A survey on fiber nonlinearity compensation for 400 Gbps and beyond optical communication systems

Optical communication systems represent the backbone of modern communication networks. Since their deployment, different fiber technologies have been used to deal with optical fiber impairments such as dispersion-shifted fibers and dispersion-compensation fibers. In recent years, thanks to the introduction of coherent detection based systems, fiber impairments can be mitigated using digital signal processing (DSP) algorithms. Coherent systems are used in the current 100 Gbps wavelength-division multiplexing (WDM) standard technology. They allow the increase of spectral efficiency by using multi-level modulation formats, and are combined with DSP techniques to combat the linear fiber distortions. In addition to linear impairments, the next generation 400 Gbps/1 Tbps WDM systems are also more affected by the fiber nonlinearity due to the Kerr effect. At high input power, the fiber nonlinear effects become more important and their compensation is required to improve the transmission performance. Several approaches have been proposed to deal with the fiber nonlinearity. In this paper, after a brief description of the Kerr-induced nonlinear effects, a survey on the fiber nonlinearity compensation (NLC) techniques is provided. We focus on the well-known NLC techniques and discuss their performance, as well as their implementation and complexity. An extension of the inter-subcarrier nonlinear interference canceler approach is also proposed. A performance evaluation of the well-known NLC techniques and the proposed approach is provided in the context of Nyquist and super-Nyquist superchannel systems.Comment: Accepted in the IEEE Communications Surveys and Tutorial

An Overview on Application of Machine Learning Techniques in Optical Networks

Today's telecommunication networks have become sources of enormous amounts of widely heterogeneous data. This information can be retrieved from network traffic traces, network alarms, signal quality indicators, users' behavioral data, etc. Advanced mathematical tools are required to extract meaningful information from these data and take decisions pertaining to the proper functioning of the networks from the network-generated data. Among these mathematical tools, Machine Learning (ML) is regarded as one of the most promising methodological approaches to perform network-data analysis and enable automated network self-configuration and fault management. The adoption of ML techniques in the field of optical communication networks is motivated by the unprecedented growth of network complexity faced by optical networks in the last few years. Such complexity increase is due to the introduction of a huge number of adjustable and interdependent system parameters (e.g., routing configurations, modulation format, symbol rate, coding schemes, etc.) that are enabled by the usage of coherent transmission/reception technologies, advanced digital signal processing and compensation of nonlinear effects in optical fiber propagation. In this paper we provide an overview of the application of ML to optical communications and networking. We classify and survey relevant literature dealing with the topic, and we also provide an introductory tutorial on ML for researchers and practitioners interested in this field. Although a good number of research papers have recently appeared, the application of ML to optical networks is still in its infancy: to stimulate further work in this area, we conclude the paper proposing new possible research directions

Compensation of Laser Phase Noise Using DSP in Multichannel Fiber-Optic Communications

One of the main impairments that limit the throughput of fiber-optic communication systems is laser phase noise, where the phase of the laser output drifts with time. This impairment can be highly correlated across channels that share lasers in multichannel fiber-optic systems based on, e.g., wavelength-division multiplexing using frequency combs or space-division multiplexing. In this thesis, potential improvements in the system tolerance to laser phase noise that are obtained through the use of joint-channel digital signal processing are investigated. To accomplish this, a simple multichannel phase-noise model is proposed, in which the phase noise is arbitrarily correlated across the channels. Using this model, high-performance pilot-aided phase-noise compensation and data-detection algorithms are designed for multichannel fiber-optic systems using Bayesian-inference frameworks. Through Monte Carlo simulations of coded transmission in the presence of moderate laser phase noise, it is shown that joint-channel processing can yield close to a 1 dB improvement in power efficiency. It is further shown that the algorithms are highly dependent on the positions of pilots across time and channels. Hence, the problem of identifying effective pilot distributions is studied.The proposed phase-noise model and algorithms are validated using experimental data based on uncoded space-division multiplexed transmission through a weakly-coupled, homogeneous, single-mode, 3-core fiber. It is found that the performance improvements predicted by simulations based on the model are reasonably close to the experimental results. Moreover, joint-channel processing is found to increase the maximum tolerable transmission distance by up to 10% for practical pilot rates.Various phenomena decorrelate the laser phase noise between channels in multichannel transmission, reducing the potency of schemes that exploit this correlation. One such phenomenon is intercore skew, where the spatial channels experience different propagation velocities. The effect of intercore skew on the performance of joint-core phase-noise compensation is studied. Assuming that the channels are aligned in the receiver, joint-core processing is found to be beneficial in the presence of skew if the linewidth of the local oscillator is lower than the light-source laser linewidth.In the case that the laser phase noise is completely uncorrelated across channels in multichannel transmission, it is shown that the system performance can be improved by applying transmitter-side multidimensional signal rotations. This is found by numerically optimizing rotations of four-dimensional signals that are transmitted through two channels. Structured four-dimensional rotations based on Hadamard matrices are found to be near-optimal. Moreover, in the case of high signal-to-noise ratios and high signal dimensionalities, Hadamard-based rotations are found to increase the achievable information rate by up to 0.25 bits per complex symbol for transmission of higher-order modulations

Nonlinear Distortion in Wideband Radio Receivers and Analog-to-Digital Converters: Modeling and Digital Suppression

Emerging wireless communications systems aim to flexible and efficient usage of radio spectrum in order to increase data rates. The ultimate goal in this field is a cognitive radio. It employs spectrum sensing in order to locate spatially and temporally vacant spectrum chunks that can be used for communications. In order to achieve that, flexible and reconfigurable transceivers are needed. A software-defined radio can provide these features by having a highly-integrated wideband transceiver with minimum analog components and mostly relying on digital signal processing. This is also desired from size, cost, and power consumption point of view. However, several challenges arise, from which dynamic range is one of the most important. This is especially true on receiver side where several signals can be received simultaneously through a single receiver chain. In extreme cases the weakest signal can be almost 100 dB weaker than the strongest one. Due to the limited dynamic range of the receiver, the strongest signals may cause nonlinear distortion which deteriorates spectrum sensing capabilities and also reception of the weakest signals. The nonlinearities are stemming from the analog receiver components and also from analog-to-digital converters (ADCs). This is a performance bottleneck in many wideband communications and also radar receivers. The dynamic range challenges are already encountered in current devices, such as in wideband multi-operator receiver scenarios in mobile networks, and the challenges will have even more essential role in the future.This thesis focuses on aforementioned receiver scenarios and contributes to modeling and digital suppression of nonlinear distortion. A behavioral model for direct-conversion receiver nonlinearities is derived and it jointly takes into account RF, mixer, and baseband nonlinearities together with I/Q imbalance. The model is then exploited in suppression of receiver nonlinearities. The considered method is based on adaptive digital post-processing and does not require any analog hardware modification. It is able to extract all the necessary information directly from the received waveform in order to suppress the nonlinear distortion caused by the strongest blocker signals inside the reception band.In addition, the nonlinearities of ADCs are considered. Even if the dynamic range of the analog receiver components is not limiting the performance, ADCs may cause considerable amount of nonlinear distortion. It can originate, e.g., from undeliberate variations of quantization levels. Furthermore, the received waveform may exceed the nominal voltage range of the ADC due to signal power variations. This causes unintentional signal clipping which creates severe nonlinear distortion. In this thesis, a Fourier series based model is derived for the signal clipping caused by ADCs. Furthermore, four different methods are considered for suppressing ADC nonlinearities, especially unintentional signal clipping. The methods exploit polynomial modeling, interpolation, or symbol decisions for suppressing the distortion. The common factor is that all the methods are based on digital post-processing and are able to continuously adapt to variations in the received waveform and in the receiver itself. This is a very important aspect in wideband receivers, especially in cognitive radios, when the flexibility and state-of-the-art performance is required

Transmissores-recetores de baixa complexidade para redes óticas

Traditional coherent (COH) transceivers allow encoding of information in both quadratures and the two orthogonal polarizations of the electric field. Nevertheless, such transceivers used today are based on the intradyne scheme, which requires two 90o optical hybrids and four pairs of balanced photodetectors for dual-polarization transmission systems, making its overall cost unattractive for short-reach applications. Therefore, SSB methods with DD reception, commonly referred to as self-coherent (SCOH) transceivers, can be employed as a cost-effective alternative to the traditional COH transceivers. Nevertheless, the performance of SSB systems is severely degraded. This work provides a novel SCOH transceiver architecture with improved performance for short-reach applications. In particular, the development of phase reconstruction digital signal processing (DSP) techniques, the development of other DSP subsystems that relax the hardware requirement, and their performance optimization are the main highlights of this research. The fundamental principle of the proposed transceiver is based on the reception of the signal that satisfies the minimum phase condition upon DD. To reconstruct the missing phase information imposed by DD, a novel DCValue method exploring the SSB and the DC-Value properties of the minimum phase signal is developed in this Ph.D. study. The DC-Value method facilitates the phase reconstruction process at the Nyquist sampling rate and requires a low intensity pilot signal. Also, the experimental validation of the DC-Value method was successfully carried out for short-reach optical networks. Additionally, an extensive study was performed on the DC-Value method to optimize the system performance. In the optimization process, it was found that the estimation of the CCF is an important parameter to exploit all advantages of the DC-Value method. A novel CCF estimation technique was proposed. Further, the performance of the DC-Value method is optimized employing the rate-adaptive probabilistic constellation shaping.Os sistemas de transcetores coerentes tradicionais permitem a codificação de informação em ambas quadraturas e em duas polarizações ortogonais do campo elétrico. Contudo, estes transcetores utilizados atualmente são baseados num esquema intradino, que requer dois híbridos óticos de 90o e quatro pares de foto detetores para sistemas de transmissão com polarização dupla, fazendo com que o custo destes sistemas seja pouco atrativo para aplicações de curto alcance. Por isso, métodos de banda lateral única com deteção direta, também referidos como transcetores coerentes simplificados, podem ser implementados como uma alternativa de baixo custo aos sistemas coerentes tradicionais. Contudo, o desempenho de sistemas de banda lateral única tradicionais é gravemente degradado pelo batimento sinal-sinal. Nesta tese foi desenvolvida uma nova arquitetura de transcetor coerente simplificada com um melhor desempenho para aplicações de curto alcance. Em particular, o desenvolvimento de técnicas de processamento digital de sinal para a reconstrução de fase, bem como de outros subsistemas de processamento digital de sinal que minimizem os requerimentos de hardware e a sua otimização de desempenho são o foco principal desta tese. O princípio fundamental do transcetor proposto é baseado na receção de um sinal que satisfaz a condição mínima de fase na deteção direta. Para reconstruir a informação de fase em falta causada pela deteção direta, um novo método de valor DC que explora sinais de banda lateral única e as propriedades DC da condição de fase mínima é desenvolvido nesta tese. O método de valor DC facilita a reconstrução da fase à frequência de amostragem de Nyquist e requer um sinal piloto de baixa intensidade. Além disso, a validação experimental do método de valor DC foi executada com sucesso em ligações óticas de curto alcance. Adicionalmente, foi realizado um estudo intensivo do método de valor DC para otimizar o desempenho do sistema. Neste processo de otimização, verificou-se que o fator de contribuição da portadora é um parâmetro importante para explorar todas as vantagens do método de valor DC. Neste contexto, é proposto um novo método para a sua estimativa. Por último, o desempenho do método de valor DC é otimizado recorrendo a mapeamento probabilístico de constelação com taxa adaptativa.Programa Doutoral em Engenharia Eletrotécnic