Relative Span weighted localization of uncooperative nodes in wireless networks

Increasingly ubiquitous wireless technologies require novel localization techniques to pinpoint the position of an uncooperative node, whether the target be a malicious device engaging in a security exploit or a low-battery handset in the middle of a critical emergency. Such scenarios necessitate that a radio signal source be localized by other network nodes efficiently, using minimal information. We propose two new algorithms for estimating the position of an uncooperative transmitter, based on the received signal strength (RSS) of a single target message at a set of receivers whose coordinates are known. As an extension to the concept of centroid localization, our mechanisms weigh each receiver's coordinates based on the message's relative RSS at that receiver, with respect to the span of RSS values over all receivers. The weights may decrease from the highest RSS receiver either linearly or exponentially. Our simulation results demonstrate that for all but the most sparsely populated wireless networks, our exponentially weighted mechanism localizes a target node within the regulations stipulated for emergency services location accuracy

Blind localization of radio emitters in wireless communications

The proliferation of wireless services is expected to increase the demand for radio spectrum in the foreseeable future. Given the limitations of the radio spectrum, it is evident that the current fixed frequency assignment policy fails to accommodate this increasing demand. Thus, the need for innovative technologies that can scale to accommodate future demands both in terms of spectrum efficiency and high reliable communication. Cognitive radio (CR) is one of the emerging technologies that offers a more flexible use of frequency bands allowing unlicensed users to exploit and use portions of the spectrum that are temporarily unused without causing any potential harmful interference to the incumbents. The most important functionality of a CR system is to observe the radio environment through various spectrum awareness techniques e.g., spectrum sensing or detection of spectral users in the spatio-temporal domain. In this research, we mainly focus on one of the key cognitive radio enabling techniques called localization, which provides crucial geo-location of the unknown radio transmitter in the surrounding environment. Knowledge of the user’s location can be very useful in enhancing the functionality of CRs and allows for better spectrum resource allocations in the spatial domain. For instance, the location-awareness feature can be harnessed to accomplish CR tasks such as spectrum sensing, dynamic channel allocation and interference management to enable cognitive radio operation and hence to maximize the spectral utilization. Additionally, geo-location can significantly expand the capabilities of many wireless communication applications ranging from physical layer security, geo-routing, energy efficiency, and a large set of emerging wireless sensor network and social networking applications. We devote the first part of this research to explore a broad range of existing cooperative localization techniques and through Monte-Carlo simulations analyze the performance of such techniques. We also propose two novel techniques that offer better localization performance with respect to the existing ones. The second and third parts of this research put forth a new analytical framework to characterize the performance of a particular low-complexity localization technique called weighted centroid localization (WCL), based on the statistical distribution of the ratio of two quadratic forms in normal variables. Specifically, we evaluate the performance of WCL in terms of the root mean square error (RMSE) and cumulative distribution function (CDF). The fourth part of this research focuses on studying the bias of the WCL and also provides solutions for bias correction. Throughout this research, we provide a case study analysis to evaluate the performance of the proposed approaches under changing channel and environment conditions. For the new theoretical framework, we compare analytical and Monte-Carlo simulation results of the performance metric of interest. A key contribution in our analysis is that we present not only the accurate performance in terms of the RMSE and CDF, but a new analytical framework that takes into consideration the finite nature of the network, overcoming the limitations of asymptotic results based on the central limit theorem. Remarkably, the numerical results unfold that the new analytical framework is able to predict the performance of WCL capturing all the essential aspects of propagation as well as the cognitive radio network spatial topology. Finally, we present conclusions gained from this research and possible future directions

The Optimum Location for Access Point Deployment based on RSS for Indoor Communication

YesIn indoor wireless communication networks, the optimal locations had been known to deploy the access points (AP's) which has a significant impact on improving various aspects of network operation, management, and coverage. In addition, develop the behavioral characteristics of the wireless network. The most used approach for localization purposes was based on Received Signal Strength (RSS) measurements, which is widely used in the wireless network. As well as, it can be easily accessed from different operating systems. In this paper, we proposed an optimal AP localization algorithm based on RSS measurement obtained from different received points. This localization algorithm works as a complementary to the 3D Ray tracing model based REMCOM wireless InSite software and considered two-step localization approach, data collection phase, and localization phase. Obtained result give relatively high accuracy to select the optimum location for AP compare with other selected locations. It is worth to mention that effect of different building materials on signal propagation has been considered with specifying the optimum location of deployment. Furthermore, channel characterizations that based on path losses have been considered as a confirmation for the optimum location being selected

PRLS-INVES: A General Experimental Investigation Strategy for High Accuracy and Precision in Passive RFID Location Systems

Due to cost-effectiveness and easy-deployment, radio-frequency identification (RFID) location systems are widely utilized into many industrial fields, particularly in the emerging environment of the Internet of Things (IoT). High accuracy and precision are key demands for these location systems. Numerous studies have attempted to improve localization accuracy and precision using either dedicated RFID infrastructures or advanced localization algorithms. But these effects mostly consider utilization of novel RFID localization solutions rather than optimization of this utilization. Practical use of these solutions in industrial applications leads to increased cost and deployment difficulty of RFID system. This paper attempts to investigate how accuracy and precision in passive RFID location systems (PRLS) are impacted by infrastructures and localization algorithms. A general experimental-based investigation strategy, PRLS-INVES, is designed for analyzing and evaluating the factors that impact the performance of a passive RFID location system. Through a case study on passive high frequency (HF) RFID location systems with this strategy, it is discovered that: 1) the RFID infrastructure is the primary factor determining the localization capability of an RFID location system and 2) localization algorithm can improve accuracy and precision, but is limited by the primary factor. A discussion on how to efficiently improve localization accuracy and precision in passive HF RFID location systems is given

Physical Layer Challenges and Solutions in Seamless Positioning via GNSS, Cellular and WLAN Systems

As different positioning applications have started to be a common part of our lives, positioning methods have to cope with increasing demands. Global Navigation Satellite System (GNSS) can offer accurate location estimate outdoors, but achieving seamless large-scale indoor localization remains still a challenging topic. The requirements for simple and cost-effective indoor positioning system have led to the utilization of wireless systems already available, such as cellular networks and Wireless Local Area Network (WLAN). One common approach with the advantage of a large-scale standard-independent implementation is based on the Received Signal Strength (RSS) measurements.This thesis addresses both GNSS and non-GNSS positioning algorithms and aims to offer a compact overview of the wireless localization issues, concentrating on some of the major challenges and solutions in GNSS and RSS-based positioning. The GNSS-related challenges addressed here refer to the channel modelling part for indoor GNSS and to the acquisition part in High Sensitivity (HS)-GNSS. The RSSrelated challenges addressed here refer to the data collection and calibration, channel effects such as path loss and shadowing, and three-dimensional indoor positioning estimation.This thesis presents a measurement-based analysis of indoor channel models for GNSS signals and of path loss and shadowing models for WLAN and cellular signals. Novel low-complexity acquisition algorithms are developed for HS-GNSS. In addition, a solution to transmitter topology evaluation and database reduction solutions for large-scale mobile-centric RSS-based positioning are proposed. This thesis also studies the effect of RSS offsets in the calibration phase and various floor estimators, and offers an extensive comparison of different RSS-based positioning algorithms

Optimization of a boundary element approach to electromagnet design with application to a host of current problems in Magnetic Resonance Imaging

Magnetic resonance imaging (MRI) has proven to be a valuable methodological approach in both basic research and clinical practice. However, significant hardware advances are still needed in order to further improve and extend the applications of the technique. The present dissertation predominantly addresses gradient and shim coil design (sub-systems of the MR system). A design study to investigate gradient performance over a set of surface geometries ranging in curvature from planar to a full cylinder using the boundary element (BE) method is presented. The results of this study serve as a guide for future planar and pseudo-planar gradient systems for a range of applications. Additions to the BE method of coil design are developed, including the direct control of the magnetic field uniformity produced by the final electromagnet and the minimum separation between adjacent wires in the final design. A method to simulate induced eddy currents on thin conducting surfaces is presented. The method is used to predict the time-dependent decay of eddy currents induced on a cylindrical copper bore within a 7 T MR system and the induced heating on small conducting structures; both predictions are compared against experiment. Next, the method is extended to predict localized power deposition and the spatial distribution of force due to the Lorentz interaction of the eddy current distribution with the main magnetic field. New methods for the design of actively shielded electromagnets are presented and compared with existing techniques for the case of a whole-body transverse gradient coil. The methods are judged using a variety of shielding performance parameters. A novel approach to eliminate the interactions between the MR gradient system and external, non-MR specific, active devices is presented and its feasibility is discussed. A completely new approach to shimming is presented utilizing a network of current pathways that can be adaptively changed on a subject-by-subject basis and dynamically controlled. The potential benefits of the approach are demonstrated using computer simulations and a prototype coil is constructed and tested as a proof-of-principle

Centroid Localization of Uncooperative Nodes in Wireless Networks Using a Relative Span Weighting Method

Increasingly ubiquitous wireless technologies require novel localization techniques to pinpoint the position of an uncooperative node, whether the target is a malicious device engaging in a security exploit or a low-battery handset in the middle of a critical emergency. Such scenarios necessitate that a radio signal source be localized by other network nodes efficiently, using minimal information. We propose two new algorithms for estimating the position of an uncooperative transmitter, based on the received signal strength (RSS) of a single target message at a set of receivers whose coordinates are known. As an extension to the concept of centroid localization, our mechanisms weigh each receiver's coordinates based on the message's relative RSS at that receiver, with respect to the span of RSS values over all receivers. The weights may decrease from the highest RSS receiver either linearly or exponentially. Our simulation results demonstrate that for all but the most sparsely populated wireless networks, our exponentially weighted mechanism localizes a target node within the regulations stipulated for emergency services location accuracy