Due to the tremendous increase in wireless data traffic, one of the major challenges for future wireless systems is the utilization of the available spectrum to achieve better data rates over limited spectrum. Currently, systems operate in what is termed "Half Duplex Mode," where they are either transmitting or receiving, but never both using the same temporal and spectral resources. Full-duplex transmission promises to double the spectral efficiency where bidirectional communications is carried out over the same temporal and spectral resources. The main limitation impacting full-duplex transmission is managing the strong self-interference signal imposed by the transmit antenna on the receive antenna within the same transceiver. Several recent publications have demonstrated that the key challenge in practical full-duplex systems is un-cancelled self-interference power caused by a combination of hardware imperfections, especially Radio Frequency (RF) circuits' impairments.

In this thesis, we consider the problem of self-interference cancellation in full-duplex systems. The ultimate goal of this work is to design and build a complete, real-time, full-duplex system that is capable of achieving wireless full-duplex transmission using practical hardware platforms. Since RF circuits' impairments are shown to have significant impact on the self-interference cancellation performance, first, we present a thorough analysis of the effect of RF impairments on the cancellation performance, with the aim of identifying the main performance limiting factors and bottlenecks. Second, the thesis proposes several impairments mitigation techniques to improve the overall self-interference cancellation capability by mitigating most of the transceiver RF impairments. In addition to impairments mitigation, two novel full-duplex transceiver architectures that achieve significant self-interference cancellation performance are proposed. The performance of the proposed techniques is analytically and experimentally investigated in practical wireless environments. Finally, the proposed self-interference cancellation techniques are used to build a complete full-duplex system with a 90\% experimentally proven full-duplex rate improvement compared to half-duplex systems.

In this research, we consider the next-generation systems (100-340GHz), as millimeter frequencies permit a much larger spectrum, and shorter wavelengths provide massive MIMO array and high image resolution. This thesis focuses on building the hardware and necessary components for such systems. It is very challenging to produce decent efficiency and power at mm-wave frequencies as the gain drops significantly and the loss increases. Additionally, mm-wave packaging requires advanced assembly techniques. Here, we introduce a network theory to analyze the amplifier design options for the maximum PAE. The proposed theory considers the stacking and parallel power approaches using two-port techniques. This theory establishes a design framework for designing high-efficiency power amplifiers. We demonstrate record efficiency mm-wave power amplifiers (140, 210, and 300GHz) with moderate output power. The 140GHz amplifiers produce measured output power (20.5-23dBm) with a record efficiency of 17.8-20.8% PAE. We present 17.7-18.5dBm output power over the 190-210GHz frequency range with high efficiency of 6.9-8.5% PAE. Finally, a massive MIMO demonstration and mm-wave packaging are presented. We started with on-waver CMOS transmitters and receivers, then moved to a single packaged CMOS channel transmitter with eight-element series fed patch antenna, which has an EIRP of 13dBm at 135GHz. Finally, we built, in fabrication, a tile holding eight elements transmitter or receiver. The thesis covered the design and implementation of high-efficient packaged transmitters that prove the feasibility of the mm-wave communication system.

In the aftermath of a natural disaster, reconnaissance is typically conducted by teams of engineers tasked with tagging buildings according to their damage state. Tagging (red, yellow, or green) conveys information about the condition of the building (unsafe, needs further evaluation, or safe, respectively). While thorough, the process can take several days to weeks to be completed. Automated assessment is an attractive alternative to manual inspection but requires deploying a dense network of sensors at the granularity of each structure. Such a network was deemed to be impractical with respect to cost or deployment time. However, with the advent of the Internet of things (IoT) era, a massive network of citizen-owned smart devices such as tablets and smart-phones that contain vibration sensors (e.g. accelerometers) is already deployed. The objective of this work is to develop a framework that can crowd-source relatively low-quality readings from distributed smart citizen owned devices and distill that information into actionable information. This information can be provided to public safety personnel within minutes of an event, in the form of a disaster map, with buildings tagged by their most likely damage state. This paper reports on the development of an application running on a mobile phone to collect readings and coupled to a cloud-based server used to generate the necessary tags.

Smart phones are an indispensable tool in modern day-to-day life. Their widespread use has spawned numerous applications targeting diverse domains such as bio-medical, environment sensing and infrastructure monitoring. In such applications, the accuracy of the sensors at the core of the system is still questionable, since these devices are not originally designed for high accuracy sensing purposes. In this thesis, we investigate the accuracy limits of one of the commonly used sensors, namely, a smart phone accelerometer. As a use case, we focus on utilizing smart phone accelerometers in structural health monitoring (SHM). Using the already deployed network of distributed citizen-owned sensors is considered a cheap alternative to standalone sensors. These devices can capture floors vibration during disasters, and consequently compute the instantaneous displacement of each floor. Hence, damage indicators defined by government standards such as peak relative displacement can be estimated. In this work, we study the displacement estimation accuracy and propose a zero-velocity update (ZUPT) method for noise cancellation. Theoretical derivation and experimental validation are presented, and we discuss the impact of sensor error on the achieved building classification accuracy. Moreover, in spite of the presence of sensor error, SHM systems can be resilient by adopting machine learning. Several algorithms such as support vector machine (SVM), K-nearest neighbor (KNN) and convolutional neural network (CNN) are adopted and compared. Techniques for addressing noise levels are proposed and the results are compared to regular noise cancellation techniques such as filtering.

Finally, since most previous work focused on modelling the sensor chip error itself, we study other sources of error such as sampling time uncertainty which is introduced by the device operating system (OS). That type of error can be considered a major contributor to the overall error, specially for sufficiently large signals. Hence, we propose a novel smart device accelerometer error model that includes the traditional additive noise as well as sampling time uncertainty errors. The model is validated experimentally using shake table experiments, and maximum likely-hood estimation (MLE) is used to estimate the model parameters. Moreover, we derive the Cramer-Rao lower bound (CRLB) of acceleration estimation based on the proposed model.

Current techniques for assessing the effects of liquefaction-induced lateral spreading on pile foundations are based on simplified analytical methods that potentially lead to estimates that vary within a wide range. This might lead to potential excessive design demands, with high expenses for pre-event mitigation. Conversely, underestimated design demands might lead to costly post-event damage remediation.

The conducted study is directed towards enhancements to the assessment of liquefaction induced lateral spreading effects on bridge foundation systems. Current simplified analysis techniques have been only been developed recently in preliminary form. In addition, quantitative data sets from large-scale experimentation are needed concerning the response of such ground-foundation scenarios.

An effort was undertaken to address the simplified method areas of applicability and potential for enhancements. Challenges in implementing the methodology are presented within a comparative scope contrasting results of a California bridge site from different studies. On this basis, insights are derived for improvement of the currently employed simplified analysis guidelines.

Furthermore, large scale shake table testing was performed on pile foundation-ground systems, under conditions of liquefaction-induced lateral spreading. A total of 7 different experiments were conducted with varying heights, ground inclination, soil profiles, pile material and cross-section. The tested models were densely instrumented, including strain gauges, total pressure and excess pore-pressure sensors, accelerometers and displacement pots. In addition, data from 4 different experiments conducted in the NIED Japan shake table facility, including single piles and pile groups and varying soil profiles were utilized to provide additional insights and characteristics.

In these tests, the laminar soil container was placed in a mildly-inclined configuration to allow for accumulation of the liquefaction-induced lateral deformations. Detailed instrumentation and data interpretation procedures enable measurement of the fundamental soil-pile interaction behavior. The loading mechanisms have large cyclic components that may act in-phase or out-of-phase along the pile embedded length.

The conducted heavily instrumented tests resulted in a wealth of quantitative response data sets, to be used for: i) drawing insights and recommendations of practical significance based directly on the observed response, ii) calibration of simplified and more elaborate computational analysis tools, and iii) enhancement of our design guidelines and practical assessment procedures. Monotonic pushover analysis based on newly derived p-y curves in this study is found to provide useful design estimates in good agreement with the observed experimental results.

Mobile health has recently expanded to include wearable devices as a part of the vision of a holistic approach to wellness in general and health care services in particular. Once wearables become ubiquitous, they can provide healthy users, patients and doctors with an accurate reflection of the state of their body. This information will ultimately lead to better preventative medical practices and a truly personalized medical approach. Driven by the vision of a cable-free biomedical monitoring system, new wireless technologies that focus on sensor applications have been promoted as the next biomedical revolution, promising a significant improvement in the quality of health-care services. However, a major barrier to adoption of wearable technologies is the size and power requirements of wireless sensors which are typically dominated by the Radio Frequency (RF) section of the associated transceivers. There is a need to have a new class of devices that are small in area and exhibit ultra-low power consumption. An attractive solution to such emerging vision is the use of intra-body communication (IBC) systems where data transmission is achieved through the body rather than through air. Sensors and actuators can then inter-communicate through body and be relayed to a centralized wireless hub that could be a smart watch for instance. This technique would ultimately lead to body area networks (BANs) that operate at extremely low power, with minimal foot print by replacing expensive, power consuming Radio Frequency front ends, for each individual node with simpler interfaces.

In this work, we study and explore the characteristics, nature, specifications and potential of the IBC technology. We introduce novel approaches to accurately model this new channel, through simulation techniques as well as physical ones, in form of physical phantoms, to understand and model the channel behavior and relation between the system’s different components. This work aims at providing a platform for the design of body area networks that adopt IBC as means of connection between the network’s nodes. Finally, possible applications that uniquely utilize such technology are introduced, verifying its potential to boost the healthcare field.