Circuit and System Designs for Millimeter Scale IoT and Wireless Neural Recording

Abstract:

Miniaturization and interactive communication are the two main topics that dominate the recent research in the IoT. The high demand for continuous monitoring of environmental and bio-medical information has accelerated sensor technologies as well as circuit innovations. Simultaneously, the advances in communication methods and the widespread use of cellular and local data links enable the networking of sensor nodes. This potential improvement in machine service for humans could trigger the commercial development of a sensor node with platforms that collect, process and transmit widely spread environmental and bio-medical data.

The next generation of computing platforms increases proximity to the source of information rather than to humans, allowing much more aggressive miniaturization. The key technology of miniaturization has been process scaling, which has reduced the silicon area, increased computational capability and lowered power consumption. However, the latest deep-submicron technologies do not fit well on the mm-scale computing because of the increased leakage current. Therefore, advances in circuit level techniques are critical to realize networks of mm-scale IoT computing platforms.

In this work, we demonstrate circuit level innovations for the key building blocks, such as a 4.7nW wakeup timer, a 2.5ps phase locked loop with noise self-adjustment, a 1.8 NEF neural recording amplifier and a 2.7 cm3 GNSS logger system.