Diagonal Kernel Point Estimation of nth-Order Discrete Volterra-Wiener Systems

The estimation of diagonal elements of a Wiener model kernel is a well-known problem. The new operators and notations proposed here aim at the implementation of efficient and accurate nonparametric algorithms for the identification of diagonal points. The formulas presented here allow a direct implementation of Wiener kernel identification up to the th order. Their efficiency is demonstrated by simulations conducted on discrete Volterra systems up to fifth order

Parametric Macromodels of Digital I/O Ports

This paper addresses the development of macromodels for input and output ports of a digital device. The proposed macromodels consist of parametric representations that can be obtained from port transient waveforms at the device ports via a well established procedure. The models are implementable as SPICE subcircuits and their accuracy and efficiency are verified by applying the approach to the characterization of transistor-level models of commercial devices

Parameter and volterra-kernel estimation of bilinear systems

It has been established that bilinear models occur frequently in nature and offer some important advantages from the standpoint. of controllability, optimization and modeling. The estimation of bilinear systeim models from the Measurements of input-output data are discussed. In the first approach a parametric model of a discrete-time linear system is obtained by correlation analysis. The method is extended to bilinear systems using higher- order correlations, It is shown that for a pseudorandom binary input signal the computations in the estimation algorithm can be simplified. The estimates are asymptotically normal unbiased and consistent. The efficiency of the estimates is improved by least-squares fit on a parametric model involving correlation functions. A recursive formulation is given which makes the algorithm attractive for on-line implementation. These methods are compared with maximum-likelihood and least-squares parameter estimation for a model of a nuclear fission process. An experimental furnace to control the temperature of a sample is modeled. The power applied. to the furnace and the rate of air flow inside the chamber are the control variables. Only one input is perturbed at a time with a pseudorandom binary sequence and the linear and the bilinear models of the process are obtained from the input-output measurements. The identification results are used to design a feedforward-feedback programmable controller for the system with constant air flow rates. The second approach is to estimate the first and the second-order kernels in a Volterra series expansion of bilinear systems using correlation analysis. The kernels are estimated for a simulation model of a nuclear fission process. It is seen that the correlation method yields good estimates of the first -order kernel under noisy input -output measurements, However, the second-order kernel estimates are not satisfactory. A new approach to the estimation of the second and the higher-order kernels is then developed. The input-output relation of the bilinear system is represented by an integral-equation. A Wiener-Hopf type equation is obtained by crosscorrelation of the input and the output. An algorithm is given to estimate the unknown parameters in the bilinear operator. The estimation of the second-order kernel is significantly improved

Performance Evaluation of Different DS-CDMA Receivers Using Chaotic Sequences

Direct sequence-code division multiple access (DS-CDMA) technique is used in cellular systems where users in the cell are separated from each other with their unique spreading codes. In recent times DS-CDMA has been used extensively. These systems suffers from multiple access interference (MAI) due to other users transmitting in the cell, channel inter symbol interference (ISI) due to multipath nature of channels in presence of additive white Gaussian noise(AWGN). Spreading codes play an important role in multiple access capacity of DS-CDMA system. M-sequences, gold sequences etc., has been traditionally used as spreading codes in DS-CDMA. These sequences are generated by shift registers and periodic in nature. So these sequences are less in number and also limits the security. This thesis presents an investigation on use of new type of sequences called chaotic sequences for DS-CDMA system. These sequences are generated by chaotic maps. First of all, chaotic sequences are easy to generate and store. Only a few parameters and functions are needed even for very long sequences. In addition, an enormous number of different sequences can be generated simply by changing its initial condition. . Chaotic sequences are deterministic, reproducible, uncorrelated and random-like, which can be very helpful in enhancing the security of transmission in communication. This Thesis investigates the performance of chaotic sequences in DS-CDMA communication systems using various receiver techniques. Extensive simulation studies demonstrate the performance of the different linear and nonlinear DS-CDMA receivers like RAKE receiver, matched filter (MF) receiver, minimum mean square error (MMSE) receiver and Volterra receiver using chaotic sequences and the performance have been compared with gold sequences

Process identification using second order Volterra models for nonlinear model predictive control design of flotation circuits

The control of flotation circuits is a complicated problem, since flotation circuits are nonlinear multivariable processes with a significant degree of interaction between the variables. Isolated PID controllers usually do not perform adequately. The application of a nonlinear model predictive algorithm based on second order Volterra models was investigated. Volterra series models are a higher order extension of linear impulse response models. The nonlinear model predictive control algorithm can also be seen as a linear model predictive controller with higher order correction terms. A dynamic model of a flotation circuit based on the governing continuity equations was developed. The responses obtained represented the qualitative relationships between the model inputs and the controlled variables. This model exhibited strong nonlinearities, including asymmetrical responses to symmetrical inputs and gain sign changes. This dynamic model was treated as the plant to be identified and from which second order Volterra models were obtained. Full Volterra models required excessively large data sets, but significant reductions in the size of the required data set could be achieved if some of the second order coefficients were constrained to zero. These "pruned" Volterra models represented the plant dynamics significantly better than linear models. In particular, these second order Volterra models were able to model asymmetrical responses including gain sign changes. A special case of "pruned" second order Volterra models are diagonal second order models, where all the off-diagonal coefficients (hij where i ≠ j) are constrained to zero. These models required less data than pruned Volterra models containing off-diagonal coefficients, but were less accurate. The performance of nonlinear model predictive controllers based on a pruned second order and diagonal second order Volterra models was evaluated. The performance of these controllers was also compared to the performance obtained with a first order (linear) Volterra model. All three controllers gave equivalent results for large manipulated variable weights. However, when the controllers were tuned more aggressively, results obtained from the three controllers differed considerably. The pruned nonlinear controller performed well even when tuned aggressively while the performance of the linear controller deteriorated. For the case of disturbance rejection, the linear controller performed slightly better than the nonlinear controllers.Dissertation (MEng (Control Engineering))--University of Pretoria, 2006.Chemical Engineeringunrestricte

Advanced digital predistortion of power amplifiers for mobile and wireless communications

This research work focuses on improving the performances of digital predistorters while maintaining low computational complexity for mobile and wireless communication systems. Initially, the thesis presents the fundamental theory of power amplifiers, overview of existing linearisation and memory-effects compensation techniques and reveals the current issues in the field. Further, the thesis depicts the proposed solutions to the problems, including the developed in-band distortion modelling technique, model extraction methods, memoryless digital predistortion technique based on distortion components iterative injection, baseband equalisation technique for minimising memory effects, Matlab-ADS co-simulation system and adaptation circuit with an offline training scheme. The thesis presents the following contributions of the research work. A generalized in-band distortion modelling technique for predicting the nonlinear behaviour of power amplifiers is developed and verified experimentally. Analytical formulae are derived for calculating predistorter parameters. Two model extraction techniques based on the least-squares regression method and frequency-response analysis are developed and verified experimentally. The area of implementation and the trade-off between the methods are discussed. Adjustable memoryless digital predistortion technique based on the distortion components iterative injection method is proposed in order to overcome the distortion compensation limit peculiar to the conventional injection techniques. A baseband equalisation method is developed in order to provide compensation of memory effects for increasing the linearising performance of the proposed predistorter. A combined Matlab-ADS co-simulation system is designed for providing powerful simulation tools. An adaptation circuit is developed for the proposed predistorter for enabling its adaptation to environmental conditions. The feasibility, performances and computational complexity of the proposed digital predistortion are examined by simulations and experimentally. The proposed method is tuneable for achieving the best ratio of linearisation degree to computational complexity for any particular application

Parametric Macromodels of Digital I/O Ports

This paper addresses the development of macromodels for input and output ports of a digital device. The proposed macromodels consist of parametric representations that can be obtained from port transient waveforms at the device ports via a well established procedure. The models are implementable as SPICE subcircuits and their accuracy and efficiency are verified by applying the approach to the characterization of transistor-level models of commercial devices

Advanced digital predistortion of power amplifiers for mobile and wireless communications

This research work focuses on improving the performances of digital predistorters while maintaining low computational complexity for mobile and wireless communication systems. Initially, the thesis presents the fundamental theory of power amplifiers, overview of existing linearisation and memory-effects compensation techniques and reveals the current issues in the field. Further, the thesis depicts the proposed solutions to the problems, including the developed in-band distortion modelling technique, model extraction methods, memoryless digital predistortion technique based on distortion components iterative injection, baseband equalisation technique for minimising memory effects, Matlab-ADS co-simulation system and adaptation circuit with an offline training scheme. The thesis presents the following contributions of the research work. A generalized in-band distortion modelling technique for predicting the nonlinear behaviour of power amplifiers is developed and verified experimentally. Analytical formulae are derived for calculating predistorter parameters. Two model extraction techniques based on the least-squares regression method and frequency-response analysis are developed and verified experimentally. The area of implementation and the trade-off between the methods are discussed. Adjustable memoryless digital predistortion technique based on the distortion components iterative injection method is proposed in order to overcome the distortion compensation limit peculiar to the conventional injection techniques. A baseband equalisation method is developed in order to provide compensation of memory effects for increasing the linearising performance of the proposed predistorter. A combined Matlab-ADS co-simulation system is designed for providing powerful simulation tools. An adaptation circuit is developed for the proposed predistorter for enabling its adaptation to environmental conditions. The feasibility, performances and computational complexity of the proposed digital predistortion are examined by simulations and experimentally. The proposed method is tuneable for achieving the best ratio of linearisation degree to computational complexity for any particular application.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Contribuição ao estudo do impacto das não linearidades nos sistemas de telecomunicações

Doutoramento em Engenharia ElectrotécnicaEsta tese insere-se na área de Electrónica de Rádio Frequência e Microondas e visa o desenvolvimento de ferramentas que permitam a melhor compreensão e análise do impacto da distorção não linear produzida em amplificadores de potência no desempenho de um sistema de telecomunicações sem fios. Devido à crescente complexidade dos amplificadores a simulação baseada em representações de circuito equivalente tornou-se extremamente pesada do ponto de vista computacional. Assim têm surgido várias técnicas de simulação de sistemas baseadas em modelos comportamentais, ou seja, que tentam aproximar a resposta do sistema a um sinal de entrada, independentemente dos elementos físicos que implementam o circuito. Neste trabalho foram estudadas as principais técnicas de modelação comportamental existentes assim como as principais características de um amplificador de potência que o modelo comportamental deve ser capaz de prever. Uma nova formulação de um modelo comportamental baseado na série de Volterra é apresentada em conjunto com o método de extracção ortogonal dos seus coeficientes. A principal vantagem deste novo método de extracção é permitir a determinação independente de cada valor coeficiente na série, garantindo-se deste modo um modelo com uma capacidade de aproximação óptima. A determinação dos coeficientes na série de modo independente é conseguida com base na reorganização dos termos da série e na identificação ortogonal de cada componente de saída. Adicionalmente, a identificação das componentes de saída de uma não linearidade é ainda utilizada na definição de uma métrica que permite avaliar de modo simples qual é a degradação imposta à qualidade do sinal ao ser passado num amplificador não linear. Esta métrica contabiliza simultaneamente a degradação imposta pelo ruído e pela distorção.This thesis is related to the RF and Microwave Electronics field and the main goal of this thesis is to develop tools that can contribute to understand and analyse the impact of nonlinear distortion generated by power amplifiers on wireless communication systems. Due to the growing complexity of amplifiers, equivalent circuit based simulations become a heavy computational task due to the large number of nonlinear elements to account for. So, several system simulation techniques have been proposed based on behavioural modelling, that is, models that can approximate the system’s response to a given input signal regardless of the physical circuit implementation description. In this thesis, the most important behavioural modelling techniques have been studied as well as the main power amplifier characteristics that the behavioural model should account for. A new formulation of a Volterra series based behavioural model is presented as well as the corresponding coefficient orthogonal extraction procedure. The main advantage of this new extraction method is to allow the independent determination of the exact value of each coefficient, guaranteeing this way an optimum approximation condition. The exact coefficient determination is achieved by reorganizing the series terms to reach independent subsets and by identifying separately each of systems’ output components. In addition, nonlinearity output component separation is also used to define a Figure of Merit that allows the simple evaluation of signal quality degradation when passed through a nonlinear amplifier. This Figure takes into account simultaneously the impact of noise and distortion.FCTFS