An Explicit Knowledge-Embedded Space Mapping Technique and Its Application to Optimization of LTCC RF Passive Circuits

A novel explicit knowledge embedded space mapping (SM) optimization technique is presented in this paper. It generalizes the implementation procedure of the efficient SM technique by introducing a buffer space called embedded knowledge space between the original coarse model space and the fine model space, where the ingredients of the coarse model space can be completely different from those of the fine model space. Therefore, this generic scheme can be used to map the coarse model space of arbitrary physical content to the fine model space of different physical content through the embedded knowledge space that is built up with the available radio frequency (RF) circuit CAD formula. The emphasis of the application of the proposed scheme is put on the design of low temperature cofired ceramic (LTCC) RF passive circuits in this paper, along with the required CAD formulas (knowledge) for typical embedded multilayer passives. The effectiveness of the proposed new scheme is demonstrated through two design examples of LTCC lumped element band pass filters for wireless applications. The detailed procedure and flowchart of the proposed implementation scheme are also given in the paper.