An improved small-signal parameter extraction technique for short channel enhancement-mode N-polar GaN MOS-HEMT is proposed, which is a combination of a conventional analytical method and optimization techniques. The ...An improved small-signal parameter extraction technique for short channel enhancement-mode N-polar GaN MOS-HEMT is proposed, which is a combination of a conventional analytical method and optimization techniques. The extrinsic parameters such as parasitic capacitance, inductance and resistance are extracted under the pinch-off condition. The intrinsic parameters of the small-signal equivalent circuit（SSEC） have been extracted including gate forward and backward conductance. Different optimization algorithms such as PSO, Quasi Newton and Firefly optimization algorithm is applied to the extracted parameters to minimize the error between modeled and measured S-parameters. The different optimized SSEC models have been validated by comparing the S-parameters and unity current-gain with TCAD simulations and available experimental data from the literature. It is observed that the Firefly algorithm based optimization approach accurately extracts the small-signal model parameters as compared to other optimization algorithm techniques with a minimum error percentage of 1.3%.展开更多
基金project under the Visvesvaraya PhD Scheme of the Ministry of Electronics&Information Technology,Government of India,being implemented by the Digital IndiaCorporation (formerly Media Lab Asia)TEQIP-Ⅱ funding for facilitating Silvaco TCAD and Keysight's ADS tools for carrying out the research work
文摘An improved small-signal parameter extraction technique for short channel enhancement-mode N-polar GaN MOS-HEMT is proposed, which is a combination of a conventional analytical method and optimization techniques. The extrinsic parameters such as parasitic capacitance, inductance and resistance are extracted under the pinch-off condition. The intrinsic parameters of the small-signal equivalent circuit（SSEC） have been extracted including gate forward and backward conductance. Different optimization algorithms such as PSO, Quasi Newton and Firefly optimization algorithm is applied to the extracted parameters to minimize the error between modeled and measured S-parameters. The different optimized SSEC models have been validated by comparing the S-parameters and unity current-gain with TCAD simulations and available experimental data from the literature. It is observed that the Firefly algorithm based optimization approach accurately extracts the small-signal model parameters as compared to other optimization algorithm techniques with a minimum error percentage of 1.3%.
