Global optimization of integrated transformers for high frequency microwave circuits using a Gaussian process based surrogate model

Design and optimization of microwave passive components is one of the most critical problems for RF IC designers. However, the state-of-the-art methods either have good efficiency but highly depend on the accuracy of the equivalent circuit models, which may fail the synthesis when the frequency is high; or fully depend on electromagnetic (EM) simulations, whose solution quality is high but are too expensive. To address the problem, a new method, called Gaussian Process-Based Differential Evolution for Constrained Optimization (GPDECO) is proposed. In particular, GPDECO performs global optimization of the microwave structure using EM simulations, and a Gaussian process (GP) based surrogate model is constructed ON-LINE at the same time to predict the results of expensive EM simulations. GPDECO is tested by two 60GHz transformers and comparisons with the state-of-the-art methods are performed. The results show that GPDECO can generate high performance RF passive components that cannot be generated by the available efficient methods. Compared with available methods with the best solution quality, GPDECO can achieve comparable results but only costs 20%-25% of the computational effort. Using parallel computation in an 8-core CPU, the synthesis can be finished in less than 0.5 hour.