Automated Construction of Macromodels from Frequency Data for Simulation of Distributed Interconnect Networks
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As the complexity of interconnects and packages increases and the rise and fall time of the signal decreases, the electromagnetic effects of distributed passive devices are becoming an important factor in determining the performance of gigahertz systems. The electromagnetic behavior extracted using an electromagnetic simulation or from measurements is available as frequency dependent data. This information can be represented as a black box called a macromodel, which captures the behavior of the passive structure at the input/output ports. In this dissertation, the macromodels have been categorized as scalable, passive and broadband macromodels. The scalable macromodels for building design libraries of passive devices have been constructed using multidimensional rational functions, orthogonal polynomials and selective sampling. The passive macromodels for time-domain simulation have been constructed using filter theory and multiport passivity formulae. The broadband macromodels for high-speed simulation have been constructed using band division, selector, subband reordering, subband dilation and pole replacement. An automated construction method has been developed. The construction time of the multiport macromodel has been reduced. A method for reducing the order of the macromodel has been developed. The efficiency of the methods was demonstrated through embedded passive devices, known transfer functions and distributed interconnect networks.