Ultra-Low-Power Sensors and Receivers for IoT Applications

The combination of ultra-low power analog front-ends and CMOS-compatible transducers enable new applications, such as environmental monitors, household appliances, health trackers, etc. that are seamlessly integrated into our daily lives. Furthermore, wireless connectivity allows many of these sensors to operate both independently and collectively. These techniques collectively fulfil the recent surge of internet-of-things (IoT) applications that have the potential to fundamentally change daily life for millions of people.In this dissertation, the circuit and system design of wireless receivers and sensors is presented that explores the challenges of implementing long lifespan, high accuracy, and large coverage range IoT sensor networks. The first is a wake-up receiver (WuRX), which continuously monitors the RF environment to wake up a higher-power radio upon detection of a predetermined RF signature. This work both improves sensitivity and reduces power over prior art through a multi-faceted design featuring an impedance transformation network with large passive voltage gain, an active envelope detector with high input impedance to facilitate large passive voltage gain, a low-power precision comparator, and a low-leakage digital baseband correlator.Although pushing the prior WuRX performance boundary by orders of magnitude, the first work shows moderate sensitivity, inferior temperature robustness, and large area with external lumped components. Thus, the second work shows a miniaturized WuRX that is temperature-compensated, yet still consumes only nano-watt power and millimeter area while operating at 9 GHz. To further reduce the area, a global common-mode feedback is utilized across the envelope detector and baseband amplifier that eliminates the need for off-chip ac-coupling components. Multiple temperature-compensation techniques are proposed to maintain constant bandwidth of the signal path and constant clock frequency. Both WuRXs operate at 0.4 V supply, consume near-zero power and achieve ~-70 dBm sensitivity.Lastly, the first reported CMOS 2-in-1 relative humidity and temperature sensor is presented. A unified analog front-end interfaces on-chip transducers and converts the inputs into a frequency vis a high-linearity frequency-locked loop. An incomplete-settling switched-capacitor-based Wheatstone bridge is proposed to sense the inputs in a power-efficient fashion

Design and implementation of a multi-modal sensor with on-chip security

With the advancement of technology, wearable devices for fitness tracking, patient monitoring, diagnosis, and disease prevention are finding ways to be woven into modern world reality. CMOS sensors are known to be compact, with low power consumption, making them an inseparable part of wireless medical applications and Internet of Things (IoT). Digital/semi-digital output, by the translation of transmitting data into the frequency domain, takes advantages of both the analog and digital world. However, one of the most critical measures of communication, security, is ignored and not considered for fabrication of an integrated chip. With the advancement of Moore\u27s law and the possibility of having a higher number of transistors and more complex circuits, the feasibility of having on-chip security measures is drawing more attention. One of the fundamental means of secure communication is real-time encryption. Encryption/ciphering occurs when we encode a signal or data, and prevents unauthorized parties from reading or understanding this information. Encryption is the process of transmitting sensitive data securely and with privacy. This measure of security is essential since in biomedical devices, the attacker/hacker can endanger users of IoT or wearable sensors (e.g. attacks at implanted biosensors can cause fatal harm to the user). This work develops 1) A low power and compact multi-modal sensor that can measure temperature and impedance with a quasi-digital output and 2) a low power on-chip signal cipher for real-time data transfer

Digital-Based Analog Processing in Nanoscale CMOS ICs for IoT Applications

L'abstract è presente nell'allegato / the abstract is in the attachmen

Power Management ICs for Internet of Things, Energy Harvesting and Biomedical Devices

This dissertation focuses on the power management unit (PMU) and integrated circuits (ICs) for the internet of things (IoT), energy harvesting and biomedical devices. Three monolithic power harvesting methods are studied for different challenges of smart nodes of IoT networks. Firstly, we propose that an impedance tuning approach is implemented with a capacitor value modulation to eliminate the quiescent power consumption. Secondly, we develop a hill-climbing MPPT mechanism that reuses and processes the information of the hysteresis controller in the time-domain and is free of power hungry analog circuits. Furthermore, the typical power-performance tradeoff of the hysteresis controller is solved by a self-triggered one-shot mechanism. Thus, the output regulation achieves high-performance and yet low-power operations as low as 12 µW. Thirdly, we introduce a reconfigurable charge pump to provide the hybrid conversion ratios (CRs) as 1⅓× up to 8× for minimizing the charge redistribution loss. The reconfigurable feature also dynamically tunes to maximum power point tracking (MPPT) with the frequency modulation, resulting in a two-dimensional MPPT. Therefore, the voltage conversion efficiency (VCE) and the power conversion efficiency (PCE) are enhanced and flattened across a wide harvesting range as 0.45 to 3 V. In a conclusion, we successfully develop an energy harvesting method for the IoT smart nodes with lower cost, smaller size, higher conversion efficiency, and better applicability. For the biomedical devices, this dissertation presents a novel cost-effective automatic resonance tracking method with maximum power transfer (MPT) for piezoelectric transducers (PT). The proposed tracking method is based on a band-pass filter (BPF) oscillator, exploiting the PT’s intrinsic resonance point through a sensing bridge. It guarantees automatic resonance tracking and maximum electrical power converted into mechanical motion regardless of process variations and environmental interferences. Thus, the proposed BPF oscillator-based scheme was designed for an ultrasonic vessel sealing and dissecting (UVSD) system. The sealing and dissecting functions were verified experimentally in chicken tissue and glycerin. Furthermore, a combined sensing scheme circuit allows multiple surgical tissue debulking, vessel sealer and dissector (VSD) technologies to operate from the same sensing scheme board. Its advantage is that a single driver controller could be used for both systems simplifying the complexity and design cost. In a conclusion, we successfully develop an ultrasonic scalpel to replace the other electrosurgical counterparts and the conventional scalpels with lower cost and better functionality

Interface Circuits for Microsensor Integrated Systems

ca. 200 words; this text will present the book in all promotional forms (e.g. flyers). Please describe the book in straightforward and consumer-friendly terms. [Recent advances in sensing technologies, especially those for Microsensor Integrated Systems, have led to several new commercial applications. Among these, low voltage and low power circuit architectures have gained growing attention, being suitable for portable long battery life devices. The aim is to improve the performances of actual interface circuits and systems, both in terms of voltage mode and current mode, in order to overcome the potential problems due to technology scaling and different technology integrations. Related problems, especially those concerning parasitics, lead to a severe interface design attention, especially concerning the analog front-end and novel and smart architecture must be explored and tested, both at simulation and prototype level. Moreover, the growing demand for autonomous systems gets even harder the interface design due to the need of energy-aware cost-effective circuit interfaces integrating, where possible, energy harvesting solutions. The objective of this Special Issue is to explore the potential solutions to overcome actual limitations in sensor interface circuits and systems, especially those for low voltage and low power Microsensor Integrated Systems. The present Special Issue aims to present and highlight the advances and the latest novel and emergent results on this topic, showing best practices, implementations and applications. The Guest Editors invite to submit original research contributions dealing with sensor interfacing related to this specific topic. Additionally, application oriented and review papers are encouraged.

Low Power Circuits for Smart Flexible ECG Sensors

Cardiovascular diseases (CVDs) are the world leading cause of death. In-home heart condition monitoring effectively reduced the CVD patient hospitalization rate. Flexible electrocardiogram (ECG) sensor provides an affordable, convenient and comfortable in-home monitoring solution. The three critical building blocks of the ECG sensor i.e., analog frontend (AFE), QRS detector, and cardiac arrhythmia classifier (CAC), are studied in this research. A fully differential difference amplifier (FDDA) based AFE that employs DC-coupled input stage increases the input impedance and improves CMRR. A parasitic capacitor reuse technique is proposed to improve the noise/area efficiency and CMRR. An on-body DC bias scheme is introduced to deal with the input DC offset. Implemented in 0.35m CMOS process with an area of 0.405mm2, the proposed AFE consumes 0.9W at 1.8V and shows excellent noise effective factor of 2.55, and CMRR of 76dB. Experiment shows the proposed AFE not only picks up clean ECG signal with electrodes placed as close as 2cm under both resting and walking conditions, but also obtains the distinct -wave after eye blink from EEG recording. A personalized QRS detection algorithm is proposed to achieve an average positive prediction rate of 99.39% and sensitivity rate of 99.21%. The user-specific template avoids the complicate models and parameters used in existing algorithms while covers most situations for practical applications. The detection is based on the comparison of the correlation coefficient of the user-specific template with the ECG segment under detection. The proposed one-target clustering reduced the required loops. A continuous-in-time discrete-in-amplitude (CTDA) artificial neural network (ANN) based CAC is proposed for the smart ECG sensor. The proposed CAC achieves over 98% classification accuracy for 4 types of beats defined by AAMI (Association for the Advancement of Medical Instrumentation). The CTDA scheme significantly reduces the input sample numbers and simplifies the sample representation to one bit. Thus, the number of arithmetic operations and the ANN structure are greatly simplified. The proposed CAC is verified by FPGA and implemented in 0.18m CMOS process. Simulation results show it can operate at clock frequencies from 10KHz to 50MHz. Average power for the patient with 75bpm heart rate is 13.34W

Low-power Wearable Healthcare Sensors

Advances in technology have produced a range of on-body sensors and smartwatches that can be used to monitor a wearer’s health with the objective to keep the user healthy. However, the real potential of such devices not only lies in monitoring but also in interactive communication with expert-system-based cloud services to offer personalized and real-time healthcare advice that will enable the user to manage their health and, over time, to reduce expensive hospital admissions. To meet this goal, the research challenges for the next generation of wearable healthcare devices include the need to offer a wide range of sensing, computing, communication, and human–computer interaction methods, all within a tiny device with limited resources and electrical power. This Special Issue presents a collection of six papers on a wide range of research developments that highlight the specific challenges in creating the next generation of low-power wearable healthcare sensors

Low Power Memory/Memristor Devices and Systems

This reprint focusses on achieving low-power computation using memristive devices. The topic was designed as a convenient reference point: it contains a mix of techniques starting from the fundamental manufacturing of memristive devices all the way to applications such as physically unclonable functions, and also covers perspectives on, e.g., in-memory computing, which is inextricably linked with emerging memory devices such as memristors. Finally, the reprint contains a few articles representing how other communities (from typical CMOS design to photonics) are fighting on their own fronts in the quest towards low-power computation, as a comparison with the memristor literature. We hope that readers will enjoy discovering the articles within

Proceedings of the Fifth International Mobile Satellite Conference 1997

Satellite-based mobile communications systems provide voice and data communications to users over a vast geographic area. The users may communicate via mobile or hand-held terminals, which may also provide access to terrestrial communications services. While previous International Mobile Satellite Conferences have concentrated on technical advances and the increasing worldwide commercial activities, this conference focuses on the next generation of mobile satellite services. The approximately 80 papers included here cover sessions in the following areas: networking and protocols; code division multiple access technologies; demand, economics and technology issues; current and planned systems; propagation; terminal technology; modulation and coding advances; spacecraft technology; advanced systems; and applications and experiments