Synthesis of On-Chip Square Spiral Inductors for RFIC’s using Artificial Neural Network Toolbox and Particle Swarm Optimization

In this paper on-chip square spiral inductors are designed using ANN modeling techniques. Layout geometries form the input of the ANN model and electrical quantities forms the output . The dependency of inductor performances such as inductance (L), quality factor (Q) and self-resonance frequency (SRF) on geometric dimensions are described. Spirals of wide range of RF applications are studied. In our ANN based synthesis approach on-chip spiral inductor layout parameters such as spiral outer diameter(D), width of metal trace(W), number of turns in spiral(N), spacing between the adjutants metal traces(S) are taken as input and Inductance ,Q-factor and Self resonance frequency are the output of our model. Further a PSO based searching algorithm is applied with ANN model for optimization of layout parameters for the electrical parameters. We present several synthesis results which show good accuracy with respect to full-wave electromagnetic (EM) simulations. Since the proposed procedure does not require a time consuming EM simulation in the synthesis loop, it substantially reduces the cycle time in RF-circuit design optimization.