Joseph Barkate, Alexander Tsatsoulas, C. Baylis, L. Cohen, R. Marks
{"title":"Comparison of multidimensional circuit optimization techniques for real-time transmitter use","authors":"Joseph Barkate, Alexander Tsatsoulas, C. Baylis, L. Cohen, R. Marks","doi":"10.1109/WMCAS.2016.7577485","DOIUrl":null,"url":null,"abstract":"In reconfigurable transmitter amplifiers, it is often desirable to simultaneously optimize multiple circuit characteristics, including load impedance, input power, and bias voltages. We compare different algorithms for multi-parameter circuit optimization using the Smith Tube. Comparison is performed between gradient, pattern, and simplex searches in 2, 3, 4, and 5 dimensions. While simplex performs very well in lower dimensions, its usefulness significantly decreases for higher dimensions. Gradient search is shown through these comparisons to provide the best results in five dimensions for the types of searches and starting points examined in this work.","PeriodicalId":227955,"journal":{"name":"2016 Texas Symposium on Wireless and Microwave Circuits and Systems (WMCS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 Texas Symposium on Wireless and Microwave Circuits and Systems (WMCS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WMCAS.2016.7577485","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
In reconfigurable transmitter amplifiers, it is often desirable to simultaneously optimize multiple circuit characteristics, including load impedance, input power, and bias voltages. We compare different algorithms for multi-parameter circuit optimization using the Smith Tube. Comparison is performed between gradient, pattern, and simplex searches in 2, 3, 4, and 5 dimensions. While simplex performs very well in lower dimensions, its usefulness significantly decreases for higher dimensions. Gradient search is shown through these comparisons to provide the best results in five dimensions for the types of searches and starting points examined in this work.