FAST gradient based yield optimization of nonlinear circuits

Yield optimization of nonlinear microwave circuits operating in the steady state under large-signal periodic excitations is studied. Two novel high-speed methods of gradient calculation, the integrated gradient approximation technique (IGAT) and the feasible adjoint sensitivity technique (FAST) are introduced. IGAT utilizes the Broyden formula with special iterations of Powell to update the approximate gradients. FAST combines the efficiency and accuracy of the adjoint sensitivity technique with the simplicity of the perturbation technique. IGAT and FAST are compared with the simple perturbation approximate sensitivity technique (PAST) on the one extreme and the theoretical exact adjoint sensitivity technique (EAST) on the other. A FET frequency doubler example treats statistics of both linear elements and nonlinear device parameters. This design has six optimizable variables, including input power and bias conditions, and 34 statistical parameters. Using either IGAT or FAST, yield is driven from 40% to 70%. FAST exhibits superior efficiency