https://doi.org/10.5281/zenodo.12594495.

cs.NI↗
arXiv2024

Topology Bench: Systematic Graph Based Benchmarking for Core Optical Networks

Topology Bench is a comprehensive topology dataset designed to accelerate benchmarking studies in optical networks. The dataset, focusing on core optical networks, comprises publicly accessible and ready-to-use topologies, including (a) 105 georeferenced real-world optical networks and (b) 270,900 validated synthetic topologies. Prior research on real-world core optical networks has been characterised by fragmented open data sources and disparate individual studies. Moreover, previous efforts have notably failed to provide synthetic data at a scale comparable to our present study. Topology Bench addresses this limitation, offering a unified resource and represents a 61.5% increase in spatially-referenced real world optical networks. To benchmark and identify the fundamental nature of optical network topologies through the lens of graph-theoretical analysis, we analyse both real and synthetic networks using structural, spatial and spectral metrics. Our comparative analysis identifies constraints in real optical network diversity and illustrates how synthetic networks can complement and expand the range of topologies available for use. Currently, topologies are selected based on subjective criteria, such as preference, data availability, or perceived suitability, leading to potential biases and limited representativeness. Our framework enhances the generalisability of optical network research by providing a more objective and systematic approach to topology selection. A statistical and correlation analysis reveals the quantitative range of all of these graph metrics and the relationships between them. Finally, we apply unsupervised machine learning to cluster real-world topologies into distinctive groups using nine optimal graph metrics using K-means. We conclude the analysis by providing guidance on how to use such clusters to select a diverse set of topologies for future studies.

cs.NI↗