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Optimal characterization of a microwave transistor using grey wolf algorithms

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SPRINGER
DOI: 10.1007/s10470-021-01914-y

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Meta-heuristic algorithm; Grey wolf; Low noise amplifier; Multi-objective optimization

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Modern microwave stages require high-performance LNA designs which can be achieved through optimization using meta-heuristic algorithms, specifically in selecting the optimal source and load terminations to meet the required performance measures.
Modern time microwave stages require low power consumption, low size, low-noise amplifier (LNA) designs with high-performance measures. These demands need a single transistor LNA design, which is a challenging multi-objective, multi-dimensional optimization problem that requires solving objectives with non-linear feasible design target space, that can only be achieved by optimally selecting the source (Z(S)) and load (Z(L)) terminations. Meta-heuristic algorithms (MHAs) have been extensively used as a search and optimization method in many problems in the field of science, commerce, and engineering. Since feasible design target space (FDTS) of an LNA transistor (NE3511S02 biased at VDS = 2 V and IDS = 7 mA) is a multi-objective multi-variable optimization problem the MHA can be considered as a suitable choice. Three different types of grey wolf variants inspired algorithms had been applied to the LNA FDTS problem to obtain the optimal source and load terminations that satisfies the required performance measures of the aimed LNA design. Furthermore, the obtained results are justified via the use of the Electromagnetic Simulator tool AWR. As a result, an efficient optimization method for optimal determination of Z(S) and Z(L) terminations of a high-performance LNA design had been achieved.

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