Signal Processing in Wireless Communications: Device Fingerprinting and Wide-Band Interference Rejection

The rapid progress of wireless communication technologies that has taken place in recent years has significantly improved the quality of everyday life. However with this expansion of wireless communication systems come significant security threats and significant technological challenges, both of which are due to the fact that the communication medium is shared. The ubiquity of open wireless Internet access networks creates a new avenue for cyber-criminals to impersonate and act in an unauthorized way. The increasing number of deployed wide-band wireless communication systems entails technological challenges for effective utilization of the shared medium, which implies the need for advanced interference rejection methods. Wireless security and interference rejection in wide-band wireless communications are therefore often considered as the two main challenges in wireless network\u27s design and research. Important aspects of these challenges are illuminated and addressed in this dissertation. This dissertation considers signal processing approaches for exploiting or mitigating the effects of non-ideal components in wireless communication systems. In the first part of the dissertation, we introduce and study a novel, model-based approach to wireless device identification that exploits imperfections in the transmitter caused by manufacturing process nonidealities. Previous approaches to device identification based on hardware imperfections vary from transient analysis to machine learning but have not provided verifiable accuracy. Here, we detail a model-based approach, that uses statistical models of RF transmitter components: digital-to-analog converter, power amplifier and RF oscillator, which are amenable for analysis. Our proposed approach examines the key device characteristics that cause anonymity loss, countermeasures that can be applied by the nodes to regain the anonymity, and ways of thwarting such countermeasures. We develop identification algorithms based on statistical signal processing methods and address the challenging scenario when the units that need to be distinguished from one another are of the same model and from the same manufacturer. Using simulations and measurements of components that are commonly used in commercial communications systems, we show that our anonymity breaking techniques are effective. In the second part of the dissertation, we consider innovative approaches for the acquisition of frequency-sparse signals with wide-band receivers when a weak signal of interest is received in the presence of a very strong interference, and the effects of the nonlinearities in the low-noise amplifier at the receiver must be mitigated. All samples with amplitude above a given threshold, dictated by the linear input range of the receiver, are discarded to avoid the distortion caused by saturation of the low noise amplifier. Such a sampling scheme, while avoiding nonlinear distortion that cannot be corrected in the digital domain, poses challenges for signal reconstruction techniques, as the samples are taken non-uniformly, but also non-randomly. The considered approaches fall into the field of compressive sensing (CS); however, what differentiates them from conventional CS is that a structure is forced upon the measurement scheme. Such a structure causes a violation of the core CS assumption of the measurements\u27 randomness. We consider two different types of structured acquisition: signal independent and signal dependent structured acquisition. For the first case, we derive bounds on the number of samples needed for successful CS recovery when samples are drawn at random in predefined groups. For the second case, we consider enhancements of CS recovery methods when only small-amplitude samples of the signal that needs to be recovered are available for the recovery. Finally, we address a problem of spectral leakage due to the limited processing block size of block processing, wide-band receivers and propose an adaptive block size adjustment method, which leads to significant dynamic range improvements

Software-Defined Lighting.

For much of the past century, indoor lighting has been based on incandescent or gas-discharge technology. But, with LED lighting experiencing a 20x/decade increase in flux density, 10x/decade decrease in cost, and linear improvements in luminous efficiency, solid-state lighting is finally cost-competitive with the status quo. As a result, LED lighting is projected to reach over 70% market penetration by 2030. This dissertation claims that solid-state lighting’s real potential has been barely explored, that now is the time to explore it, and that new lighting platforms and applications can drive lighting far beyond its roots as an illumination technology. Scaling laws make solid-state lighting competitive with conventional lighting, but two key features make solid-state lighting an enabler for many new applications: the high switching speeds possible using LEDs and the color palettes realizable with Red-Green-Blue-White (RGBW) multi-chip assemblies. For this dissertation, we have explored the post-illumination potential of LED lighting in applications as diverse as visible light communications, indoor positioning, smart dust time synchronization, and embedded device configuration, with an eventual eye toward supporting all of them using a shared lighting infrastructure under a unified system architecture that provides software-control over lighting. To explore the space of software-defined lighting (SDL), we design a compact, flexible, and networked SDL platform to allow researchers to rapidly test new ideas. Using this platform, we demonstrate the viability of several applications, including multi-luminaire synchronized communication to a photodiode receiver, communication to mobile phone cameras, and indoor positioning using unmodified mobile phones. We show that all these applications and many other potential applications can be simultaneously supported by a single lighting infrastructure under software control.PhDElectrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/111482/1/samkuo_1.pd

Seamount structure and subduction at the Louisville Ridge – Tonga-Kermadec collision

The Louisville Ridge (LRSC) is an ~4000 km-long SW Pacific seamount chain currently being subducted at the Tonga-Kermadec Trench (TKT). Both the trend of the LRSC and the subduction of the Pacific plate are oblique to the trench, resulting in southward migration of the intersection point at a rate of 120-180 mm yr-1, and producing significant along-strike variation in forearc structure and seismicity. The LRSC-TKT intersection was investigated by a multi-disciplinary geophysical experiment aboard the R/V Sonne in 2011, acquiring multichannel and wide-angle seismic, gravity, and bathymetry data, to better understand the effect of subducting bathymetric features on forearc deformation. As part of this, it is necessary to determine the structure and characteristics of the incoming seamounts, and how they are deformed during subduction. This study is underpinned by an ~725 km-long profile traversing the oldest extant LRSC seamounts, that continues along its projection into the trench and forearc. LRSC seamounts display a range of internal structures, including shallow, high-velocity (≥6 km s-1) cores. The also sit on crust that is not significantly thickened. At the trench, Osbourn seamount is experiencing bend-induced normal faulting which suggests that each seamount may be disarticulated to a size smaller than the imaging resolution. Observed similarity between the P-wave velocity structure of seamount flank material and ordinary subducting oceanic crust also suggests that distinguishing between these in the trench-forearc region is challenging. Consequently, it is not unequivocally possible to determine, within the confines of the profile locations and model resolution, whether the last LRSC seamount to have subducted, was subducted intact along the continuation of the trend of the extant chain. Along-margin observations indicate that significant seamount-related forearc deformation is superimposed on pre-existing crustal structures, with the maximum deformation occurring in the wake of the migration of active collision. Observations of forearc morphology at the present-day intersection point support those from seismicity and plate reconstruction, which suggests that this location may also coincide with a westerly rotation in the trend of the chain

An Object-oriented expert system shell with image diagnosis.

by Chan Wai Kwong Samual.Thesis (M.Phil.)--Chinese University of Hong Kong.Bibliography: leaves R. 1-6.ACKNOWLEDGEMENTSABSTRACTTABLE OF CONTENTSChapter CHAPTER 1. --- OVERVIEWS --- p.1.1Chapter 1.1 --- Introduction --- p.1.1Chapter 1.2 --- Image Understanding and Artificial Intelligence --- p.1.3Chapter 1.3 --- Object-Oriented Programming and Artificial Intelligence --- p.1.6Chapter 1.4 --- Related Works --- p.1.8Chapter 1.5 --- Discussions and Outlines --- p.1.9Chapter CHAPTER 2. --- OBJECT-ORIENTED SOFTWARE SYSTEMS --- p.2.1Chapter 2.1 --- Introduction --- p.2.1Chapter 2.2 --- Traditional Software Systems --- p.2.1Chapter 2.3 --- Object-Oriented Software Systems --- p.2.2Chapter 2.4 --- Characteristics of an Object-Oriented Systems --- p.2.4Chapter 2.5 --- Knowledge Representation in Image Recognition --- p.2.9Chapter 2.5.1 --- Rule-Based System --- p.2.10Chapter 2.5.2 --- Structured Objects --- p.2.12Chapter 2.5.3 --- Object-Oriented Knowledge Management --- p.2.13Chapter 2.5.4 --- Object-Oriented Expert System Building Tools --- p.2.14Chapter 2.6 --- Concluding Remarks --- p.2.16Chapter CHAPTER 3. --- SYSTEM DESIGN AND ARCHITECTURE --- p.3.1Chapter 3.1 --- Introduction --- p.3.1Chapter 3.2 --- Inheritance and Recognition --- p.3.2Chapter 3.3 --- System Design --- p.3.9Chapter 3.4 --- System Architecture --- p.3.11Chapter 3.4.1 --- The Low Level Vision Kernel --- p.3.14Chapter 3.4.2 --- The High Level Vision Kernel --- p.3.15Chapter 3.4.3 --- User Consultation Kernel --- p.3.17Chapter 3.5 --- Structure of the Image Object Model --- p.3.17Chapter 3.5.1 --- Image Object Model in Object-Oriented Form --- p.3.19Chapter 3.5.2 --- Image Objects Hierarchy --- p.3.23Chapter 3.6 --- Reasoning in OOI --- p.3.26Chapter 3.7 --- Concluding Remarks --- p.3.27Chapter CHAPTER 4. --- CONTROL AND STRATEGIES --- p.4.1Chapter 4.1 --- Introduction --- p.4.1Chapter 4.2 --- Consultation Class Objects --- p.4.4Chapter 4.2.1 --- Audience --- p.4.5Chapter 4.2.2 --- Intrinsic Hypothesis (IH_object) --- p.4.5Chapter 4.2.3 --- Priority Table (PT_object) --- p.4.6Chapter 4.3 --- Operation Objects --- p.4.7Chapter 4.3.1 --- Scheme Scheduler (SS一object) --- p.4.7Chapter 4.3.2 --- Task Scheduler (TS_object) --- p.4.7Chapter 4.4 --- Taxonomy of Image Objects in OOI --- p.4.8Chapter 4.4.1 --- Object Template --- p.4.8Chapter 4.4.2 --- Attributes --- p.4.9Chapter 4.4.3 --- Tasks and Life Cycles --- p.4.9Chapter 4.4.4 --- Object Security --- p.4.10Chapter 4.5 --- Message Passing --- p.4.11Chapter 4.6 --- Strategies --- p.4.12Chapter 4.6.1 --- The Bottom-Up Approach --- p.4.15Chapter 4.6.2 --- The Top-Down Approach --- p.4.18Chapter 4.7 --- Concluding Remarks --- p.4.19Chapter CHAPTER 5. --- IMAGE PROCESSING ALGORITHMS --- p.5.1Chapter 5.1 --- Introduction --- p.5.1Chapter 5.2 --- Image Enhancement --- p.5.2Chapter 5.2.1 --- Spatial Filtering --- p.5.2Chapter 5.2.2 --- Feature Enhancement --- p.5.5Chapter 5.3 --- Pixel Classification --- p.5-7Chapter 5.4 --- Edge Detection Methods --- p.5.9Chapter 5.4.1 --- Local Gradient Operators --- p.5.9Chapter 5.4.2 --- Zero Crossing Method --- p.5.12Chapter 5.5 --- Regional Approaches in Segmentation --- p.5.13Chapter 5.5.1 --- Multi-level Threshold Method --- p.5.13Chapter 5.5.2 --- Region Growing --- p.5.15Chapter 5.6 --- Image Processing Techniques in Medical Domain --- p.5.17Chapter 5.7 --- Concluding Remarks --- p.5.18Chapter CHAPTER 6. --- PICTORIAL DATA MANAGEMENT IN OOI --- p.6.1Chapter 6.1 --- Introduction --- p.6.1Chapter 6.2 --- Description of Basic Properties --- p.6.1Chapter 6.3 --- Description of Relations --- p.6.7Chapter 6.3.1 --- Relational Database of Pictorial Data --- p.6.7Chapter 6.3.2 --- Relational Graphs and Relational Databases --- p.6.10Chapter 6.4 --- Access Functions in Image Objects --- p.6.14Chapter 6.4.1 --- Basic Access Functions --- p.6.14Chapter 6.4.2 --- User Accessible Functions in Objects --- p.6.15Chapter 6.5 --- Image Functions --- p.6.16Chapter 6.5.1 --- Unary Image operations --- p.6.16Chapter 6.5.2 --- Binary Relation Operations --- p.6.19Chapter 6.5.3 --- Update Operations --- p.6.20Chapter 6.6 --- Concluding Remarks --- p.6.21Chapter CHAPTER 7. --- KNOWLEDGE MANAGEMENT --- p.7.1Chapter 7.1 --- Introduction --- p.7.1Chapter 7.2 --- Knowledge in A Domain Knowledge Base --- p.7.1Chapter 7.2.1 --- Structure of Rules --- p.7.2Chapter 7.2.2 --- Hypothesis Generation --- p.7.6Chapter 7.2.3 --- Inference Engine --- p.7.8Chapter 7.3 --- Model Based Reasoning in OOI --- p.7.9Chapter 7.3.1 --- Merging and Labelling --- p.7.9Chapter 7.3.2 --- Vision Model --- p.7.11Chapter 7.4 --- Fuzzy Reasoning --- p.7.12Chapter 7.5 --- Concluding Remarks --- p.7.15Chapter CHAPTER 8. --- KNOWLEDGE ACQUISITION AND USER INTERFACES --- p.8.1Chapter 8.1 --- Introduction --- p.8.1Chapter 8.2 --- Knowledge Acquisition Subsystem --- p.8.3Chapter 8.2.1 --- Rule Management Module --- p.8.3Chapter 8.2.2 --- Attribute Management Module --- p.8.4Chapter 8.2.3 --- Model Management Module --- p.8.8Chapter 8.2.4 --- Methods of Knowledge Encoding and Acquisition --- p.8.9Chapter 8.3 --- User Interface in OOI --- p.8.11Chapter 8.3.1 --- Screen Layout --- p.8.13Chapter 8.3.2 --- Menus and Options --- p.8.15Chapter 8.4 --- Concluding Remarks --- p.8.20Chapter CHAPTER 9. --- IMPLEMENTATION AND RESULTS --- p.9.1Chapter 9.1 --- Introduction --- p.9.1Chapter 9.2 --- Using Expanded Memory --- p.9.2Chapter 9.3 --- ESCUM --- p.9.3Chapter 9.3.1 --- General Description --- p.9.3Chapter 9.3.2 --- Cervical Intraepithelial Neoplasia (CIN) --- p.9.4Chapter 9.3.3 --- Development of ESCUM --- p.9.5Chapter 9.4 --- Results --- p.9.12Chapter 9.5 --- Concluding Remarks --- p.9.13Chapter CHAPTER 10. --- CONCLUSION --- p.10.1Chapter 10.1 --- Summary --- p.10.1Chapter 10.2 --- Areas of Future Work --- p.10.5Chapter APPENDIX A. --- Rule Base of ESCUM --- p.A1Chapter APPENDIX B. --- Glossary for Objected-Oriented Programming --- p.B1REFERENCES --- p.R

Concept definition for space station technology development experiments. Experiment definition, task 2

The second task of a study with the overall objective of providing a conceptual definition of the Technology Development Mission Experiments proposed by LaRC on space station is discussed. During this task, the information (goals, objectives, and experiment functional description) assembled on a previous task was translated into the actual experiment definition. Although still of a preliminary nature, aspects such as: environment, sensors, data acquisition, communications, handling, control telemetry requirements, crew activities, etc., were addressed. Sketches, diagrams, block diagrams, and timeline analyses of crew activities are included where appropriate

Apollo-Soyuz test project. Volume 1: Astronomy, earth atmosphere and gravity field, life sciences, and materials processing

The joint U.S.-USSR experiments and the U.S. conducted unilateral experiments performed during the Apollo Soyuz Test Project are described. Scientific concepts and experiment design and operation are discussed along with scientific results of postflight analysis

Applications of MATLAB in Science and Engineering

The book consists of 24 chapters illustrating a wide range of areas where MATLAB tools are applied. These areas include mathematics, physics, chemistry and chemical engineering, mechanical engineering, biological (molecular biology) and medical sciences, communication and control systems, digital signal, image and video processing, system modeling and simulation. Many interesting problems have been included throughout the book, and its contents will be beneficial for students and professionals in wide areas of interest

Alternate avionics system study and phase B extension

Results of alternate avionics system studies for the space shuttle are presented that reduce the cost of vehicle avionics without incurring major off-setting costs on the ground. A comprehensive summary is provided of all configurations defined since the completion of the basic Phase B contract and a complete description of the optimized avionics baseline is given. In the new baseline, inflight redundancy management is performed onboard without ground support; utilization of off-the-shelf hardware reduces the cost figure substantially less than for the Phase B baseline. The only functional capability sacrificed in the new approach is automatic landing