Current signal processing algorithms excel at impairment compensation when the parameters of optical fiber systems are precisely defined. However, their effectiveness diminishes considerably in the presence of imprecise parameters. By integrating ‘knowledge application from physics to neural networks (NN)’ with ‘information feedback from NNs to physics’, this paper proposes a physics-regulated digital backpropagation (PR-DBP) algorithm, which shows great promise for impairment compensation with imprecise fiber parameters. The PR-DBP employs an optimization-estimation-initialization loop structure. The optimization process provides the network’s adaptability by minimizing the loss value as in conventional NNs. The estimation process dynamically tracks physical parameters by extracting information from NNs to the physical domain. The initialization process offers a physics-based global control over the neural network, thereby mitigating the risk of overfitting by preventing an excessive focus on loss minimization. Moreover, a phase-shift weight function is applied to further improve algorithmic efficiency. Numerical analyses indicate that the PR-DBP significantly outperforms conventional methods in optical fiber systems with imprecise parameters, achieving a bit error rate reduction by an order of magnitude. As a mutually reinforcing part of impairment compensation, a high-accuracy and adaptive fiber parameter estimation is also demonstrated.

Abstract The International Football Association Board decided to introduce Video Assistant Referee (VAR) in 2018. This led to the need to develop methods for quality control of the VAR-systems. This article focuses on the important aspect to evaluate the video quality. Video Quality assessment has matured in the sense that there are standardized, commercial products and established open-source solutions to measure it with objective methods. Previous research has primarily focused on the end-user quality assessment. How to assess the video in the contribution phase of the chain is less studied. The novelties of this study are two-fold: 1) The user study is specifically targeting video experts i.e., to assess the perceived quality of video professionals working with video production. 2) Six video quality models have been independently benchmarked against the user data and evaluated to show which of the models could provide the best predictions of perceived quality. The independent evaluation is important to get unbiased results as shown by the Video Quality Experts Group. An experiment was performed involving 25 video experts in which they rated the perceived quality. The video formats tested were High-Definition TV both progressive and interlaced as well as a quarters size format that was scaled down half the size in both width and height. The videos were encoded with both H.264 and Motion JPEG for the full size but only H.264 for the quarter size. Bitrates ranged from 80 Mbit/s down to 10 Mbit/s. We could see that for H.264 that the quality was overall very good but dropped somewhat for 10 Mbit/s. For Motion JPEG the quality dropped over the whole range. For the interlaced format the degradation that was based on a simple deinterlacing method did receive overall low ratings. For the quarter size three different scaling algorithms were evaluated. Lanczos performed the best and Bilinear the worst. The performance of six different video quality models were evaluated for 1080p and 1080i. The Video Quality Metric for Variable Frame Delay had the best performance for both formats, followed by Video Multimethod Assessment Fusion method and the Video Quality Metric General model.

Nonlinearity is one of the key issues that hinder the development of high-capacity optical short reach systems. This paper proposes three variants of kernel affine projection (KAP) algorithms, all of which combine kernel mapping and affine projection in a reproducing kernel Hilbert space for compensating nonlinear impairments in optical short reach systems. An intensity modulation/direct detection system with a single digital-to-analogue converter, a packaged externally modulated laser and a packaged InP photo-detector is used for experimental demonstration, achieving 238-Gbps (net rate 222-Gbps). Experimental results show that the KAP algorithms can mitigate nonlinear impairments in short-reach communications while maintaining low complexity in reproducing kernel Hilbert space.