Compensation Of Impairments Research Articles

Nonlinear impairment compensation in multi-channel communication systems based on correlated digital backpropagation with separation of walk-off effect

Digital backpropagation (DBP) is a commonly used method to compensate for the nonlinear impairments of optical fiber channels in the electrical domain, offering a new approach to enhancing the data capacity without affecting the system performance. However, due to the repeated Fourier transform and inverse transform of the split-step Fourier method (SSFM), the complexity of DBP algorithm has increased significantly. In this paper, a correlated backpropagation algorithm with the separation of the walk-off effect is developed, which improves the computational step and significantly reduces the complexity of the algorithm. Simulation results demonstrate that in a 6-channel PDM-16QAM system, the proposed hybrid algorithm reduces the computational complexity by 73.96 % compared to the traditional DBP algorithm for an 800 km transmission.

Planning tools for next-generation DSP-based passive optical networks above 50G [Invited Tutorial

Next-generation optical access networks are evolving towards ultra-high bit rates (above 50 Gbps per wavelength) and extended fiber reach architectures. This trend will likely push the optoelectronics to their limits, thus requiring impairment compensation based on digital signal processing (DSP) techniques in the transceivers. In this paper, which is an invited follow-up of a tutorial given at ECOC 2023, we first present an overview of this evolving scenario and then propose a unified analytical model that is able to predict the performance of these new systems for both direct-detection and coherent transceiver types. We believe that this model can be useful for preliminary scalability studies of new access architectures (as it happens in international standardization bodies). Moreover, when they are deployed, it can be useful as a base for network planning tools, particularly if future transceivers will be, as expected, highly reconfigurable at the DSP level.

Signal Impairments Compensation Based on Wavelength-Shift-Free Optical Phase Conjugation

Signal Impairments Compensation Based on Wavelength-Shift-Free Optical Phase Conjugation

Robust, in-service, and joint monitoring of a dual-polarization transceiver IQ skew for a coherent DSCM system without channel impairment compensation.

A robust, in-service, and joint monitoring of a dual-polarization (DP) transceiver IQ skew for a coherent DSCM system is proposed and experimentally validated. Unlike traditional monitoring schemes, the proposed scheme realizes robust transceiver impairments monitoring without channel impairment compensation, including chromatic dispersion (CD), polarization variation, and carrier phase noise. This enhances the stability and precision of the monitoring process and reduces computational complexity by eliminating sophisticated DSP for impairment compensation. A complex system model for a single-tone signal is given first. Based on the model, the proposed scheme enables monitoring of the DP transmitter and the receiver IQ skew using the inserted frequency domain pilots (FPTs). Experimental results show that the proposed scheme can estimate the transceiver IQ skew within 16 ps with an estimation error of less than 0.2 ps and is robust to CD, polarization variation, phase noise, and amplified spontaneous emission noise. To the best of our knowledge, the proposed scheme achieves in-service transceiver IQ skew monitoring for coherent DSCM systems for the first time.

Characterization of PetM cytochrome b6f subunit 7 domain-containing protein in tomato

Abstract In recent years, multiple advances have been made in understanding the photosynthetic machinery in model organisms. Knowledge transfer to horticultural important fruit crops is challenging and time-consuming due to restrictions in gene editing tools and prolonged life cycles. Here, we characterize a gene encoding a PetM domain-containing protein in tomato. The CRISPR/Cas9 knockout lines of the PetM showed impairment in the chloroplastic electron transport rate (ETR), reduced CO2 assimilation, and reduction of carotenoids and chlorophylls (Chl) under several light conditions. Further, growth-condition-dependent elevation or repression of Chl a/b ratios and de-epoxidation states were identified, underlining possible impairment compensation mechanisms. However, under low light and glasshouse conditions, there were basal levels in CO2 assimilation and ETR, indicating a potential role of the PetM domain in stabilizing the cytochrome b6f complex (Cb6f) under higher light irradiance and increasing its quantum efficiency. This suggests a potential evolutionary role in which this domain might stabilize the site of the Cb6f regulating ratios of cyclic and linear electron transport and its potential importance during the conquest of terrestrial ecosystems during which plants were exposed to higher irradiance. Finally, the results are discussed with regard to metabolism and their implication to photosynthesis from an agronomic perspective.

Fast polarization state tracking for dual-polarization direct detection with Jones-space field recovery.

Direct detection system is expected to possess the phase and polarization diversity in order to achieve high spectral efficiency and fiber impairment compensation such as chromatic dispersion and polarization rotation. In this Letter, we theoretically extend the concept of the proposed Jones-space field recovery (JSFR) to include a dynamic polarization rotation matrix and experimentally demonstrate the rapid polarization state tracking ability of the JSFR receiver based on a 3 × 3 optical coupler. Under a rotation of the state of polarization at a rate of 1 Mrad/s, we successfully transmit 59-GBd dual-polarization 16-ary quadrature-amplitude-modulation signals over an 80-km standard single-mode fiber based on a decision-directed least mean square (DD-LMS) or a recursive least square (DD-RLS), with a bit-error rate below the 14% hard-decision forward error correction threshold of 1 × 10-2. The experimental results indicate that the legacy polarization tracking algorithms designed for coherent optical communication are also applicable for this direct detection scheme. To our best knowledge, this work demonstrates the first polarization rotation-tolerant direct detection system with phase and polarization diversity, providing a low-cost and high-speed solution for short-reach communications.

Data Perspectives in AI-Assisted Fiber-Optic Communication Networks

Machine learning (ML) is widely being regarded as a powerful technology to solve various complex problems in fiberoptic communication networks. Recently, ML algorithms have been considered for a variety of use-cases in optical networks ranging from the design of network devices to the compensation of transmission impairments to predicting network-wide traffic flow patterns. As ML techniques are inherently data driven, the availability of relevant data sets largely dictates the performance of developed ML models. Presently, majority of ML-aided methods in the literature rely either on synthetic data from certain simulation tools or exploit data from some simple laboratory setups. However, developing robust ML-based solutions for real fiber-optic networks demands assembling big data from various parts as well as across different layers and domains of the network. Unfortunately, there is currently a lack of understanding among the research community about various crucial data aspects in practical optical networks as well as key challenges faced. While there has been a plethora of works discussing numerous ML applications in fiber-optic communications and networking, to the best of our knowledge, there is presently no paper which particularly focuses on data perspectives. In this paper, we aim to shed light on various critical data factors by first describing the tools and technologies imperative for adequate network monitoring and data acquisition. We also elucidate different data types, their physical sources, and their applications. Several useful data handling and pre-processing techniques for efficient network data collection, storage, presentation, analysis, etc., are discussed. Major challenges in the generation, transmission, and sharing of the data are highlighted and some potential solutions to the outstanding problems are proposed, thus paving the way for seamless availability of pertinent data sets essential for realizing intelligent data-driven operations in future fiber-optic networks.

Compensation of Phase Noise Impairments in Distributed Acoustic Sensors Based on Optical Pulse Compression Time-Domain Reflectometry

We introduce a method to compensate for the deleterious effects of the phase noise of the laser source on long-range distributed acoustic sensors (DAS) that implement optical pulse compression (OPC). Pulse compression can be used in coherent optical time-domain reflectometry (COTDR) sensors to extend the measurement range without compromising spatial resolution. In fact, OPC-COTDR sensors have demonstrated the longest measurement range to date in passive sensing links that do not require distributed amplification to compensate fiber attenuation. However, it has been found that the limited coherence of the laser source has a degrading effect on the actual performance enhancement that pulse compression can bring because it constrains the maximum duration of the compression waveforms that can be used and makes the use of lasers with extremely low phase noise necessary. We introduce a technique to compensate for the effects of phase noise on OPC-COTDR sensors so that they can demonstrate their full potential for long-range measurements using lasers with less stringent phase noise requirements. The method is based on sampling the phase noise of the laser with an auxiliary interferometer and using this information in a simple signal processing technique to mitigate its deleterious effect on the signal measured. We test our method in an OPC-COTDR sensor that uses 500- <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\mu$</tex-math></inline-formula> s linear frequency modulated pulses to demonstrate 100-km range measurements with 200 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\rm{p}\epsilon /\sqrt{\rm{Hz}}$</tex-math></inline-formula> of strain sensitivity at 2-m initial spatial resolution that becomes 10-m after applying the gauge length. To our knowledge, this is the longest compression waveform demonstrated to date in an OPC-COTDR sensor. Its use provides an extra 20-km range compared to previous demonstrations using laser sources of comparable linewidth. Furthermore, comparable performance is also demonstrated when using a laser source with an order of magnitude larger linewidth.

Learning-Based Traffic Scheduling in Non-Stationary Multipath 5G Non-Terrestrial Networks

In non-terrestrial networks, where low Earth orbit satellites and user equipment move relative to each other, line-of-sight tracking and adapting to channel state variations due to endpoint movements are a major challenge. Therefore, continuous line-of-sight estimation and channel impairment compensation are crucial for user equipment to access a satellite and maintain connectivity. In this paper, we propose a framework based on actor-critic reinforcement learning for traffic scheduling in non-terrestrial networks scenario where the channel state is non-stationary due to the variability of the line of sight, which depends on the current satellite elevation. We deploy the framework as an agent in a multipath routing scheme where the user equipment can access more than one satellite simultaneously to improve link reliability and throughput. We investigate how the agent schedules traffic in multiple satellite links by adopting policies that are evaluated by an actor-critic reinforcement learning approach. The agent continuously trains its model based on variations in satellite elevation angles, handovers, and relative line-of-sight probabilities. We compare the agent’s retraining time with the satellite visibility intervals to investigate the effectiveness of the agent’s learning rate. We carry out performance analysis while considering the dense urban area of Paris, where high-rise buildings significantly affect the line of sight. The simulation results show how the learning agent selects the scheduling policy when it is connected to a pair of satellites. The results also show that the retraining time of the learning agent is up to 0.1times the satellite visibility time at given elevations, which guarantees efficient use of satellite visibility.

Highly Accurate Technique for CO-OFDM Channel Estimation Technique Using Extreme Learning Machine (ELM)

In wireless systems, channel estimation is considered a problematic technology, due to the fact of the difference in time between wireless channels and the noise effect. Orthogonal frequency-division multiplexing (OFDM) is a promising candidate for future optical communications and has received wide concern. The article proposed a Coherent Optical (CO) orthogonal frequency division multiplexing (OFDM) scheme, which gives a scalable and flexible solution for increasing the transmission rate, being extremely robust to chromatic dispersion as well as polarization mode dispersion. Nevertheless, both coherent detection and OFDM are prone to phase noise due to the phase mismatch between the laser oscillators at the transmitter and receiver sides and the relatively long OFDM symbol duration compared to that of single carrier communications. An Extreme Learning Machine (ELM) with Pilot Assisted Equalization (PEM) is proposed for compensation of impairments caused by fibre nonlinearity in coherent optical communication systems. Channel estimation using ELM and the value of distortion is sent to the OSTBC receiving end based on the distortion information the data is decoded and pilot data is removed. FFT is applied to the data and QPSK demodulation is done in the data to get its original form. In addition, the article utilized a free-space optical communication system of multi-input multi-output orthogonal frequency division multiplexing (MIMO-OFDM) with a modified receiver structure. Simulation reveals that the proposed model exhibits significant BER (0.0112) performance and provides better spectral efficiency as compared with conventional systems and less computational complexity. This suggested that the proposed method shows better performance by using the CO-OFDM-FSO-MIMO-ELM-based channel estimation technique for high-speed data communication networks in real-time scenarios respectively.

Compensation of Kerr-induced impairments in silicon nitride third-harmonic generators.

Integrated third-harmonic generators enable on-chip wavelength conversion translating telecom signals to the visible spectrum. Despite the desirable functionality, the device performance is susceptible to phase distortions. Here, we present a design method of compensating the Kerr-induced distortions in third-harmonic generation. The design method yields a chirped Bragg grating theoretically improving the conversion efficiency by ∼30 dB. We envision the design method will pave the way for demonstrating efficient infrared-to-visible upconversion in silicon nitride chips.

Digital Background Compensation of Analog Impairments in Jointly Frequency-Time Interleaved DACs

Digital Background Compensation of Analog Impairments in Jointly Frequency-Time Interleaved DACs

Adaptive Digital Compensation of Analog Impairments in Frequency Interleaved ADC for Next-Generation High-Speed Communication Receivers

Adaptive Digital Compensation of Analog Impairments in Frequency Interleaved ADC for Next-Generation High-Speed Communication Receivers

Optical Field Recovery in Jones Space

Optical full-field recovery allows for fiber impairments compensation such as chromatic dispersion and polarization mode dispersion (PMD) in the digital signal processing. For cost-sensitive short-reach optical networks, some advanced single-polarization (SP) optical field recovery schemes are recently proposed to avoid chromatic dispersion-induced power fading effect and improve the spectral efficiency for larger potential capacity. Polarization division multiplexing (PDM) can further double both the spectral efficiency and the system capacity of these SP carrier-assisted direct detection (DD) schemes. However, the so-called polarization fading phenomenon induced by random polarization rotation is a fundamental obstacle that prevents SP carrier-assisted DD systems from polarization diversity. In this paper, we propose a receiver of Jones-space field recovery (JSFR) to realize polarization diversity with SP carrier-assisted DD schemes. Different receiver structures and simplified recovery procedures for JSFR are explored theoretically. The proposed JSFR pushes SP DD schemes towards PDM without an extra optical signal-to-noise ratio (OSNR) penalty. In addition, the JSFR shows good tolerance to PMD since the optical field recovery is conducted before polarization recovery. In the concept-of-proof experiment, we demonstrate 448-Gb/s reception over 80-km single-mode fiber using the proposed JSFR based on 2 × 2 couplers. Furthermore, we qualitatively compare the optical field recovery in Jones space and Stokes space in terms of the modulation dimension and hardware complexity.

Training Free In-Service Chromatic Dispersion Estimation Using Power Spectrum Analysis for MZM Based IM/DD Optical Communication Systems

In high-speed optical fiber communications, chromatic dispersion (CD) estimation is essential for the monitoring and compensation of CD-induced impairments. Compared with coherent detection, in short-reach optical communication systems, intensity modulation/direct detection (IM/DD) is more widely used, and the existing dispersion estimation techniques usually require training signals or a large amount of data for curve fitting or machine learning. However, these methods cannot provide in-service estimation. This paper presents a novel technique for in-service CD estimation in IM/DD short-reach optical communication systems based on our derived analytical model. With the analytical model, the in-service CD estimation is realized via the direct power spectrum analysis of the received signal. Unlike previous studies that only work with single-frequency sinusoidal signals, the practical random data with the rectangular type of base waveform is considered in our model. Therefore, our method can be applied to the dispersion estimation of various pulse amplitude modulation (PAM) based systems. Our proposed training free in-service CD estimation method is verified and investigated, where results show that better than 0.5% accuracy in dispersion estimation can be achieved in optical communication systems with up to 40 GBaud data rate and 100 km transmission distance.

Nonlinear Impairment Compensation Using Transfer Learning-Assisted Convolutional Bidirectional Long Short-Term Memory Neural Network for Coherent Optical Communication Systems

By combining the nonlinear impairment features derived from the first-order perturbation theory, we propose a nonlinear impairment compensation (NLC) scheme based on the transfer learning-assisted convolutional bidirectional long short-term Memory (CNN-BiLSTM) neural network structure. When considering the correlation of nonlinear impairment between preceding and succeeding consecutive adjacent symbols on the current moment symbol and integrating the multidimensional feature extraction and time memory characteristics of CNN-BiLSTM, the nonlinear impairment information contained in the input feature can be fully utilized to accurately predict the nonlinear impairment showing significant compensation effect. Meanwhile, transfer learning (TL) is introduced to greatly reduce the complexity of the scheme on the basis of high compensation performance. To verify the effectiveness of the proposed scheme, we construct single-channel (SC) and 5-channel 28 GBaud polarization division multiplexing 16 quadrature amplitude modulation (PDM-16QAM)/85 GBaud PDM-64QAM simulation systems, and SC and 3-channel 28 GBaud PDM-16QAM experimental systems. The experimental results show that when compared with simple recurrent neural network (SRNN) NLC and DBP 20 steps per span (DBP20StPs), the Q-factor gain of our scheme is about 1 dB and 1.7 dB in the SC system, and about 1.1 dB and 1.5 dB in the 3-channel system at the optimal launch power, respectively. It is interesting to highlight that, by applying TL to the simulation and experimental systems, our scheme based on only 5% of the training samples can achieve compensation performance comparable to or higher quality than retraining at various launch powers.

Volterra-Aided Neural Network Equalization for Channel Impairment Compensation in Visible Light Communication System

This paper addresses the channel impairment to enhance the system performance of visible light communication (VLC). Inspired by the model-solving procedure in the conventional equalizer, the channel impairment compensation is formulated as a spatial memory pattern prediction problem, then we propose efficient deep-learning (DL)-based nonlinear post-equalization, combining the Volterra-aided convolutional neural network (CNN) and long-short term memory (LSTM) neural network, to mitigate the system nonlinearity and then recover the original transmitted signal from the distorted one at the receiver end. The Volterra structure is employed to construct a spatial pattern that can be easily interpreted by the proposed scheme. Then, we take advantage of the CNN to extract the implicit feature of channel impairments and utilize the LSTM to predict the memory sequence. Results demonstrate that the proposed scheme can provide a fairly fast convergence during the training stage and can effectively mitigate the overall nonlinearity of the system at testing. Furthermore, it can recover the original signal accurately and exhibits an excellent bit error rate performance as compared with the conventional equalizer, demonstrating the prospect and validity of this methodology for channel impairment compensation.

Digital Compensation of IQ Imbalance, DC Offset for Zero-Padded OTFS Systems

Next generation communication systems (e.g., 6G) foresee higher mobility, higher data rates with higher constellations and with high levels of integration in a small form factor. Direct conversion orthogonal time frequency space modulation (OTFS) systems suffer from hardware impairments such as in-phase and quadrature (IQ) imbalance, direct current (DC) offset causing image Doppler interference (IDI) among the sub-carriers in the delay Doppler (DD) domain. In this letter, we propose a novel method of estimation and compensation of hardware impairments for zero padded (ZP) OTFS systems in the delay time (DT) domain. A dual pilot approach with a phase difference of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${\frac {\pi }{2}}$ </tex-math></inline-formula> between these symbols is followed in DD domain with which hardware impairments are estimated with less computational complexity in DT domain. It is found that the compensated system performs close to ideal system. The mean square error (MSE) of the estimated channel is computed and MSE reduces with increase in signal to noise ratio (SNR), pilot power ratio (PPR) and with reduction in mobility.

Beyond 200 Gbit/s/λ VSB PS-PAM8 Employing Joint Neural Network Equalization at C-band

We experimentally demonstrate a high-speed vestigial sideband (VSB) probability shaping 8-ary pulse amplitude modulation (PS-PAM8) system at C-Band. The strong-coupled linear and nonlinear impairments in high-speed VSB transmission systems lead to performance degradation. Neural network-based equalization has been widely adopted in the optical transmission system. However, the effective combination of linear and nonlinear impairment compensation in NN equalization has not been discussed intensively. In this experiment, we have proposed an equalizer based on the joint neural network (JNN) to compensate for the linear and nonlinear impairments. With the proposed JNN equalizer and PS technique, 92 GBaud PS-PAM8 signals can be delivered over 10 km standard single mode fiber (SSMF). Given the forward error correction (FEC) overhead and the entropy of PS-PAM8 signals, the net bit rate can reach 207 Gbit/s/ <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\lambda $ </tex-math></inline-formula> , satisfying the demand for a 200 Gbit/s/ <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\lambda $ </tex-math></inline-formula> data connection.

Performance and Complexity Analysis of Conventional and Deep Learning Equalizers for the High-Speed IMDD PON

To accommodate the exponential growth of network services in the five-generation (5G) and beyond wireless system, 50 Gb/s/λ passive optical network (PON) is developed for mobile xhaul applications. Intensity modulation and direct detection (IMDD) technology together with digital signal procession (DSP) is being considered as the promising solution for 50 Gb/s/λ PON due to its low cost, low power consumption, and compact footprint. Different DSP algorithms with varied structures are proposed for linear and nonlinear impairments compensation in the high-speed PON, while the performance and complexity analysis of these algorithms is still missing. To find the most efficient equalizers, in this paper, four conventional equalizers, including feed-forward equalizer, decision feedback equalizer (DFE), Volterra equalizer (Vol) and Volterra DFE equalizer (Vol-DFE), together with two deep learning equalizers namely fully-connected neural network, and long short-term memory equalizer are experimentally compared in a 10G optics based 50G-PON system in terms of the equalization performance, computation complexity, optimization difficulty, and generalization ability. After the evaluation of our proposed fair comparison algorithm, we consider Vol-DFE is the most efficient one considering both performance and complexity. Attributes to the strong and efficient equalization capability of Vol-DFE, C-band 50 Gb/s PAM-4 signal transmission can be supported in a 10G optics based IMDD system with a 3 dB bandwidth of 6.11 GHz, and a power budget up to 38 dB can be achieved.