UC San Diego

This dissertation presents energy-efficient schemes for short-range wireless communication for wearable devices. Generally, there are two types of wireless scenarios that happen around the human body. The first case is the data transfer between the wearable devices and the local hub devices, e.g., smartphones and smartwatches, allowing to connect to the external network and centrally control multiple wearable devices. Many researchers had proposed various wireless approaches for this scenario; however, there are still limitations in realistic implementations such as restricted form factors and limited energy sources of wearable devices. To address the barriers and challenges of the previously proposed schemes, my doctoral research introduced a new data transmission concept around the human body using magnetic fields, showing the theoretical background and experimental results that validate that the human body acts as a leaky dielectric waveguide. To demonstrate that the proposed concept can be implemented in the practical application, e.g., Hi-Fi audio streaming for portable headphones, this dissertation describes the design procedure and its measurement results of an energy-efficient ultra-low-power transceiver fabricated with CMOS technology.

The other wireless scenario occurs in a single wearable device, especially a body sensor device. For the practical reasons of accurate health monitoring, the body sensor device needs to be implanted or injected inside the human body, and it should operate in a fully-wireless environment for the portability of the wearable devices. This work presents guidelines for the design and optimization of on-chip coils used for wireless millimeter-scale integrated neural implants as an example of this wireless scenario. Since available real estate of a silicon chip is limited, on-chip coil design involves difficult managing multi-dimension trade-offs amongst the number of turns, trace width and spacing, proximity to other active circuits and metalization, quality factor, matching network performance/size, and load impedance conditions, all towards achieving high data/power transfer efficiency.