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Polina Bayvel

Publications and source records attributed to Polina Bayvel.

At least 37 records · Page 2Linked to original sources
arXiv2024

Optimising O-to-U Band Transmission Using Fast ISRS Gaussian Noise Numerical Integral Model

We model the transmission of ultrawideband signals, including wavelength-dependent fibre parameters: dispersion, nonlinear coefficient and effective fibre core area. To that end, the inter-channel stimulated Raman scattering Gaussian noise integral model is extended to include these parameters. The integrals involved in this frequency-domain model are numerically solved in hyperbolic coordinates using a Riemann sum. The model implementation is designed to work on parallel GPUs and is optimised for fast computational time. The model is valid for Gaussian-distributed signals and is compared with the split-step Fourier method, for transmission over standard single-mode fibre (SSMF) in the O-band (wavelengths around the zero-dispersion wavelength), showing reasonable agreement. Further, we demonstrated SNR evaluation over an 80~km SSFM single-span transmission using 589x96 GBaud channels, corresponding to almost 59 THz optical bandwidth, fully populating the O, E, S, C, L and U bands (1260-1675 nm). The SNR evaluation is completed in just 3.6 seconds using four Nvidia V100 16GB PCIe GPUs. Finally, we used this model to find the optimum launch power profile for this system achieving 747 Tbps of potential throughput over 80 km fibre and demonstrating its suitability for UWB optimisation routines.

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arXiv2024

Impact of launch power optimisation in hybrid-amplified links

Per-channel launch power optimisation in a hybrid-amplified link with optimised pump powers and wavelengths is described. Compared to using the optimum spectrally uniform launch power, an average SNR gain of 0.13 dB is obtained against 0.56 dB for the same system operating with lumped amplifiers only.

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arXiv2022

High-Cardinality Geometrical Constellation Shaping for the Nonlinear Fibre Channel

This paper presents design methods for highly efficient optimisation of geometrically shaped constellations to maximise data throughput in optical communications. It describes methods to analytically calculate the information-theoretical loss and the gradient of this loss as a function of the input constellation shape. The gradients of the \ac{MI} and \ac{GMI} are critical to the optimisation of geometrically-shaped constellations. It presents the analytical derivative of the achievable information rate metrics with respect to the input constellation. The proposed method allows for improved design of higher cardinality and higher-dimensional constellations for optimising both linear and nonlinear fibre transmission throughput. Near-capacity achieving constellations with up to 8192 points for both 2 and 4 dimensions, with generalised mutual information (GMI) within 0.06 bit/2Dsymbol of additive white Gaussian noise channel (AWGN) capacity, are presented. Additionally, a design algorithm reducing the design computation time from days to minutes is introduced, allowing the presentation of optimised constellations for both linear AWGN and nonlinear fibre channels for a wide range of signal-to-noise ratios.

cs.IT↗
arXiv2020

Experimental Analysis on Variations and Accuracy of Crosstalk in Trench-Assisted Multi-core Fibers

Space division multiplexing using multi-core fiber (MCF) is a promising solution to cope with the capacity crunch in standard single-mode fiber based optical communication systems. Nevertheless, the achievable capacity of MCF is limited by inter-core crosstalk (IC-XT). Many existing researches treat IC-XT as a static interference, however, recent research shows that IC-XT varies with time, wavelength and baud rate. This inherent stochastic feature requires a comprehensive characterization of the behaviour of MCF to its application in practical transmission systems and the theoretical understanding of IC-XT phenomenon. In this paper, we experimentally investigate the IC-XT behaviour of an 8-core trench-assisted MCF in a temperature-controlled environment, using popular modulation formats. We compare the measured results with the theoretical prediction to validate the analytical IC-XT models previously developed. Moreover, we explore the effects of the measurement configurations on the IC-XT accuracy and present an analysis on the IC-XT step distribution. Our results indicate that a number of transmission parameters have significant influence on the strength and volatility of IC-XT. Moreover, the averaging time of the power meter and the observation time window can affect the value of the observed IC-XT, the degrees of the effects vary with the type of the source signals.

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arXiv2020

Geometric Shaping of 2-Dimensional Constellations in the Presence of Laser Phase Noise

In this paper, we propose a geometric shaping (GS) strategy to design 8, 16, 32 and 64-ary modulation formats for the optical fibre channel impaired by both additive white Gaussian (AWGN) and phase noise. The constellations were optimised to maximise generalised mutual information (GMI) using a mismatched channel model. The presented formats demonstrate an enhanced signal-to-noise ratio (SNR) tolerance in high phase noise regimes when compared with their quadrature amplitude modulation (QAM) or AWGN-optimised counterparts. By putting the optimisation results in the context of the 400ZR implementation agreement, we show that GS alone can either relax the laser linewidth (LW) or carrier phase estimation (CPE) requirements of 400 Gbit/s transmission links and beyond. Following the GMI validation, the performance of the presented formats was examined in terms of post forward error correction (FEC) bit-error-rate (BER) for a soft decision (SD) extended Hamming code (128, 120), implemented as per the 400ZR implementation agreement. We demonstrate gains of up to 1.2 dB when compared to the 64-ary AWGN shaped formats.

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arXiv2020

Modelling the delayed nonlinear fiber response in coherent optical communications

Fiber nonlinearities, that lead to nonlinear signal interference (NLI), are typically regarded as an instantaneous material response with respect to the optical field. However, in addition to an instantaneous part, the nonlinear fiber response consists of a delayed contribution, referred to as the Raman response. The imaginary part of its Fourier transform, referred to as the Raman gain spectrum, leads to inter-channel stimulated Raman scattering (ISRS). ISRS is a nonlinear effect that redistributes optical power from high to lower frequencies during propagation. However, as the nonlinear fiber response is causal, the Raman spectrum obeys the Kramers-Kronig relations resulting in the real part of the complex valued Raman spectrum. While the impact of the imaginary part (i.e. ISRS) is well studied, the direct implications of its associated real part on the NLI are unexplored. In this work, a theory is proposed to analytically quantify the impact of the real Raman spectrum on the nonlinear interference power. Starting from a generalized Manakov equation, an extension of the ISRS Gaussian Noise (GN) model is derived to include the real Raman spectrum and, thus, to account for the complete nonlinear Raman response. Accurate integral expressions are derived and approximations in closed-form are proposed. Different formulations for the case of single -and dual polarized signals are derived and novel analytical approximations of the real Raman spectrum are proposed. Moreover, it is analytically shown that the real Raman spectrum scales the strength of the instantaneous nonlinear distortions depending on the frequency separation of the interacting frequencies. A simple functional form is derived to assess the scaling of the NLI strength. The proposed theory is validated by numerical simulations over C-and C+L band, using experimentally measured fiber data.

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arXiv2020

PULSE: Optical circuit switched Data Center architecture operating at nanosecond timescales

We introduce PULSE, a sub-microsecond optical circuit-switched data centre network architecture controlled by distributed hardware schedulers. PULSE is a flat architecture that uses parallel passive coupler-based broadcast and select networks. We employ a novel transceiver architecture, for dynamic wavelength-timeslot selection, to achieve a reconfiguration time down to O(100ps), establishing timeslots of O(10ns). A novel scheduling algorithm that has a clock period of 2.3ns performs multiple iterations to maximize throughput, wavelength usage and reduce latency, enhancing the overall performance. In order to scale, the single-hop PULSE architecture uses sub-networks that are disjoint by using multiple transceivers for each node in 64 node racks. At the reconfiguration circuit duration (epoch = 120 ns), the scheduling algorithm is shown to achieve up to 93% throughput and 100% wavelength usage of 64 wavelengths, incurring an average latency that ranges from 0.7-1.2 microseconds with best-case 0.4 microsecond median and 5 microsecond tail latency, limited by the timeslot (20 ns) and epoch size (120 ns). We show how the 4096-node PULSE architecture allows up to 260k optical channels to be re-used across sub-networks achieving a capacity of 25.6 Pbps with an energy consumption of 85 pJ/bit.

cs.NI↗
arXiv2020

Optical Fiber Communication Systems Based on End-to-End Deep Learning

We investigate end-to-end optimized optical transmission systems based on feedforward or bidirectional recurrent neural networks (BRNN) and deep learning. In particular, we report the first experimental demonstration of a BRNN auto-encoder, highlighting the performance improvement achieved with recurrent processing for communication over dispersive nonlinear channels.

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arXiv2020

Experimental Investigation of Deep Learning for Digital Signal Processing in Short Reach Optical Fiber Communications

We investigate methods for experimental performance enhancement of auto-encoders based on a recurrent neural network (RNN) for communication over dispersive nonlinear channels. In particular, our focus is on the recently proposed sliding window bidirectional RNN (SBRNN) optical fiber autoencoder. We show that adjusting the processing window in the sequence estimation algorithm at the receiver improves the reach of simple systems trained on a channel model and applied "as is" to the transmission link. Moreover, the collected experimental data was used to optimize the receiver neural network parameters, allowing to transmit 42 Gb/s with bit-error rate (BER) below the 6.7% hard-decision forward error correction threshold at distances up to 70km as well as 84 Gb/s at 20 km. The investigation of digital signal processing (DSP) optimized on experimental data is extended to pulse amplitude modulation with receivers performing sliding window sequence estimation using a feed-forward or a recurrent neural network as well as classical nonlinear Volterra equalization. Our results show that, for fixed algorithm memory, the DSP based on deep learning achieves an improved BER performance, allowing to increase the reach of the system.

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arXiv2020

Packet Timescale Wavelength Switching Enabled by Regression Optimisation

A linear regression algorithm is applied to a digital-supermode distributed Bragg reflector laser to optimise wavelength switching times. The algorithm uses the output of a digital coherent receiver as feedback to update the pre-emphasis weights applied to the laser section currents. This permits in-situ calculation without manual weight adjustments. The application of this optimiser to a representative subsection of channels indicates this commercially available laser can rapidly reconfigure over 6.05 THz, supporting 122 channels, in less than 10 ns.

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