From on-chip self-healing to self-adaptivity in analog/RF ICs: challenges and opportunities

The numerous variations that affect analog and RF circuits are becoming a limiting factor in the design of these circuits in deeply scaled CMOS technologies. An emerging idea to counteract these effects is to let the circuit compensate for these variations itself, referred to as self-healing. Over the last decade, a wide variety of off- and on-chip techniques for compensating these variations have been researched. This paper targets to give an overview of the state-of-the-art, and organize the proposed techniques in a common taxonomy. This allows to determine remaining open issues and research challenges. In particular, the SotA lacks efficient solutions for fully-integrated, short time-scale self-adaptation. The paper ends by giving an outlook towards promising research directions to enable such self-adaptation in mWatt power budgets for Internet of things applications, focusing on embedded machine-learning techniques.