Because of their high performance, Metal-Semiconductor Field Effect Transistors (MESFETs) and High-Electron-Mobility Transistors (HEMTs) are widely used in microwave and millimeter wave communication systems, particularly in low noise applications. Therefore, accurate noise models are essential to ensure robust simulation and optimization during the design process. The sophistication of modern communication systems urged the need of monolithic microwave integrated circuits (MMICs), which contain several MESFETs or HEMTs on the same chip. As the chip density increases, the request for accurate MESFET or HEMT noise models becomes more pronounced.
In this study, a new method has been developed to extract a 15-element small signal model of MESFET and HEMT devices. This method uses three sets of S-parameter measurements at different bias conditions. The technique consists of two major steps; in the first step, part of the bias-independent extrinsic parameters is evaluated in preparation to the second step. In the second step, all other parameters should be extracted at the bias point of interest using an optimization method. This method has been tested on S-parameters of a hypothetical device model with ideal and noisy data, compared with other optimization-based techniques, and shows reliable results and a unique solution for all parameter values.
Another method has been proposed to extract the noise parameters of a packaged device at any frequency. This technique has also been tested on S-parameters of a hypothetical device model with ideal and noisy data, and compared with other noise parameter extraction techniques. The study shows consistent results and demonstrates its accuracy, simplicity and efficiency as a noise parameter extraction method of microwave/millimeter-wave transistors.
| Identifer | oai:union.ndltd.org:uottawa.ca/oai:ruor.uottawa.ca:10393/27088 |
| Date | January 2005 |
| Creators | Yang, Xiuzhu |
| Publisher | University of Ottawa (Canada) |
| Source Sets | Université d’Ottawa |
| Language | English |
| Detected Language | English |
| Type | Thesis |
| Format | 115 p. |
Page generated in 0.0016 seconds