APSK coded modulation schemes for nonlinear satellite channels with high power and spectral efficiency

A new class of 16-ary Amplitude Phase Shift Keying (APSK) coded modulations deemed double-ring PSK modulations best suited for (satellite) nonlinear channels is proposed. Constellation parameters optimization has been based on geometric and information-theoretic considerations. Furthermore, pre- and post-compensation techniques to reduce the nonlinearity impact have been examined. Digital timing clock and carrier phase have been derived and analyzed for a Turbo coded version of the same new modulation scheme. Finally, the performance of state-of the art Turbo coded modulation for this new 16-ary digital modulation has been investigated and compared to the known TCM schemes. It is shown that for the same coding scheme, double-ring APSK modulation outperforms classical 16-QAM and 16-PSK over a typical satellite nonlinear channel due to its intrinsic robustness against the High Power Amplifier (HPA) nonlinear characteristics. The new modulation is shown to be power- and spectrally-efficient, with interesting applications to satellite communications. © 2002 by the American Institute of Aeronautics and Astronautics, Inc.

Optimization and characterization of the guest-host polyetherketone polymer films for application in integrated optical devices

In order to optimize the loading of 3-(1, 1-dicyanothenyl)-1-phenyl-4, 5-dihydro-1H-pryazole (DCNP) in polyetherketone (PEK-c) guest-host polymer films, ten kinds of DCNP/PEK-c thin films, in which the weight per cent of DCNP changes from 5 to 50, were prepared. Their second-order nonlinear optical coefficients chi(33)((2)) at 1064 nm were measured by Using Maker fringe method after poling under the optimal poling condition. Their optical waveguide transmission losses were measured at 632.8 nm. Optimal weight per cent of the chromophore for the DCNP/PEK-c guest-host polymer system has been determined as about 20 for use in the integrated optical devices.

THEORETICAL TREATMENT OF A3B5 CHLORIDE VAPOR-PHASE EPITAXY - GROWTH, DOPING, OPTIMIZATION

A theoretical description of chloride vapour-phase epitaxy (CVPE) has been proposed which contains two-dimensional (2D) gas-dynamic equations for transport of reactive components and kinetic equations for surface growth processes connected by nonlinear adiabatic boundary conditions. No one of these stages is supposed to be the limiting one. Calculated variations of growth rate and impurity concentrations along the growing layer fit experimental data well.

Algorithm Studies on How to Obtain a Conditional Nonlinear Optimal Perturbation (CNOP)

The conditional nonlinear optimal perturbation (CNOP), which is a nonlinear generalization of the linear singular vector (LSV), is applied in important problems of atmospheric and oceanic sciences, including ENSO predictability, targeted observations, and ensemble forecast. In this study, we investigate the computational cost of obtaining the CNOP by several methods. Differences and similarities, in terms of the computational error and cost in obtaining the CNOP, are compared among the sequential quadratic programming (SQP) algorithm, the limited memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS) algorithm, and the spectral projected gradients (SPG2) algorithm. A theoretical grassland ecosystem model and the classical Lorenz model are used as examples. Numerical results demonstrate that the computational error is acceptable with all three algorithms. The computational cost to obtain the CNOP is reduced by using the SQP algorithm. The experimental results also reveal that the L-BFGS algorithm is the most effective algorithm among the three optimization algorithms for obtaining the CNOP. The numerical results suggest a new approach and algorithm for obtaining the CNOP for a large-scale optimization problem.

Nonlinear piezoelectricity in electroelastic energy harvesters: Modeling and experimental identification

We propose and experimentally validate a first-principles based model for the nonlinear piezoelectric response of an electroelastic energy harvester. The analysis herein highlights the importance of modeling inherent piezoelectric nonlinearities that are not limited to higher order elastic effects but also include nonlinear coupling to a power harvesting circuit. Furthermore, a nonlinear damping mechanism is shown to accurately restrict the amplitude and bandwidth of the frequency response. The linear piezoelectric modeling framework widely accepted for theoretical investigations is demonstrated to be a weak presumption for near-resonant excitation amplitudes as low as 0.5 g in a prefabricated bimorph whose oscillation amplitudes remain geometrically linear for the full range of experimental tests performed (never exceeding 0.25% of the cantilever overhang length). Nonlinear coefficients are identified via a nonlinear least-squares optimization algorithm that utilizes an approximate analytic solution obtained by the method of harmonic balance. For lead zirconate titanate (PZT-5H), we obtained a fourth order elastic tensor component of c1111p =-3.6673× 1017 N/m2 and a fourth order electroelastic tensor value of e3111 =1.7212× 108 m/V. © 2010 American Institute of Physics.

Two-stage mixed discrete-continuous identification of radial basis function (RBF) neural models for nonlinear systems

The identification of nonlinear dynamic systems using radial basis function (RBF) neural models is studied in this paper. Given a model selection criterion, the main objective is to effectively and efficiently build a parsimonious compact neural model that generalizes well over unseen data. This is achieved by simultaneous model structure selection and optimization of the parameters over the continuous parameter space. It is a mixed-integer hard problem, and a unified analytic framework is proposed to enable an effective and efficient two-stage mixed discrete-continuous; identification procedure. This novel framework combines the advantages of an iterative discrete two-stage subset selection technique for model structure determination and the calculus-based continuous optimization of the model parameters. Computational complexity analysis and simulation studies confirm the efficacy of the proposed algorithm.

Two-stage RBF network construction based on particle swarm optimization

The conventional radial basis function (RBF) network optimization methods, such as orthogonal least squares or the two-stage selection, can produce a sparse network with satisfactory generalization capability. However, the RBF width, as a nonlinear parameter in the network, is not easy to determine. In the aforementioned methods, the width is always pre-determined, either by trial-and-error, or generated randomly. Furthermore, all hidden nodes share the same RBF width. This will inevitably reduce the network performance, and more RBF centres may then be needed to meet a desired modelling specification. In this paper we investigate a new two-stage construction algorithm for RBF networks. It utilizes the particle swarm optimization method to search for the optimal RBF centres and their associated widths. Although the new method needs more computation than conventional approaches, it can greatly reduce the model size and improve model generalization performance. The effectiveness of the proposed technique is confirmed by two numerical simulation examples.

Nonlinear time series prediction based on a power-law noise model

In this paper we investigate the influence of a power-law noise model, also called noise, on the performance of a feed-forward neural network used to predict time series. We introduce an optimization procedure that optimizes the parameters the neural networks by maximizing the likelihood function based on the power-law model. We show that our optimization procedure minimizes the mean squared leading to an optimal prediction. Further, we present numerical results applying method to time series from the logistic map and the annual number of sunspots demonstrate that a power-law noise model gives better results than a Gaussian model.

Numerical simulation of a patent technology for sealing of deep-sea oil wells using nonlinear finite element method

For over 50 years bridge plugs and cement have been used for well abandonment and work over and are still the material of choice. However the failures of cement abandonments using bridge plugs has been reported on many occasions, some of which have resulted in fatal consequences. A new patented product is designed to address the shortcomings associated with using bridge plugs and cement. The new developed tools use an alloy based on bismuth that is melted in situ using Thermite reaction. The tool uses the expansion properties of bismuth to seal the well. Testing the new technology in real field under more than 2 km deep sea water can be expensive. Virtual simulation of the new device under simulated thermal and mechanical environment can be achieved using nonlinear finite element method to validate the product and reduce cost. Experimental testing in the lab is performed to measure heat generated due to thermite reaction. Then, a sequential thermal mechanical explicit/implicit finite element solver is used to simulate the device under both testing lab and deep water conditions.

Advanced Modelling and Optimization of Infared Oven in Injection Stretch Blow-moulding for Energy Saving

In the production process of polyethylene terephthalate (PET) bottles, the initial temperature of preforms plays a central role on the final thickness, intensity and other structural properties of the bottles. Also, the difference between inside and outside temperature profiles could make a significant impact on the final product quality. The preforms are preheated by infrared heating oven system which is often an open loop system and relies heavily on trial and error approach to adjust the lamp power settings. In this paper, a radial basis function (RBF) neural network model, optimized by a two-stage selection (TSS) algorithm combined with partial swarm optimization (PSO), is developed to model the nonlinear relations between the lamp power settings and the output temperature profile of PET bottles. Then an improved PSO method for lamp setting adjustment using the above model is presented. Simulation results based on experimental data confirm the effectiveness of the modelling and optimization method.

On Infinite Time Performance of Nonlinear Model Predictive Controllers

This paper addresses the problem of infinite time performance of model predictive controllers applied to constrained nonlinear systems. The total performance is compared with a finite horizon optimal cost to reveal performance limits of closed-loop model predictive control systems. Based on the Principle of Optimality, an upper and a lower bound of the ratio between the total performance and the finite horizon optimal cost are obtained explicitly expressed by the optimization horizon. The results also illustrate, from viewpoint of performance, how model predictive controllers approaches to infinite optimal controllers as the optimization horizon increases.

Improving the robustness of the iterative solver in state-space modelling of guitar distortion circuitry

Iterative solvers are required for the discrete-time simulation of nonlinear behaviour in analogue distortion circuits. Unfortunately,these methods are often computationally too expensive for realtime simulation. Two methods are presented which attempt to reduce the expense of iterative solvers. This is achieved by applying information that is derived from the specific form of the non linearity.The approach is first explained through the modelling of an asymmetrical diode clipper, and further exemplified by application to the Dallas Rangemaster Treble Booster guitar pedal, which provides an initial perspective of the performance on systems with multiple nonlinearities.

Performance Limits of MIMO Systems with Nonlinear Power Amplifiers

The development of 5G enabling technologies brings new challenges to the design of power amplifiers (PAs). In particular, there is a strong demand for low-cost, nonlinear PAs which, however, introduce nonlinear distortions. On the other hand, contemporary expensive PAs show great power efficiency in their nonlinear region. Inspired by this trade-off between nonlinearity distortions and efficiency, finding an optimal operating point is highly desirable. Hence, it is first necessary to fully understand how and how much the performance of multiple-input multiple-output (MIMO) systems deteriorates with PA nonlinearities. In this paper, we first reduce the ergodic achievable rate (EAR) optimization from a power allocation to a power control problem with only one optimization variable, i.e. total input power. Then, we develop a closed-form expression for the EAR, where this variable is fixed. Since this expression is intractable for further analysis, two simple lower bounds and one upper bound are proposed. These bounds enable us to find the best input power and approach the channel capacity. Finally, our simulation results evaluate the EAR of MIMO channels in the presence of nonlinearities. An important observation is that the MIMO performance can be significantly degraded if we utilize the whole power budget.

Design and optimization next generation passive all-optical networks

Este trabalho investiga novas metodologias para as redes óticas de acesso de próxima geração (NG-OAN). O trabalho está dividido em quatro tópicos de investigação: projeto da rede, modelos numéricos para efeitos não lineares da fibra ótica, impacto dos efeitos não lineares da fibra ótica e otimização da rede. A rede ótica de acesso investigada nesse trabalho está projetado para suprir os requisitos de densidade de utilizadores e cobertura, isto é, suportar muitos utilizadores ( 1000) com altas velocidades de conexão dedicada ( 1 Gb/s) ocupando uma faixa estreita do espectro ( 25 nm) e comprimentos de fibra ótica até 100 km. Os cenários são baseados em redes óticas passivas com multiplexagem por divisão no comprimento de onda de alta densidade (UDWDM-PON) utilizando transmissores/receptores coerentes nos terminais da rede. A rede é avaliada para vários ritmos de transmissão usando formatos de modulação avançados, requisitos de largura de banda por utilizador e partilha de banda com tecnologias tradicionais de redes óticas passivas (PON). Modelos numéricos baseados em funções de transferência das séries de Volterra (VSTF) são demonstrados tanto para a análise dos efeitos não lineares da fibra ótica quanto para avaliação do desempenho total da rede. São apresentadas as faixas de potência e distância de transmissão nas quais as séries de Volterra apresentam resultados semelhantes ao modelo referência Split-Step Fourier (SSF) (validado experimentalmente) para o desempenho total da rede. Além disso, um algoritmo, que evita componentes espectrais com intensidade nulo, é proposto para realizar cálculos rápidos das séries. O modelo VSTF é estendido para identificar unicamente os efeitos não lineares da fibra ótica mais relevantes no cenário investigado: Self-Phase Modulation (SPM), Cross-Phase Modulation (XPM) e Four-Wave Mixing (FWM). Simulações numéricas são apresentadas para identificar o impacto isolado de cada efeito não linear da fibra ótica, SPM, XPM e FWM, no desempenho da rede com detecção coerente UDWDM-PON, transportando canais com modulação digital em fase (M-ária PSK) ou modulação digital em amplitude (M-ária QAM). A análise numérica é estendida para diferentes comprimentos de fibra ótica mono modo (SSMF), potência por canal e ritmo de transmissão por canal. Por conseguinte, expressões analíticas são extrapoladas para determinar a evolução do SPM, XPM e FWM em função da potência e distância de transmissão em cenários NG-OAN. O desempenho da rede é otimizada através da minimização parcial da interferência FWM (via espaçamento desigual dos canais), que nesse caso, é o efeito não linear da fibra ótica mais relevante. Direções para melhorias adicionas no desempenho da rede são apresentados para cenários em que o XPM é relevante, isto é, redes transportando formatos de modulação QAM. A solução, nesse caso, é baseada na utilização de técnicas de processamento digital do sinal.