The increasing complexity of the beyond 4G systems has resulted in the optimization of several different technologies for each specific function. Hence, systems are composed of many chips. The downscaling of Si CMOS technology has not only allowed for a large integration level but also the integration of high-speed transceivers on the chips. Nevertheless, the requirements of high power, high-efficiency power amplifiers are not met by the low voltage operation of CMOS technology. Thus, alternate materials are used for power amplifier applications. Of those materials, GaN is the most promising based on its ability to operate at high frequency and high-power levels. Conversely, RF Front-End Modules (RF-FEMs) include high-performance switches which are fabricated on semi-insulating substrates.

Therefore, the realization of the next generations of power and cost-efficient RF systems is highly dependent on the co-integration of the different device technologies.

This PhD work targets the optimization of RF components for high-performance communication systems. This entails focusing on multiple domains; mainly device modelling, and circuit design. Device modelling necessitates proper understanding of the device fabrication as well as RF characterization. From device measurements, compact models will be developed and then used to evaluate the circuit performance. Furthermore, the requirements at the circuit-level should be translated into device-level figures of merit (FoMs), which can subsequently give insight into device optimization.

Furthermore, this PhD aims to establish methodologies that are independent of the device architecture, thus, different device architectures are to be considered ((MIS)HEMTs, HBTs…). A major concern with III-V devices is the various reliability degradation mechanisms that shorten the device lifetime. In III-V HEMTS and HBTs, substrate trapping centres and contact resistances affect key RF FOMs, namely the cut-off and maximum operating frequencies. It is the final target of this PhD to characterize and model such mechanisms.