Maciej Tomasz Myslinski

Large-Signal Network Analysis Including the Baseband

In recent years, wireless systems have rapidly evolved due to the increasing demands of different services, functionalities, and applications. In order to provide high-speed connectivity while using the available spectrum in an efficient manner, wideband digitally modulated signals are increasingly used to transmit information.

State-space modelling of slow-memory effects based on multisine vector measurements

Non-linear microwave devices and circuits often exhibit slow-memory effects. When subjected to two-tone, or more general multisine excitations, the characteristics of these devices and circuits depend on the offset frequency between the tones. Since modulated excitations are an integral part of telecommunication systems, models aimed for circuit and system design should be able to accurately represent slow-memory behaviour. In this work, we develop a modelling procedure based on the state-space modelling approach to accurately incorporate these slow-memory effects. The technique is experimentally demonstrated on a high electron mobility transistor (HEMT).

A state-space modeling approach for dynamic nonlinear microwave system based on large signal time domain measurements

This paper introduces a model for dynamic nonlinear microwave systems or device operating in large signal regime, based on a state-space formulation. It differs from previous approaches in the comprehensive description of the describing functions and the identification procedure based on the solution of a linear system of equations. The model is able to predict specific operation states, having identified the model in an a-priory defined set of operation states. The identification procedure, as well as the validation, are based on multisine Large Signal Time Domain Measurements at different input power levels. Extensive experimental results are provided for a case study based on a commercial InGaP HBT gain block driven by a set of 9 tones equally distributed in 1.6 MHz bandwidth around the frequency of 4.9GHz, with all the power levels ranging from linear to saturation regions. The accuracy of the model, also in terms of prediction capabilities is provided in both time- and frequency-domain.