PROJECT TITLE :

Automatic Test Stimulus Generation for Diagnosis of RF Transceivers Using Model Parameter Estimation

ABSTRACT:

During this brief, an optimized check stimulus generation technique is proposed for model parameter computation-based diagnosis and testing, which will give a terribly compact deterministic take a look at signal and results in vital reduction in check time. The proposed test stimulus generation algorithm maximizes the accuracy with which a nonlinear solver can determine RF transceiver model parameters from raw downconverted check response data. The simulation results show that using optimized take a look at signals, a comprehensive range of model parameters can be computed accurately employing a single knowledge acquisition. Knowledge from experiments performed on a hardware prototype are shown to validate the proposed methodology.