Efficient optimization of a Ka-Band MMIC sub-harmonically pumped image rejection diode mixer
An efficient optimization technique, support vector regression (SVR) approach, is proposed for designing of Ka-band MMIC sub-harmonically pumped image rejection diode mixer. This SVR approach comes from the support vector machine (SVM) learning theory, which is based on the structural risk minimization (SRM) principle and leads good generalization ability. With this method, a Ka-band MMIC 4th harmonic image rejection diode mixer is designed using comercial United Monolithic Semiconductors process. Details of design approach and outcome of performance simulations is presented.