## 6 High Frequency Characterization and Modelling
### Toward a Reliability-Aware Design Framework  
To emphasize the aforementioned discussions, one of the prerequisites of the monolithic integration of electronic and photonic technologies, that are capable of functioning at terahertz/sub terahertz frequencies, is a systematic assembly of existing design software that will not only take into account multi-physics transport, electro-magnetic simulation as well as interconnect modeling, but will also address emerging reliability concerns. Optical devices, in particular photodiodes, are prone to significant heat dissipation [38], which may consequently impact the electronic part and can eventually become a serious reliability issue. Catastrophic failure (burn-out) can occur at constant power dissipations of 240 mW for the UTC-PDs [39]. On the other hand, owing to continuous scaling of electronic devices, self-heating is already a severe problem in highly scaled electronic components such as in advanced bipolar transistor technologies including SiGe or InP HBT [40]. As made evident in Section 7.2, thermal resistances (\(R_{TH}\)) of DHBTs increase rapidly as device geometries are scaled down. Self-heating management has become the major issue of further HBT process development. The first problem due to increased junction temperature is the impact on its electrical performance. The second problem is reliability related. In fact, increasing junction temperature has a negative impact on the device lifetime [21]. Most of the degradation modes of InP HBTs are strongly accelerated by temperature. Rise in device temperature will ultimately lead to pronounced self-heating at the circuit level and the failure mechanisms are likely to activate leading to degradation in the circuit performances. To address the emerging reliability concerns in InP-based monolithic integrated circuits, [41] has proposed a reliability-aware design methodology to \"pre-diagnose\" failure mechanisms in advanced circuits and to design optimized \"robust\" circuit architectures in order to maximize circuit operation lifetime. The overall goal of this methodology is to provide a holistic reliability analysis solution for next-generation electronic system design that will meet the pre-requisite reliability-constraints prior to manufacturing. This unique methodology is achievable with already available design tools and can be applied regardless of the technology type, thus allowing a straightforward implementation into  
Figure 22: Extrapolating figures of merit of the III–V DHBTs: (**a**) \(f_{T}\); (**b**) \(\beta\); (**c**) \(f_{MAX}\); and (**d**) \(R_{TH}\). commercial computer-aided design (CAD) flows. In terms of resources, the methodology aims to work with a single simulator-based design approach, i.e., to offer unified simulation capabilities for all parts of the integrated circuit (IC). In the context of monolithic integrated circuits, multiphysics simulation is thus in high-demand, as emphasized in Section 1. Moreover, this methodology can help drastically shorten design time and costs, while ensuring the same accuracy of results compared to conventional reliability analysis methodologies, by avoiding rigorous circuit aging tests and IC redesign phases for technology qualification. Figure 23 shows the different phases of the IC qualification process which are typically repeated several times in order to meet the qualification criteria. Apart from the obvious time constraints owing to redesign cycles, process optimization and especially mask redesigning costs tens of thousands of dollars for InP-based technologies [41]. The reliability-aware design and optimization at the circuit simulation stage thus allows to carefully choose most \"robust\" circuit architecture leveraging dynamic degradation laws directly implemented in the compact models compatible with all Berkeley-SPICE derivative simulators. A \"virtual degradation acceleration mechanism\" is pivotal for ensuring the simulation efficiency of the aging model in order to emulate years of circuit aging by picoseconds of simulation time [41].