Mixed-Mode Extraction of Figures of Merit for InGaAs Quantum-Well Lasers and SiGe Low-Noise Amplifiers

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We propose a new parameter-extraction approach based on a mixed-mode genetic algorithm (GA), including the efficient search-space separation and local-minima-convergence prevention process. The technique, substantially extended from our previous work, allows the designed figures-of-merit, such as internal quantum efficiency (ηi) as well as transparency current density (Jtr) of lasers and minimum noise figure (NFmin) as well as associated available gain (GA, assoc) of low-noise amplifiers (LNAs), extracted by an analytical equation-based methodology combined with an evolutionary numerical tool. Extraction results, which agree well with actually measured data, for both state-of-the-art InGaAs quantum-well lasers and advanced SiGe LNAs are presented for the first time to demonstrate this multi-parameter analysis and high-accuracy optimization.
2010-11-01