Low power CMOS IC, biosensor and wireless power transfer techniques for wireless sensor network application

The emerging field of wireless sensor network (WSN) is receiving great attention due to the interest in healthcare. Traditional battery-powered devices suffer from large size, weight and secondary replacement surgery after the battery life-time which is often not desired, especially for an implantable application. Thus an energy harvesting method needs to be investigated. In addition to energy harvesting, the sensor network needs to be low power to extend the wireless power transfer distance and meet the regulation on RF power exposed to human tissue (specific absorption ratio). Also, miniature sensor integration is another challenge since most of the commercial sensors have rigid form or have a bulky size. The objective of this thesis is to provide solutions to the aforementioned challenges

Energy-efficient Wireless Analog Sensing for Persistent Underwater Environmental Monitoring

The design of sensors or "things" as part of the new Internet of Underwater Things (IoUTs) paradigm comes with multiple challenges including limited battery capacity, not polluting the water body, and the ability to track continuously phenomena with high temporal/spatial variability. We claim that traditional digital sensors are incapable to meet these demands because of their high power consumption, high complexity (cost), and the use of non-biodegradable materials. To address the above challenges, we propose a novel architecture consisting of a sensing substrate of dense analog biodegradable sensors over which lies the traditional Wireless Sensor Network (WSN). The substrate analog biodegradable sensors perform Shannon mapping (a data-compression technique) using just a single Field Effect Transistor (FET) without the need for power-hungry Analog-to-Digital Converters (ADCs) resulting in much lower power consumption, complexity, and the ability to be powered using only sustainable energy-harvesting techniques. A novel and efficient decoding technique is also presented. Both encoding/decoding techniques have been verified via Spice and MATLAB simulations accounting for underwater acoustic channel variations.Comment: 5 pages, IEEE UComms 201

ISM-Band Energy Harvesting Wireless Sensor Node

In recent years, the interest in remote wireless sensor networks has grown significantly, particularly with the rapid advancements in Internet of Things (IoT) technology. These networks find diverse applications, from inventory tracking to environmental monitoring. In remote areas where grid access is unavailable, wireless sensors are commonly powered by batteries, which imposes a constraint on their lifespan. However, with the emergence of wireless energy harvesting technologies, there is a transformative potential in addressing the power challenges faced by these sensors. By harnessing energy from the surrounding environment, such as solar, thermal, vibrational, or RF sources, these sensors can potentially operate autonomously for extended periods. This innovation not only enhances the sustainability of wireless sensor networks but also paves the way for a more energy-efficient and environmentally conscious approach to data collection and monitoring in various applications. This work explores the development of an RF-powered wireless sensor node in 22nm FDSOI technology working in the ISM band for energy harvesting and wireless data transmission. The sensor node encompasses power-efficient circuits, including an RF energy harvesting module equipped with a multi-stage RF Dickson rectifier, a robust power management unit, a DLL and XOR-based frequency synthesizer for RF carrier generation, and a class E power amplifier. To ensure the reliability of the WSN, a dedicated wireless RF source powers up the WSN. Additionally, the RF signal from this dedicated source serves as the reference frequency input signal for synthesizing the RF carrier for wireless data transmission, eliminating the need for an on-chip local oscillator. This approach achieves high integration and proves to be a cost-effective implementation of efficient wireless sensor nodes. The receiver and energy harvester operate at 915 MHz Frequency, while the transmitter functions at 2.45 GHz, employing On-Off Keying (OOK) for data modulation. The WSN utilizes an efficient RF rectifier design featuring a remarkable power conversion efficiency, reaching 55% at an input power of -14 dBm. Thus, the sensor node can operate effectively even with an extremely low RF input power of -25 dBm. The work demonstrates the integration of the wireless sensor node with an ultra-low-power temperature sensor, designed using 65 nm CMOS technology. This temperature sensor features an ultra-low power consumption of 60 nW and a Figure of Merit (FOM) of 0.022 [nJ.K-2]. The WSN demonstrated 55% power efficiency at a TX output power of -3.8 dBm utilizing a class E power amplifier