<p> The thesis proposes a novel method for the computation of the design sensitivity of microwave network parameters. The approach is based on the finite-element method. When combined with the iterative update method (the Broyden method) during the gradient-based optimization process, the approach requires practically no overhead for the computation of the response Jacobian, thus accelerating the optimization. </p> <p> The efficiency and accuracy of the gradient-based optimization and the tolerance analysis greatly depend on the computation of the design sensitivity. However, common commercial full-wave electromagnetic solvers do not provide sensitivity information. With them, the design sensitivities are computed from the response themselves using finite-difference or higher-order approximations at the response level. Consequently, for each design parameter of interest, at least one additional full-wave analysis is performed. </p> <p> The proposed self-adjoint sensitivity analysis (SASA) is so far the most efficient way to extract the sensitivity information for the network parameters with the finite-element method. As an improvement of the adjoint-variable method (AVM), it eliminates the additional system analyses. With one single full-wave analysis, the sensitivities with respect to all design parameters are computed. This significantly improves the efficiency of the sensitivity computations. </p> <p> When employed in gradient-based optimization, the computational overhead of the SASA can be further reduced. Instead of the finite-difference approximation, the system matrix derivatives are updated iteratively using the Broyden update. This reduces the computational overhead of the sensitivity analysis to practically zero. Further, several switching criteria between the Broyden update and the finite-difference approximation of the system matrix derivatives is proposed to guarantee the robust convergence of the optimization algorithm. This leads to our Broyden/finite-difference SASA (B/FD-SASA). </p> <p> The efficiency in terms of CPU time as well as the accuracy of the SASA is verified by several numerical examples, where the reference results are provided through the traditional finite-difference approximations. Also, the efficiency of the B/FD-SASA is validated by a filter design example and a microwave imaging example, with implementations exploiting different gradientbased optimization algorithms. </p> / Thesis / Master of Applied Science (MASc)

Includes bibliographical references (leaves 272-279.)

Includes bibliographical references (leaves 272-279.) / xxiv, 279 leaves : ill. ; 30 cm. / Title page, contents and abstract only. The complete thesis in print form is available from the University Library. / Thesis (Ph.D.)--University of Adelaide, Dept. of Electrical and Electronic Engineering, 1997

<p> This thesis proposes a sensitivity solver for frequency-domain electromagnetic (EM) simulators based on volume methods such as the finite-element method (FEM). The proposed sensitivity solver computes S-parameter Jacobians directly from the field solutions available from the EM simulation. It exploits the computational efficiency of the self-adjoint sensitivity analysis (SASA) approach where only one EM simulation suffices to obtain both the responses and their gradients in the designable parameter space. The proposed sensitivity solver adopts the system equations of the finite-difference frequency-domain (FDFD) method.</p> <p> There are three major advantages to this development: (1) the Jacobian computation is completely independent of the simulation engine, its grid and its system equations; (2) the implementation is straightforward and in the form of a post-processing algorithm operating on the exported field solutions; and (3) it is computationally very efficient-time requirements are negligible in comparison with conventional field-based optimization procedures utilizing Jacobians computed via response-level finite differences or parameter sweeps.</p> <p> The accuracy and the efficiency of the proposed sensitivity solver are verified in the sensitivity analysis and the gradient-based optimization of filters and antennas. Compared to the finite-difference approximation, drastic reduction of the time required by the overall optimization process is achieved. All examples use a commercial finite-element simulator.</p> <p> Suggestions for future research are provided.</p> / Thesis / Master of Applied Science (MASc)

Thesis (MScEng (Electrical and Electronic Engineering))--Stellenbosch University, 2008. / The topic for this project entailed the development of a ‘Low Phase Noise – Microwave – Voltage Controlled Oscillator’ for use in radar applications. First of all, a low phase noise oscillator was designed. In order to minimise the phase noise of the oscillator, a high-Q, transmission line – cavity resonator was developed. By derivation it was confirmed that an optimal point for minimum phase noise does exist. The latter was done by evaluating the equation for the output power spectral density of the oscillator phase noise (as defined by Leeson’s Phase Noise Model) at its minimum point. Subsequently, the amount of power that needed to be dissipated inside the resonator could be compared to that dissipated in the source and the load. This identified the amount of coupling to the resonator allowed, assuring minimum phase noise. Since a specific amount of coupling to the resonator was sought after, it had to be practically feasible. Therefore several coupling techniques were investigated to ensure the most user-friendly way of tuning the amount of coupling to the resonator, and hence easily reaching the optimum point of minimum phase noise. After successful completion of the low phase noise oscillator design, it was modified for voltage controlled oscillator (VCO) use by means of variable tuning diodes. These varactor diodes were situated inside the cavity of the resonator. Again the most suitable position to place the diodes had to be determined. The latter was done through considerably detailed transmission line theory; where the loaded Q, the tuning bandwidth (amount of change in frequency reached) and the amount of power dissipated inside the resonator were measured against each other. By means of the necessary phase noise measurements, it was confirmed that in order to keep the phase noise to a minimum, the tuning bandwidth had to be kept small and the amount of power dissipated inside the resonator maximised; so as to keep the overall loaded Q-value of the circuit as high as possible.

In this thesis, a new approach combining neural networks and genetic algorithms is presented for microwave design. In this method, an accurate neural network model is developed from the experimental data. This neural network model is used to perform sensitivity analysis and derive response surfaces. An innovative technique is then applied in which genetic algorithms are coupled with the neural network model to assist in synthesis and optimization. The proposed method is used for modeling and analysis of circuit parameters for flip chip interconnects up to 35 GHz, as well as for design of multilayer inductors and capacitors at 1.9 GHz and 2.4 GHz. The method was also used to synthesize mm wave low pass filters in the range of 40-60 GHz. The devices obtained from layout parameters predicted by the neuro-genetic design method yielded electrical response close to the desired value (95% accuracy). The proposed method also implements a weighted priority scheme to account for tradeoffs in microwave design. This scheme was implemented to synthesize bandpass filters for 802.11a and HIPERLAN wireless LAN applications in the range of 5-6 GHz. This research also develops a novel neuro-genetic design centering methodology for yield enhancement and design for manufacturability of microwave devices and circuits. A neural network model is used to calculate yield using Monte Carlo methods. A genetic algorithm is then used for yield optimization. The proposed method has been used for yield enhancement of SiGe heterojunction bipolar transistor and mm wave voltage-controlled oscillator. It results in significant yield enhancement of the SiGe HBTs (from 25 % to 75 %) and VCOs (from 8 % to 85 %). The proposed method is can be extended for device, circuit, package, and system level integrated co-design since it can handle a large number of design variables without any assumptions about the component behavior. The proposed algorithm could be used by microwave community for design and optimization of microwave circuits and systems with greater accuracy while consuming less computational time.