Simulating and Modeling the Signal Attenuation of Wireless Local Area Network for Indoor Positioning

Location is a key filter for mobile services, including navigation or advertising. However, positioning and localization inside buildings and in indoor spaces, where users spend most of their time and where the signals of the most widely-used positioning system, i.e. Global Navigation Satellite Systems such as GPS (Global Positioning System), are not available, can be challenging. In this regard, Wireless Local Area Networks (WLAN), e.g. Wi-Fi, can be used for positioning purposes by using a WLAN-enabled device, e.g. a smartphone, to measure and match the Received Signal Strength (RSS) of a signal broadcast by an access point. The challenges of this approach are that accurate maps of RSS are required, and that measuring RSS can be affected by many factors, including the dynamics of the environment and the orientation and type of a device. This paper provides a path-loss model to produce RSS maps automatically from floor plans and introduces an agent-based simulation approach to investigate different positioning methods. This provides a pathway to reduce the time and effort associated with WLAN positioning research

Data Analysis and Memory Methods for RSS Bluetooth Low Energy Indoor Positioning

The thesis aims at finding a feasible solution to Bluetooth low energy indoor positioning (BLE-IP) including comprehensive data analysis of the received signal strength indication (RSSI) values. The data analysis of RSSI values was done to understand different factors influencing the RSSI values so as to gain better understanding of data generating process and to improve the data model. The positioning task is accomplished using a methodology called \textit{fingerprinting}. The fingerprinting based positioning involves two phases namely \textit{calibration phase} and \textit{localization phase}. The localization phase utilises the memory methods for positioning. In this thesis, we have used \textit{Gaussian process} for generation of radio maps and for localization we focus on memory methods: \textit{particle filters} and \textit{unscented Kalman filters}. The Gaussian process radio map is used as the measurement model in the Bayesian filtering context. The optimal fingerprinting phase parameters were determined and the filtering methods were evaluated in terms root mean square error

On power line positioning systems

Power line infrastructure is available almost everywhere. Positioning systems aim to estimate where a device or target is. Consequently, there may be an opportunity to use power lines for positioning purposes. This survey article reports the different efforts, working principles, and possibilities for implementing positioning systems relying on power line infrastructure for power line positioning systems (PLPS). Since Power Line Communication (PLC) systems of different characteristics have been deployed to provide communication services using the existing mains, we also address how PLC systems may be employed to build positioning systems. Although some efforts exist, PLPS are still prospective and thus open to research and development, and we try to indicate the possible directions and potential applications for PLPS.European Commissio

Exploitation of Unintentional Information Leakage from Integrated Circuits

Unintentional electromagnetic emissions are used to recognize or verify the identity of a unique integrated circuit (IC) based on fabrication process-induced variations in a manner analogous to biometric human identification. The effectiveness of the technique is demonstrated through an extensive empirical study, with results presented indicating correct device identification success rates of greater than 99:5%, and average verification equal error rates (EERs) of less than 0:05% for 40 near-identical devices. The proposed approach is suitable for security applications involving commodity commercial ICs, with substantial cost and scalability advantages over existing approaches. A systematic leakage mapping methodology is also proposed to comprehensively assess the information leakage of arbitrary block cipher implementations, and to quantitatively bound an arbitrary implementation\u27s resistance to the general class of differential side channel analysis techniques. The framework is demonstrated using the well-known Hamming Weight and Hamming Distance leakage models, and approach\u27s effectiveness is demonstrated through the empirical assessment of two typical unprotected implementations of the Advanced Encryption Standard. The assessment results are empirically validated against correlation-based differential power and electromagnetic analysis attacks

Complete Higgs sector constraints on dimension-6 operators

Constraints on the full set of Standard Model dimension-6 operators have previously used triple-gauge couplings to complement the constraints obtainable from Higgs signal strengths. Here we extend previous analyses of the Higgs sector constraints by including information from the associated production of Higgs and massive vector bosons (H+V production), which excludes a direction of limited sensitivity allowed by partial cancellations in the triple-gauge sector measured at LEP. Kinematic distributions in H+V production provide improved sensitivity to dimension-6 operators, as we illustrate here with simulations of the invariant mass and pT distributions measured by D0 and ATLAS, respectively. We provide bounds from a global fit to a complete set of CP-conserving operators affecting Higgs physics

Location-Enabled IoT (LE-IoT): A Survey of Positioning Techniques, Error Sources, and Mitigation

The Internet of Things (IoT) has started to empower the future of many industrial and mass-market applications. Localization techniques are becoming key to add location context to IoT data without human perception and intervention. Meanwhile, the newly-emerged Low-Power Wide-Area Network (LPWAN) technologies have advantages such as long-range, low power consumption, low cost, massive connections, and the capability for communication in both indoor and outdoor areas. These features make LPWAN signals strong candidates for mass-market localization applications. However, there are various error sources that have limited localization performance by using such IoT signals. This paper reviews the IoT localization system through the following sequence: IoT localization system review -- localization data sources -- localization algorithms -- localization error sources and mitigation -- localization performance evaluation. Compared to the related surveys, this paper has a more comprehensive and state-of-the-art review on IoT localization methods, an original review on IoT localization error sources and mitigation, an original review on IoT localization performance evaluation, and a more comprehensive review of IoT localization applications, opportunities, and challenges. Thus, this survey provides comprehensive guidance for peers who are interested in enabling localization ability in the existing IoT systems, using IoT systems for localization, or integrating IoT signals with the existing localization sensors