Design of a 2.4 Ghz BAW-Based CMOS Transmitter

In recent years, bulk acoustic wave resonators (BAW) in combination with RF circuits have shown a big potential in achieving the low-power consumption and miniaturization level required to address wireless sensor nodes (WSN) applications. A lot of work has been focused on the receiver side, by integrating BAW resonators with low noise amplifiers (LNA) and in frequency synthesis with the design of BAW-based local oscillators, most of them working at fixed frequency due to their limited tuning range. At the architectural level, this has forced the implementation of several single channel transceivers. This thesis aims at exploring the use of BAW resonators in the transmitter, proposing an architecture capable of taking full advantage of them. The main objective is to develop a transmitter for WSN multi-channel applications able to cover the whole 2.4 GHz ISM band and enable the compatibility with wide-spread standards like Bluetooth and Bluetooth Low Energy. Typical transmissions should thus range from low data rates (typically tens of kb/s) to medium data rates (1 Mb/s), with FSK and GFSK modulation schemes, should be centered on any of the channels provided by these standards and cover a maximum transmission range of some tens of meters. To achieve these targets and circumvent the limited tuning range of the BAW oscillator, an up-conversion transmitter using wide IF is used. The typical spurs problems related to this transmitter architecture are addressed by using a combined suppression based on SSB mixing and selective amplification. The latter is achieved by cointegration of a high efficiency power amplifier with BAW resonators, which allows performing spurs filtering while preserving the efficiency. In particular the selective amplifier is designed by including in the PA analysis the BAW resonator parameters, which allows integrating the BAW filter into the passive network loading the amplifier, participating in the drain voltage shaping. Finally, the frequency synthesis section uses a fractional division plus LC PLL filtering and further integer division to generate the IF signals and exploit the very-low BAW oscillator phase noise. The transmitter has been integrated in a 0.18 µm standard digital CMOS technology. It allows addressing the whole 80 MHz wide 2.4 GHz ISM band. The unmodulated RF frequency carrier demonstrates a very-low phase noise of –136 dBc/Hz at 1 MHz offset. The IF spurs are maintained lower than –48 dBc, satisfying the international regulations for output power up to 10 dBm without the use of any quadrature error compensation in the transmitter. This is achieved thanks to the rejection provided by the SSB mixer and the selective amplifier, which can reach drain efficiency of up to 24% with integrated inductances, including the insertion losses of the BAW filter. The transmitter consumes 35.3 mA at the maximum power of 5.4 dBm under 1.6 V (1.2 V for the PA), while transmitting a 1 Mb/s GFSK signal and complying with both Bluetooth and Bluetooth Low Energy relative and absolute spectrum requirements

RF MEMS reference oscillators platform for wireless communications

A complete platform for RF MEMS reference oscillator is built to replace bulky quartz from mobile devices, thus reducing size and cost. The design targets LTE transceivers. A low phase noise 76.8 MHz reference oscillator is designed using material temperature compensated AlN-on-silicon resonator. The thesis proposes a system combining piezoelectric resonator with low loading CMOS cross coupled series resonance oscillator to reach state-of-the-art LTE phase noise specifications. The designed resonator is a two port fundamental width extensional mode resonator. The resonator characterized by high unloaded quality factor in vacuum is designed with low temperature coefficient of frequency (TCF) using as compensation material which enhances the TCF from - 3000 ppm to 105 ppm across temperature ranges of -40˚C to 85˚C. By using a series resonant CMOS oscillator, phase noise of -123 dBc/Hz at 1 kHz, and -162 dBc/Hz at 1MHz offset is achieved. The oscillator’s integrated RMS jitter is 106 fs (10 kHz–20 MHz), consuming 850 μA, with startup time is 250μs, achieving a Figure-of-merit (FOM) of 216 dB. Electronic frequency compensation is presented to further enhance the frequency stability of the oscillator. Initial frequency offset of 8000 ppm and temperature drift errors are combined and further addressed electronically. A simple digital compensation circuitry generates a compensation word as an input to 21 bit MASH 1 -1-1 sigma delta modulator incorporated in RF LTE fractional N-PLL for frequency compensation. Temperature is sensed using low power BJT band-gap front end circuitry with 12 bit temperature to digital converter characterized by a resolution of 0.075˚C. The smart temperature sensor consumes only 4.6 μA. 700 MHz band LTE signal proved to have the stringent phase noise and frequency resolution specifications among all LTE bands. For this band, the achieved jitter value is 1.29 ps and the output frequency stability is 0.5 ppm over temperature ranges from -40˚C to 85˚C. The system is built on 32nm CMOS technology using 1.8V IO device

Low Power Circuit Design in Sustainable Self Powered Systems for IoT Applications

The Internet-of-Things (IoT) network is being vigorously pushed forward from many fronts in diverse research communities. Many problems are still there to be solved, and challenges are found among its many levels of abstraction. In this thesis we give an overview of recent developments in circuit design for ultra-low power transceivers and energy harvesting management units for the IoT. The first part of the dissertation conducts a study of energy harvesting interfaces and optimizing power extraction, followed by power management for energy storage and supply regulation. we give an overview of the recent developments in circuit design for ultra-low power management units, focusing mainly in the architectures and techniques required for energy harvesting from multiple heterogeneous sources. Three projects are presented in this area to reach a solution that provides reliable continuous operation for IoT sensor nodes in the presence of one or more natural energy sources to harvest from. The second part focuses on wireless transmission, To reduce the power consumption and boost the Tx energy efficiency, a novel delay cell exploiting current reuse is used in a ring-oscillator employed as the local oscillator generator scheme. In combination with an edge-combiner power amplifier, the Tx showed a measured energy efficiency of 0.2 nJ=bit and a normalized energy efficiency of 3.1 nJ=bit:mW when operating at output power levels up to -10 dBm and data rates of 3 Mbps

Design for energy-efficient and reliable fog-assisted healthcare IoT systems

Cardiovascular disease and diabetes are two of the most dangerous diseases as they are the leading causes of death in all ages. Unfortunately, they cannot be completely cured with the current knowledge and existing technologies. However, they can be effectively managed by applying methods of continuous health monitoring. Nonetheless, it is difficult to achieve a high quality of healthcare with the current health monitoring systems which often have several limitations such as non-mobility support, energy inefficiency, and an insufficiency of advanced services. Therefore, this thesis presents a Fog computing approach focusing on four main tracks, and proposes it as a solution to the existing limitations. In the first track, the main goal is to introduce Fog computing and Fog services into remote health monitoring systems in order to enhance the quality of healthcare. In the second track, a Fog approach providing mobility support in a real-time health monitoring IoT system is proposed. The handover mechanism run by Fog-assisted smart gateways helps to maintain the connection between sensor nodes and the gateways with a minimized latency. Results show that the handover latency of the proposed Fog approach is 10%-50% less than other state-of-the-art mobility support approaches. In the third track, the designs of four energy-efficient health monitoring IoT systems are discussed and developed. Each energy-efficient system and its sensor nodes are designed to serve a specific purpose such as glucose monitoring, ECG monitoring, or fall detection; with the exception of the fourth system which is an advanced and combined system for simultaneously monitoring many diseases such as diabetes and cardiovascular disease. Results show that these sensor nodes can continuously work, depending on the application, up to 70-155 hours when using a 1000 mAh lithium battery. The fourth track mentioned above, provides a Fog-assisted remote health monitoring IoT system for diabetic patients with cardiovascular disease. Via several proposed algorithms such as QT interval extraction, activity status categorization, and fall detection algorithms, the system can process data and detect abnormalities in real-time. Results show that the proposed system using Fog services is a promising approach for improving the treatment of diabetic patients with cardiovascular disease

Energy-efficient design and implementation of turbo codes for wireless sensor network

The objective of this thesis is to apply near Shannon limit Error-Correcting Codes (ECCs), particularly the turbo-like codes, to energy-constrained wireless devices, for the purpose of extending their lifetime. Conventionally, sophisticated ECCs are applied to applications, such as mobile telephone networks or satellite television networks, to facilitate long range and high throughput wireless communication. For low power applications, such as Wireless Sensor Networks (WSNs), these ECCs were considered due to their high decoder complexities. In particular, the energy efficiency of the sensor nodes in WSNs is one of the most important factors in their design. The processing energy consumption required by high complexity ECCs decoders is a significant drawback, which impacts upon the overall energy consumption of the system. However, as Integrated Circuit (IC) processing technology is scaled down, the processing energy consumed by hardware resources reduces exponentially. As a result, near Shannon limit ECCs have recently begun to be considered for use in WSNs to reduce the transmission energy consumption [1,2]. However, to ensure that the transmission energy consumption reduction granted by the employed ECC makes a positive improvement on the overall energy efficiency of the system, the processing energy consumption must still be carefully considered.The main subject of this thesis is to optimise the design of turbo codes at both an algorithmic and a hardware implementation level for WSN scenarios. The communication requirements of the target WSN applications, such as communication distance, channel throughput, network scale, transmission frequency, network topology, etc, are investigated. Those requirements are important factors for designing a channel coding system. Especially when energy resources are limited, the trade-off between the requirements placed on different parameters must be carefully considered, in order to minimise the overall energy consumption. Moreover, based on this investigation, the advantages of employing near Shannon limit ECCs in WSNs are discussed. Low complexity and energy-efficient hardware implementations of the ECC decoders are essential for the target applications

Applications of Antenna Technology in Sensors

During the past few decades, information technologies have been evolving at a tremendous rate, causing profound changes to our world and to our ways of living. Emerging applications have opened u[ new routes and set new trends for antenna sensors. With the advent of the Internet of Things (IoT), the adaptation of antenna technologies for sensor and sensing applications has become more important. Now, the antennas must be reconfigurable, flexible, low profile, and low-cost, for applications from airborne and vehicles, to machine-to-machine, IoT, 5G, etc. This reprint aims to introduce and treat a series of advanced and emerging topics in the field of antenna sensors

Integrated Circuits and Systems for Smart Sensory Applications

Connected intelligent sensing reshapes our society by empowering people with increasing new ways of mutual interactions. As integration technologies keep their scaling roadmap, the horizon of sensory applications is rapidly widening, thanks to myriad light-weight low-power or, in same cases even self-powered, smart devices with high-connectivity capabilities. CMOS integrated circuits technology is the best candidate to supply the required smartness and to pioneer these emerging sensory systems. As a result, new challenges are arising around the design of these integrated circuits and systems for sensory applications in terms of low-power edge computing, power management strategies, low-range wireless communications, integration with sensing devices. In this Special Issue recent advances in application-specific integrated circuits (ASIC) and systems for smart sensory applications in the following five emerging topics: (I) dedicated short-range communications transceivers; (II) digital smart sensors, (III) implantable neural interfaces, (IV) Power Management Strategies in wireless sensor nodes and (V) neuromorphic hardware

Recent Developments in Smart Healthcare

Medicine is undergoing a sector-wide transformation thanks to the advances in computing and networking technologies. Healthcare is changing from reactive and hospital-centered to preventive and personalized, from disease focused to well-being centered. In essence, the healthcare systems, as well as fundamental medicine research, are becoming smarter. We anticipate significant improvements in areas ranging from molecular genomics and proteomics to decision support for healthcare professionals through big data analytics, to support behavior changes through technology-enabled self-management, and social and motivational support. Furthermore, with smart technologies, healthcare delivery could also be made more efficient, higher quality, and lower cost. In this special issue, we received a total 45 submissions and accepted 19 outstanding papers that roughly span across several interesting topics on smart healthcare, including public health, health information technology (Health IT), and smart medicine