1,671 research outputs found

    Blind adaptive equalization for QAM signals: New algorithms and FPGA implementation.

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    Adaptive equalizers remove signal distortion attributed to intersymbol interference in band-limited channels. The tap coefficients of adaptive equalizers are time-varying and can be adapted using several methods. When these do not include the transmission of a training sequence, it is referred to as blind equalization. The radius-adjusted approach is a method to achieve blind equalizer tap adaptation based on the equalizer output radius for quadrature amplitude modulation (QAM) signals. Static circular contours are defined around an estimated symbol in a QAM constellation, which create regions that correspond to fixed step sizes and weighting factors. The equalizer tap adjustment consists of a linearly weighted sum of adaptation criteria that is scaled by a variable step size. This approach is the basis of two new algorithms: the radius-adjusted modified multitmodulus algorithm (RMMA) and the radius-adjusted multimodulus decision-directed algorithm (RMDA). An extension of the radius-adjusted approach is the selective update method, which is a computationally-efficient method for equalization. The selective update method employs a stop-and-go strategy based on the equalizer output radius to selectively update the equalizer tap coefficients, thereby, reducing the number of computations in steady-state operation. (Abstract shortened by UMI.) Source: Masters Abstracts International, Volume: 45-01, page: 0401. Thesis (M.A.Sc.)--University of Windsor (Canada), 2006

    Equalização digital para sistemas de transmissão ópticos coerentes

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    This thesis focus on the digital equalization of fiber impairments for coherent optical transmission systems. New efficient and low-complexity equalization and mitigation techniques that counteract fiber nonlinear impairments are proposed and the tradeoff between performance and complexity is numerically assessed and experimentally demonstrated in metro and long-haul 400G superchannels-based transmission systems. Digital backpropagation (DBP) based on low-complexity split-step Fourier method and Volterra series nonlinear equalizers are experimentally assessed in an uniform superchannel system. In contrast with standard DBP methods, these techniques prove to be able to be implemented with larger step-sizes, consequently requiring a reduced number of multiplications, and still achieve a significant reach extension over linear equalization techniques. Moreover, given its structure, the complexity of the proposed Volterra-based DBP approach can be easily adjusted by changing the nonlinear filter dimension according to the system requirements, thus providing a higher flexibility to the nonlinear equalization block. A frequency-hybrid superchannel envisioning near-future flexible networks is then proposed as a way to increase the system bit-rate granularity. The problematic of the power-ratio between superchannel carriers is addressed and optimized for linear and nonlinear operation regimes using three distinct FEC paradigms. Applying a single FEC to the entire superchannel has a simpler implementation and is found to be a more robust approach, tolerating larger uncertainties on the system parameters optimization. We also investigate the performance gain provided by the application of different DBP techniques in frequency-hybrid superchannel systems, and its implications on the optimum power-ratio. It is shown that the application of DBP can be restricted to the carrier transporting the higher cardinality QAM format, since the DBP benefit on the other carriers is negligible, which might bring a substantially complexity reduction of the DBP technique applied to the superchannel.A presente tese foca-se na equalização digital das distorções da fibra para sistemas óticos de transmissão coerente. São propostas novas técnicas eficientes e de baixa complexidade para a equalização e mitigação das distorções não lineares da fibra, e o compromisso entre desempenho e complexidade é testado numericamente e demonstrado experimental em sistemas de transmissão metro e longa distância baseados em supercanais 400G. A propagação digital inversa baseada no método de split-step Fourier e equalizadores não lineares de séries de Volterra de baixa complexidade são testadas experimentalmente num sistema baseado em supercanais uniformes. Ao contrário dos métodos convencionais utilizados, estas técnicas podem ser implementadas utilizando menos interações e ainda extender o alcance do sistema face às técnicas de equalização linear. Para além disso, a complexidade do método baseado em Volterra pode ser facilmente ajustada alterando a dimensão do filtro não linear de acordo com os requisitos do sistema, concedendo assim maior flexibilidade ao bloco de equalização não linear. Tendo em vista as futuras redes flexı́veis, um supercanal hı́brido na frequência é proposto de modo a aumentar a granularidade da taxa de transmissão do sistema. A problemática da relação de potência entre as portadoras do supercanal é abordada e optimizada em regimes de operação linear e não linear utilizando paradigmas diferentes de códigos correctores de erros. A aplicação de um único código corrector de erros à totalidade do supercanal mostra ser a abordagem mais robusta, tolerando maiores incertezas na optimização dos parâmetros do sistema. O ganho de desempenho dado pela aplicação de diferentes técnicas de propagação digital inversa em sistemas de supercanais hı́bridos na frequência é tamém analizado, assim como as suas implicações na relação óptima de potência. Mostra-se que esta pode ser restringida à portadora que transporta o formato de modulação de ordem mais elevada, uma vez que o benefı́cio trazido pelas restantes portadotas é negligenciável, permitindo reduzir significativamente a complexidade do algoritmo aplicado.Programa Doutoral em Telecomunicaçõe

    A Mobile Wireless Channel State Recognition Algorihm: Introduction, Definition, and Verification - Sensing for Cognitive Environmental Awareness

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    This research includes mobile wireless systems limited by time and frequency dispersive channels. A blind mobile wireless channel (MWC) state recognition (CSR) algorithm that detects hidden coherent nonselective and noncoherent selective processes is verified. Because the algorithm is blind, it releases capacity based on current channel state that traditionally is fixed and reserved for channel gain estimation and distortion mitigation. The CSR algorithm enables cognitive communication system control including signal processing, resource allocation/deallocation, or distortion mitigation selections based on channel coherence states. MWC coherent and noncoherent states, ergodicity, stationarity, uncorrelated scattering, and Markov processes are assumed for each time block. Furthermore, a hidden Markov model (HMM) is utilized to represent the statistical relationships between hidden dispersive processes and observed receive waveform processes. First-order and second-order statistical extracted features support state hard decisions which are combined in order to increase the accuracy of channel state estimates. This research effort has architected, designed, and verified a blind statistical feature recognition algorithm capable of detecting coherent nonselective, single time selective, single frequency selective, or dual selective noncoherent states. A MWC coherence state model (CSM) was designed to represent these hidden dispersive processes. Extracted statistical features are input into a parallel set of trained HMMs that compute state sequence conditional likelihoods. Hard state decisions are combined to produce a single most likely channel state estimate for each time block. To verify the CSR algorithm performance, combinations of hidden state sequences are applied to the CSR algorithm and verified against input hidden state sequences. State sequence recognition accuracy sensitivity was found to be above 99% while specificity was determined to be above 98% averaged across all features, states, and sequences. While these results establish the feasibility of a MWC blind CSR algorithm, optimal configuration requires future research to further improve performance including: 1) characterizing the range of input signal configurations, 2) waveform feature block size reduction, 3) HMM parameter tracking, 4) HMM computational complexity and latency reduction, 5) feature soft decision combining, 6) recursive implementation, 7) interfacing with state based mobile wireless communication control processes, and 8) extension to wired or wireless waveform recognition

    Optics for AI and AI for Optics

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    Artificial intelligence is deeply involved in our daily lives via reinforcing the digital transformation of modern economies and infrastructure. It relies on powerful computing clusters, which face bottlenecks of power consumption for both data transmission and intensive computing. Meanwhile, optics (especially optical communications, which underpin today’s telecommunications) is penetrating short-reach connections down to the chip level, thus meeting with AI technology and creating numerous opportunities. This book is about the marriage of optics and AI and how each part can benefit from the other. Optics facilitates on-chip neural networks based on fast optical computing and energy-efficient interconnects and communications. On the other hand, AI enables efficient tools to address the challenges of today’s optical communication networks, which behave in an increasingly complex manner. The book collects contributions from pioneering researchers from both academy and industry to discuss the challenges and solutions in each of the respective fields

    Tecnologias coerentes para redes ópticas flexíveis

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    Next-generation networks enable a broad range of innovative services with the best delivery by utilizing very dense wired/wireless networks. However, the development of future networks will require several breakthroughs in optical networks such as high-performance optical transceivers to support a very-high capacity optical network as well as optimization of the network concept, ensuring a dramatic reduction of the cost per bit. At the same time, all of the optical network segments (metro, access, long-haul) need new technology options to support high capacity, spectral efficiency and data-rate flexibility. Coherent detection offers an opportunity by providing very high sensitivity and supporting high spectral efficiency. Coherent technology can still be combined with polarization multiplexing. Despite the increased cost and complexity, the migration to dual-polarization coherent transceivers must be considered, as it enables to double the spectral efficiency. These dual-polarization systems require an additional digital signal processing (DSP) subsystem for polarization demultiplexing. This work seeks to provide and characterize cost-effective novel coherent transceivers for the development of new generation practical, flexible and high capacity transceivers for optical metro-access and data center interconnects. In this regard, different polarization demultiplexing (PolDemux) algorithms, as well as adaptive Stokes will be considered. Furthermore, low complexity and modulation format-agnostic DSP techniques based on adaptive Stokes PolDemux for flexible and customizable optical coherent systems will be proposed. On this subject, the performance of the adaptive Stokes algorithm in an ultra-dense wavelength division multiplexing (U-DWDM) system will be experimentally evaluated, in offline and real-time operations over a hybrid optical-wireless link. In addition, the efficiency of this PolDemux algorithm in a flexible optical metro link based on Nyquist pulse shaping U-DWDM system and hybrid optical signals will be assessed. Moreover, it is of great importance to find a transmission technology that enables to apply the Stokes PolDemux for long-haul transmission systems and data center interconnects. In this work, it is also proposed a solution based on the use of digital multi-subcarrier multiplexing, which improve the performance of long-haul optical systems, without increasing substantially, their complexity and cost.As redes de telecomunicações futuras permitirão uma ampla gama de serviços inovadores e com melhor desempenho. No entanto, o desenvolvimento das futuras redes implicará vários avanços nas redes de fibra ótica, como transcetores óticos de alto desempenho capazes de suportar ligações de muito elevada capacidade, e a otimização da estrutura da rede, permitindo uma redução drástica do custo por bit transportado. Simultaneamente, todos os segmentos de rede ótica (metropolitanas, acesso e longo alcance) necessitam de novas opções tecnológicas para suportar uma maior capacidade, maior eficiência espetral e flexibilidade. Neste contexto, a deteção coerente surge como uma oportunidade, fornecendo alta sensibilidade e elevada eficiência espetral. A tecnologia de deteção coerente pode ainda ser associada à multiplexação na polarização. Apesar de um potencial aumento ao nível do custo e da complexidade, a migração para transcetores coerentes de dupla polarização deve ser ponderada, pois permite duplicar a eficiência espetral. Esses sistemas de dupla polarização requerem um subsistema de processamento digital de sinal (DSP) adicional para desmultiplexagem da polarização. Este trabalho procura fornecer e caracterizar novos transcetores coerentes de baixo custo para o desenvolvimento de uma nova geração de transcetores mais práticos, flexíveis e de elevada capacidade, para interconexões óticas ao nível das futuras redes de acesso e metro. Assim, serão analisados diferentes algoritmos para a desmultiplexagem da polarização, incluindo uma abordagem adaptativa baseada no espaço de Stokes. Além disso, são propostas técnicas de DSP independentes do formato de modulação e de baixa complexidade baseadas na desmultiplexagem de Stokes adaptativa para sistemas óticos coerentes flexíveis. Neste contexto, o desempenho do algoritmo adaptativo de desmultiplexagem na polarização baseado no espaço de Stokes é avaliado experimentalmente num sistema U-DWDM, tanto em análises off-line como em tempo real, considerando um percurso ótico hibrido que combina um sistema de transmissão suportado por fibra e outro em espaço livre. Foi ainda analisada a eficiência do algoritmo de desmultiplexagem na polarização numa rede ótica de acesso flexível U-DWDM com formatação de pulso do tipo Nyquist. Neste trabalho foi ainda analisada a aplicação da técnica de desmultiplexagem na polarização baseada no espaço de Stokes para sistemas de longo alcance. Assim, foi proposta uma solução de aplicação baseada no uso da multiplexagem digital de múltiplas sub-portadoras, tendo-se demonstrado uma melhoria na eficiência do desempenho dos sistemas óticos de longo alcance, sem aumentar significativamente a respetiva complexidade e custo.Programa Doutoral em Engenharia Eletrotécnic

    Turbo multiuser detection with integrated channel estimation for differentially coded CDMA systems.

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    An Overview on Application of Machine Learning Techniques in Optical Networks

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    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
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