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Magneto-Inductive Communication and Localization
Utilizing magnetic induction for wireless communication, wireless powering, passive relaying, and localization could enable massive wireless sensor applications with tiny nodes in challenging media, foremost biomedical in-body sensor networks. This work investigates the performance limits of these unique wireless systems with hardly any assumptions. As a foundation, a general system model and an interface to communication theory are developed. A major part of this work identifies two crucial magneto-inductive fading channels: that between randomly oriented coils and that caused by a nearby swarm of resonant passive relay coils. The analysis yields important technological implications. Based thereon, an investigation of wirelessly-powered in-body sensors is conducted, revealing their active and passive data transmission capabilities. Finally, a treatise of magneto-inductive node localization develops algorithms that perform near identified accuracy limits in theory and practice.
Localization and Posture Recognition via Magneto-Inductive and Relay-Aided Sensor Networks
Body-centric wireless sensor networks are expected to enable future technologies such as medical in-body micro robots or unobtrusive smart textiles. These technologies may advance personalized healthcare as they allow for tasks such as minimally invasive surgery, in-body diagnosis, and continuous activity recognition. However, the localization of individual sensor nodes within such networks or the determination of the entire network topology still pose challenges that need to be solved. This work provides both theoretic and simulative insights to enable the required sub-millimeter localization accuracy of such sensors using magneto-inductive networks. It identifies inherent localization issues such as the asymmetry of the position estimation in magneto-inductive networks and outlines how such issues may be addressed by using passive relays or cooperation. It further proposes a novel approach to recognize the entire structure of a magneto-inductive network using simple impedance measurements and clusters of passive tags. This approach is evaluated extensively by simulation and experiment to demonstrate the feasibility of low-cost human body posture recognition.
Posture Recognition for Fall Prevention with Low-Complexity UWB WBANs
In our increasingly interconnected world, personalized and technology-assisted healthcare has become a rising trend. In an ageing society, technology enables new ways to care for and assist the elderly. Falls pose a major risk and cause of injuries for senior citizens. Technology-backed fall prevention thus has the potential to avoid severe injuries and further loss of independence, but requires continuous monitoring of the body posture in order to identify imminent falls. This work presents a system concept for a wearable wireless body area network (WBAN) for posture monitoring. It shows the principal feasibility of posture recognition from ultra-wideband (UWB) signals based on a large and diverse set of measurements. For a promising classifier-feature-combination, this work demonstrates how reliable posture recognition can be achieved with a limited number of body-mounted nodes, and analyzes its robustness towards potential pitfalls. It concludes with a proposal for a system implementation, and outlines its integration with existing and future aspects of personalized healthcare.
Inclusive Radio Communications for 5G and Beyond
Inclusive Radio Communication Networks for 5G and Beyond is based on the COST IRACON project that consists of 500 researchers from academia and industry, with 120 institutions from Europe, US and the Far East involved. The book presents state-of-the-art design and analysis methods for 5G (and beyond) radio communication networks, along with key challenges and issues related to the development of 5G networks. Covers the latest research on 5G networks – including propagation, localization, IoT and radio channels Based on the International COST research project, IRACON, with 120 institutions and 500 researchers from Europe, US and the Far East involved Provides coverage of IoT protocols, architectures and applications, along with IoT applications in healthcare Contains a concluding chapter on future trends in mobile communications and networking
Computational Statistics
Computational inference is based on an approach to statistical methods that uses modern computational power to simulate distributional properties of estimators and test statistics. This book describes computationally intensive statistical methods in a unified presentation, emphasizing techniques, such as the PDF decomposition, that arise in a wide range of methods.
Fundamentals of Statistical Signal Processing, Volume 3
"For those involved in the design and implementation of signal processing algorithms, this book strikes a balance between highly theoretical expositions and the more practical treatments, covering only those approaches necessary for obtaining an optimal estimator and analyzing its performance. Author Steven M. Kay discusses classical estimation followed by Bayesian estimation, and illustrates the theory with numerous pedagogical and real-world examples."--Cover, volume 1.
Age of Information
The Age of Information is destined to become an important research topic in networked systems. This monograph provides the reader with an easy-to-read tutorial-like introduction into this novel approach of dealing with the freshness of information within systems.
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