349 research outputs found

    Doctor of Philosophy

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    dissertationThe wireless radio channel is typically thought of as a means to move information from transmitter to receiver, but the radio channel can also be used to detect changes in the environment of the radio link. This dissertation is focused on the measurements we can make at the physical layer of wireless networks, and how we can use those measurements to obtain information about the locations of transceivers and people. The first contribution of this work is the development and testing of an open source, 802.11b sounder and receiver, which is capable of decoding packets and using them to estimate the channel impulse response (CIR) of a radio link at a fraction of the cost of traditional channel sounders. This receiver improves on previous implementations by performing optimized matched filtering on the field-programmable gate array (FPGA) of the Universal Software Radio Peripheral (USRP), allowing it to operate at full bandwidth. The second contribution of this work is an extensive experimental evaluation of a technology called location distinction, i.e., the ability to identify changes in radio transceiver position, via CIR measurements. Previous location distinction work has focused on single-input single-output (SISO) radio links. We extend this work to the context of multiple-input multiple-output (MIMO) radio links, and study system design trade-offs which affect the performance of MIMO location distinction. The third contribution of this work introduces the "exploiting radio windows" (ERW) attack, in which an attacker outside of a building surreptitiously uses the transmissions of an otherwise secure wireless network inside of the building to infer location information about people inside the building. This is possible because of the relative transparency of external walls to radio transmissions. The final contribution of this dissertation is a feasibility study for building a rapidly deployable radio tomographic (RTI) imaging system for special operations forces (SOF). We show that it is possible to obtain valuable tracking information using as few as 10 radios over a single floor of a typical suburban home, even without precise radio location measurements

    Device Free Localisation Techniques in Indoor Environments

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    The location estimation of a target for a long period was performed only by device based localisation technique which is difficult in applications where target especially human is non-cooperative. A target was detected by equipping a device using global positioning systems, radio frequency systems, ultrasonic frequency systems, etc. Device free localisation (DFL) is an upcoming technology in automated localisation in which target need not equip any device for identifying its position by the user. For achieving this objective, the wireless sensor network is a better choice due to its growing popularity. This paper describes the possible categorisation of recently developed DFL techniques using wireless sensor network. The scope of each category of techniques is analysed by comparing their potential benefits and drawbacks. Finally, future scope and research directions in this field are also summarised

    Design of a WSN Platform for Long-Term Environmental Monitoring for IoT Applications

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    The Internet of Things (IoT) provides a virtual view, via the Internet Protocol, to a huge variety of real life objects, ranging from a car, to a teacup, to a building, to trees in a forest. Its appeal is the ubiquitous generalized access to the status and location of any "thing" we may be interested in. Wireless sensor networks (WSN) are well suited for long-term environmental data acquisition for IoT representation. This paper presents the functional design and implementation of a complete WSN platform that can be used for a range of long-term environmental monitoring IoT applications. The application requirements for low cost, high number of sensors, fast deployment, long lifetime, low maintenance, and high quality of service are considered in the specification and design of the platform and of all its components. Low-effort platform reuse is also considered starting from the specifications and at all design levels for a wide array of related monitoring application

    Doctor of Philosophy

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    dissertationWe are seeing an extensive proliferation of wireless devices including various types and forms of sensor nodes that are increasingly becoming ingrained in our daily lives. There has been a significant growth in wireless devices capabilities as well. This proliferation and rapid growth of wireless devices and their capabilities has led to the development of many distributed sensing and computing applications. In this dissertation, we propose and evaluate novel, efficient approaches for localization and computation offloading that harness distributed sensing and computing in wireless networks. In a significant part of this dissertation, we exploit distributed sensing to create efficient localization applications. First, using the sensing power of a set of Radio frequency (RF) sensors, we propose energy efficient approaches for target tracking application. Second, leveraging the sensing power of a distributed set of existing wireless devices, e.g., smartphones, internet-of-things devices, laptops, and modems, etc., we propose a novel approach to locate spectrum offenders. Third, we build efficient sampling approaches to select mobile sensing devices required for spectrum offenders localization. We also enhance our sampling approaches to take into account selfish behaviors of mobile devices. Finally, we investigate an attack on location privacy where the location of people moving inside a private area can be inferred using the radio characteristics of wireless links that are leaked by legitimate transmitters deployed inside the private area, and develop the first solution to mitigate this attack. While we focus on harnessing distributed sensing for localization in a big part of this dissertation, in the remaining part of this dissertation, we harness the computing power of nearby wireless devices for a computation offloading application. Specially, we propose a multidimensional auction for allocating the tasks of a job among nearby mobile devices based on their computational capabilities and also the cost of computation at these devices with the goal of reducing the overall job completion time and being beneficial to all the parties involved

    Doctor of Philosophy

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    dissertationLow-cost wireless embedded systems can make radio channel measurements for the purposes of radio localization, synchronization, and breathing monitoring. Most of those systems measure the radio channel via the received signal strength indicator (RSSI), which is widely available on inexpensive radio transceivers. However, the use of standard RSSI imposes multiple limitations on the accuracy and reliability of such systems; moreover, higher accuracy is only accessible with very high-cost systems, both in bandwidth and device costs. On the other hand, wireless devices also rely on synchronized notion of time to coordinate tasks (transmit, receive, sleep, etc.), especially in time-based localization systems. Existing solutions use multiple message exchanges to estimate time offset and clock skew, which further increases channel utilization. In this dissertation, the design of the systems that use RSSI for device-free localization, device-based localization, and breathing monitoring applications are evaluated. Next, the design and evaluation of novel wireless embedded systems are introduced to enable more fine-grained radio signal measurements to the application. I design and study the effect of increasing the resolution of RSSI beyond the typical 1 dB step size, which is the current standard, with a couple of example applications: breathing monitoring and gesture recognition. Lastly, the Stitch architecture is then proposed to allow the frequency and time synchronization of multiple nodes' clocks. The prototype platform, Chronos, implements radio frequency synchronization (RFS), which accesses complex baseband samples from a low-power low-cost narrowband radio, estimates the carrier frequency offset, and iteratively drives the difference between two nodes' main local oscillators (LO) to less than 3 parts per billion (ppb). An optimized time synchronization and ranging protocols (EffToF) is designed and implemented to achieve the same timing accuracy as the state-of-the-art but with 59% less utilization of the UWB channel. Based on this dissertation, I could foresee Stitch and RFS further improving the robustness of communications infrastructure to GPS jamming, allow exploration of applications such as distributed beamforming and MIMO, and enable new highly-synchronous wireless sensing and actuation systems

    Whitepaper on New Localization Methods for 5G Wireless Systems and the Internet-of-Things

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    Intelligent spectrum management techniques for wireless cognitive radio networks

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    PhD ThesisThis thesis addresses many of the unique spectrum management chal- lenges in CR networks for the rst time. These challenges have a vital e ect on the network performance and are particularly di cult to solve due to the unique characteristics of CR networks. Speci cally, this thesis proposes and investigates three intelligent spectrum management tech- niques for CR networks. The issues investigated in this thesis have a fundamental impact on the establishment, functionality and security of CR networks. First, an intelligent primary receiver-aware message exchange protocol for CR ad hoc networks is proposed. It considers the problem of alleviat- ing the interference collision risk to primary user communication, explic- itly to protect primary receivers that are not detected during spectrum sensing. The proposed protocol achieves a higher measure of safeguard- ing. A practical scenario is considered where no global network topology is known and no common control channel is assumed to exist. Second, a novel CR broadcast protocol (CRBP) to reliably disseminate the broadcast messages to all or most of the possible CR nodes in the network is proposed. The CRBP formulates the broadcast problem as a bipartite-graph problem. Thus, CRBP achieves a signi cant successful delivery ratio by connecting di erent local topologies, which is a unique feature in CR ad hoc networks. Finally, a new defence strategy to defend against spectrum sensing data falsi cation attacks in CR networks is proposed. In order to identify malicious users, the proposed scheme performs multiple veri cations of sensory data with the assistance of trusted nodes.Higher Committee For Education Devel- opment in Iraq (HCED-Iraq

    Five Facets of 6G: Research Challenges and Opportunities

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    Whilst the fifth-generation (5G) systems are being rolled out across the globe, researchers have turned their attention to the exploration of radical next-generation solutions. At this early evolutionary stage we survey five main research facets of this field, namely {\em Facet~1: next-generation architectures, spectrum and services, Facet~2: next-generation networking, Facet~3: Internet of Things (IoT), Facet~4: wireless positioning and sensing, as well as Facet~5: applications of deep learning in 6G networks.} In this paper, we have provided a critical appraisal of the literature of promising techniques ranging from the associated architectures, networking, applications as well as designs. We have portrayed a plethora of heterogeneous architectures relying on cooperative hybrid networks supported by diverse access and transmission mechanisms. The vulnerabilities of these techniques are also addressed and carefully considered for highlighting the most of promising future research directions. Additionally, we have listed a rich suite of learning-driven optimization techniques. We conclude by observing the evolutionary paradigm-shift that has taken place from pure single-component bandwidth-efficiency, power-efficiency or delay-optimization towards multi-component designs, as exemplified by the twin-component ultra-reliable low-latency mode of the 5G system. We advocate a further evolutionary step towards multi-component Pareto optimization, which requires the exploration of the entire Pareto front of all optiomal solutions, where none of the components of the objective function may be improved without degrading at least one of the other components
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