Performance analysis with network-enhanced complexities: On fading measurements, event-triggered mechanisms, and cyber attacks

Copyright © 2014 Derui Ding et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Nowadays, the real-world systems are usually subject to various complexities such as parameter uncertainties, time-delays, and nonlinear disturbances. For networked systems, especially large-scale systems such as multiagent systems and systems over sensor networks, the complexities are inevitably enhanced in terms of their degrees or intensities because of the usage of the communication networks. Therefore, it would be interesting to (1) examine how this kind of network-enhanced complexities affects the control or filtering performance; and (2) develop some suitable approaches for controller/filter design problems. In this paper, we aim to survey some recent advances on the performance analysis and synthesis with three sorts of fashionable network-enhanced complexities, namely, fading measurements, event-triggered mechanisms, and attack behaviors of adversaries. First, these three kinds of complexities are introduced in detail according to their engineering backgrounds, dynamical characteristic, and modelling techniques. Then, the developments of the performance analysis and synthesis issues for various networked systems are systematically reviewed. Furthermore, some challenges are illustrated by using a thorough literature review and some possible future research directions are highlighted.This work was supported in part by the National Natural Science Foundation of China under Grants 61134009, 61329301, 61203139, 61374127, and 61374010, the Royal Society of the UK, and the Alexander von Humboldt Foundation of Germany

Data-driven design of intelligent wireless networks: an overview and tutorial

Data science or "data-driven research" is a research approach that uses real-life data to gain insight about the behavior of systems. It enables the analysis of small, simple as well as large and more complex systems in order to assess whether they function according to the intended design and as seen in simulation. Data science approaches have been successfully applied to analyze networked interactions in several research areas such as large-scale social networks, advanced business and healthcare processes. Wireless networks can exhibit unpredictable interactions between algorithms from multiple protocol layers, interactions between multiple devices, and hardware specific influences. These interactions can lead to a difference between real-world functioning and design time functioning. Data science methods can help to detect the actual behavior and possibly help to correct it. Data science is increasingly used in wireless research. To support data-driven research in wireless networks, this paper illustrates the step-by-step methodology that has to be applied to extract knowledge from raw data traces. To this end, the paper (i) clarifies when, why and how to use data science in wireless network research; (ii) provides a generic framework for applying data science in wireless networks; (iii) gives an overview of existing research papers that utilized data science approaches in wireless networks; (iv) illustrates the overall knowledge discovery process through an extensive example in which device types are identified based on their traffic patterns; (v) provides the reader the necessary datasets and scripts to go through the tutorial steps themselves

Novel approach to FM-based device free passive indoor localization through neural networks

Indoor Localization has been one of the most extensively researched topics for the past couple of years with a recent surge in a specific area of Device-free localization in wireless environments. Particularly FM-radio based technologies are being been preferred over WiFi-based technologies due to better penetration indoors and free availability. The major challenges for obtaining a consistent and highly accurate indoor FM based system are susceptibility to human presence, multipath fading and environmental changes. Our research works around these limitations and utilizes the environment itself to establish stronger fingerprints and thus creating a robust localization system. This novel thesis also investigates the feasibility of using neural networks to solve the problem of accuracy degradation when using a single passive receiver across multiple ambient FM radio stations. The system achieves high fidelity and temporal stability to the tunes of 95% by utilizing pattern recognition techniques for the multiple channel spectra

High Efficiency and High Sensitivity Wireless Power Transfer and Wireless Power Harvesting Systems.

In this dissertation, several approaches to improve the efficiency and sensitivity of wireless power transfer and wireless power harvesting systems, and to enhance their performance in fluctuant and unpredictable circumstances are described. Firstly, a nonlinear resonance circuit described by second-order differential equation with cubic-order nonlinearities (the Duffing equation) is developed. The Duffing nonlinear resonance circuit has significantly wider bandwidth as compared to conventional linear resonators, while achieving a similar level of amplitude. The Duffing resonator is successfully applied to the design of WPT systems to improve their tolerance to coupling factor variations stemming from changes of transmission distance and alignment of coupled coils. Subsequently, a high sensitivity wireless power harvester which collects RF energy from AM broadcast stations for powering the wireless sensors in structural health monitoring systems is introduced. The harvester demonstrates the capability of providing net RF power within 6 miles away from a local 50 kW AM station. The aforementioned Duffing resonator is also used in the design of WPH systems to improve their tolerance to frequency misalignment resulting from component aging, coupling to surrounding objects or variations of environmental conditions (temperature, humidity, etc.). At last, a rectifier array circuit with an adaptive power distribution method for wide dynamic range operation is developed. Adaptive power distribution is achieved through impedance transformation of the rectifiers’ nonlinear impedance with a passive network. The rectifier array achieves high RF-to-DC efficiency within a wide range of input power levels, and is useful in both WPT and WPH applications where levels of the RF power collected by the receiver are subject to unpredictable fluctuations.PhDElectrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/133338/1/tinyfish_1.pd

Time-Modulated Array Co-Simulation with the Aid of Commercial Software

This thesis report exhibits an integrated Electromagnetic/Circuit level technique to analyze the time modulated arrays. I restate this work in commercial software which was already developed in CAD domain i.e. combining the exact harmonic balanced based analysis of non-linear switches with the electromagnetic characterization of the radiating elements. In this commercial software I try to perform a full-wave co-simulation to compute the radiated far-field envelope to show the array behavior. Simulation in this new software allows a precise evaluation of several non-linear performance aspects of the radiating system, such as power usage capabilities and the switch modulation frequency boundary. Secondly I also discuss a TMA wireless power transfer technique which is based on two step procedure. In this case I carry out the full wave co-simulation in this new commercial software to analyze the antenna array with modulated non-linear feeding network. Schottky-diode based network provide proper modulated RF excitations of the array elements. Therefore, the array architecture is extremely simple, if compared to phased arrays, only simple control circuit board

An Approach to Finding Parking Space Using the CSI-based WiFi Technology

With ever-increasing number of vehicles and shortages of parking spaces, parking has always been a very important issue in transportation. It is necessary to use advanced intelligent technologies to help drivers find parking spaces, quickly. In this thesis, an approach to finding empty spaces in parking lots using the CSI-based WiFi technology is presented. First, the channel state information (CSI) of received WiFi signals is analyzed. The features of CSI data that are strongly correlated with the number of empty slots in parking lots are identified and extracted. A machine learning technique to perform multi-class classification that categorizes the input data into classes representing the number of empty slots is employed. A prototype system of the proposed approach is developed. Experiments are performed and it is shown that the system is feasible. Compared with traditional approaches based on magnetic sensors deployed on individual parking slots, the proposed approach is non-intrusive as it does not require to install specialized devices in a parking lot, and is cost-effective since it utilizes either existing WiFi infrastructure or only a pair of WiFi devices. As a result, the average classification accuracy of system is 80.8%, and the accuracy is improved to 93.8% with a tolerance of one empty slot

Measurements, Models, Systems and Design

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Integrated Circuit and System Design for Cognitive Radio and Ultra-Low Power Applications

The ubiquitous presence of wireless and battery-powered devices is an inseparable and invincible feature of our modern life. Meanwhile, the spectrum aggregation, and limited battery capacity of handheld devices challenge the exploding demand and growth of such radio systems. In this work, we try to present two separate solutions for each case; an ultra-wideband (UWB) receiver for Cognitive Radio (CR) applications to deal with spectrum aggregation, and an ultra-low power (ULP) receiver to enhance battery life of handheld wireless devices. Limited linearity and LO harmonics mixing are two major issues that ultra-wideband receivers, and CR in particular, are dealing with. Direct conversion schemes, based on current-driven passive mixers, have shown to improve the linearity, but unable to resolve LO harmonic mixing problem. They are usually limited to 3rd, and 5th harmonics rejection or require very complex and power hungry circuitry for higher number of harmonics. This work presents a heterodyne up-down conversion scheme in 180 nm CMOS technology for CR applications (54-862 MHz band) that mitigates the harmonic mixing issue for all the harmonics, while by employing an active feedback loop, a comparable to the state-of-the art IIP3 of better than +10 dBm is achieved. Measurements show an average NF of 7.5 dB when the active feedback loop is off (i.e. in the absence of destructive interference), and 15.5 dB when the feedback loop is active and a 0 dBm interferer is applied, respectively. Also, the second part of this work presents an ultra-low power super-regenerative receiver (SRR) suitable for OOK modulation and provides analytical insight into its design procedure. The receiver is fabricated in 40 nm CMOS technology and operates in the ISM band of 902-928 MHz. Binary search algorithm through Successive Approximation Register (SAR) architecture is being exploited to calibrate the internally generated quench signal and the working frequency of the receiver. Employing an on-chip inductor and a single-ended to differential architecture for the input amplifier has made the receiver fully integrable, eliminating the need for external components. A power consumption of 320 µW from a 0.65 V supply results in an excellent energy efficiency of 80 pJ/b at 4 Mb/s data rate. The receiver also employs an ADC that enables soft-decisioning and a convenient sensitivity-data rate trade-off, achieving sensitivity of -86.5, and -101.5 dBm at 1000 and 31.25 kbps data rate, respectivel

Autonomous Vehicles

This edited volume, Autonomous Vehicles, is a collection of reviewed and relevant research chapters, offering a comprehensive overview of recent developments in the field of vehicle autonomy. The book comprises nine chapters authored by various researchers and edited by an expert active in the field of study. All chapters are complete in itself but united under a common research study topic. This publication aims to provide a thorough overview of the latest research efforts by international authors, open new possible research paths for further novel developments, and to inspire the younger generations into pursuing relevant academic studies and professional careers within the autonomous vehicle field