Localization in Spatially Correlated Shadow-Fading Environment

Στην διπλωματική αυτή εργασία ενδιαφέρομαστε για Received Signal Strength (RSS) localization λόγω της ενγενης απλοτιτας του οπου ο καθε δεκτης μετρα ισχυ. Η διατριβή παρουσιάζει τόσο θεωρητικα όσο και πειραματικά αποτελέσματα. Στην αρχη κατασκευαζεται και παρουσιάζεται ένα νέο θεωρητικό όριο για το πρόβλημα εντοπισμού μίας πηγής σε χωρικα συσχέτισομενο περιβαλον, με χρησει conditional measurments και στη συνέχεια να χρησιμοποιείτε για την αξιολόγηση των επιδόσεων. Επιπλέον, παρουσιάζονται ορισμένα θεωρητικά αποτελέσματα στο πιο δύσκολο πρόβλημα του εντοπισμού πολλαπλών πηγών και πάλι για την περίπτωση του χωτικα συσχετιζομενου shadow fading περιβαλοντος. Αυτά τα αποτελέσματα δεν χρεισιμοποιουν contitionla measurments, αλλά δείχνουν πώς η απόδοση σχετιζετε με τον αριθμό των δεκτων, των αριθμό των άγνωστων πηγων, και ο συντελεστής συσχέτισης του περιβάλλοντος. Επιπλέον, δύο πειραματικές εκστρατειες εσωτερικου χωρου περιλαμβάνονται στην παρούσα διατριβή, και στις δύο χρησιμοποιηθηκε η OpenAirInterface (OAI) πλατφόρμα. Ο κύριος στόχος των εκστρατειών ήταν 1) να εξακριβώσει η ύπαρξη χωρικης συσχετισεις του shadow fading για εσοτερικο χωρο και 2) να χρησιμοποιούν ad-hoc τεχνικές και αλγόριθμοι, προκειμένου να επιτευχθεί κάποιο όφελος από την χωρική συσχέτιση υποθέτοντας γνώση contitional measurments.In this thesis we are interested on Received Signal Strength (RSS) localization due to its simplicity as every radio measures power. Thesis presents both theoretical as well as experimental results. We derive and present a new theoretical bound for the single-source localization problem that takes spatial- correlation as well as conditional measurements into account and then uses it to assess performance. Furthermore, presents some theoretical results in the more challenging multi-source localization problem again for the case of correlated shadow-fading environments. These results did not assume prior knowledge of conditional measurements, but show how the localization performance scales with respect to the number of sensors, the number of unknown sources, and the correlation coefficient of the environment. Additionally, two indoor experimental campaigns are included in this thesis, both of them used the OpenAirInterface (OAI) platform. The main target of the campaigns was 1) to verify the existence of shadow-fading in the indoor environment and 2) to use ad-hoc techniques in our localization algorithms in order achieve some gain from spatial correlation assuming knowledge of conditional measurements.

Doctor of Philosophy

dissertationIn wireless sensor networks, knowing the location of the wireless sensors is critical in many remote sensing and location-based applications, from asset tracking, and structural monitoring to geographical routing. For a majority of these applications, received signal strength (RSS)-based localization algorithms are a cost effective and viable solution. However, RSS measurements vary unpredictably because of fading, the shadowing caused by presence of walls and obstacles in the path, and non-isotropic antenna gain patterns, which affect the performance of the RSS-based localization algorithms. This dissertation aims to provide efficient models for the measured RSS and use the lessons learned from these models to develop and evaluate efficient localization algorithms. The first contribution of this dissertation is to model the correlation in shadowing across link pairs. We propose a non-site specific statistical joint path loss model between a set of static nodes. Radio links that are geographically proximate often experience similar environmental shadowing effects and thus have correlated shadowing. Using a large number of multi-hop network measurements in an ensemble of indoor and outdoor environments, we show statistically significant correlations among shadowing experienced on different links in the network. Finally, we analyze multihop paths in three and four node networks using both correlated and independent shadowing models and show that independent shadowing models can underestimate the probability of route failure by a factor of two or greater. Second, we study a special class of algorithms, called kernel-based localization algorithms, that use kernel methods as a tool for learning correlation between the RSS measurements. Kernel methods simplify RSS-based localization algorithms by providing a means to learn the complicated relationship between RSS measurements and position. We present a common mathematical framework for kernel-based localization algorithms to study and compare the performance of four different kernel-based localization algorithms from the literature. We show via simulations and an extensive measurement data set that kernel-based localization algorithms can perform better than model-based algorithms. Results show that kernel methods can achieve an RMSE up to 55% lower than a model-based algorithm. Finally, we propose a novel distance estimator for estimating the distance between two nodes a and b using indirect link measurements, which are the measurements made between a and k, for k ? b and b and k, for k ? a. Traditionally, distance estimators use only direct link measurement, which is the pairwise measurement between the nodes a and b. The results show that the estimator that uses indirect link measurements enables better distance estimation than the estimator that uses direct link measurements

Localization Of Sensors In Presence Of Fading And Mobility

The objective of this dissertation is to estimate the location of a sensor through analysis of signal strengths of messages received from a collection of mobile anchors. In particular, a sensor node determines its location from distance measurements to mobile anchors of known locations. We take into account the uncertainty and fluctuation of the RSS as a result of fading and take into account the decay of the RSS which is proportional to the transmitter-receiver distance power raised to the PLE. The objective is to characterize the channel in order to derive accurate distance estimates from RSS measurements and then utilize the distance estimates in locating the sensors. To characterize the channel, two techniques are presented for the mobile anchors to periodically estimate the channel\u27s PLE and fading parameter. Both techniques estimate the PLE by solving an equation via successive approximations. The formula in the first is stated directly from MLE analysis whereas in the second is derived from a simple probability analysis. Then two distance estimates are proposed, one based on a derived formula and the other based on the MLE analysis. Then a location technique is proposed where two anchors are sufficient to uniquely locate a sensor. That is, the sensor narrows down its possible locations to two when collects RSS measurements transmitted by a mobile anchor, then uniquely determines its location when given a distance to the second anchor. Analysis shows the PLE has no effect on the accuracy of the channel characterization, the normalized error in the distance estimation is invariant to the estimated distance, and accurate location estimates can be achieved from a moderate sample of RSS measurements

Geometric Interpretation of Theoretical Bounds for RSS-based Source Localization with Uncertain Anchor Positions

The Received Signal Strength based source localization can encounter severe problems originating from uncertain information about the anchor positions in practice. The anchor positions, although commonly assumed to be precisely known prior to the source localization, are usually obtained using previous estimation algorithm such as GPS. This previous estimation procedure produces anchor positions with limited accuracy that result in degradations of the source localization algorithm and topology uncertainty. We have recently addressed the problem with a joint estimation framework that jointly estimates the unknown source and uncertain anchors positions and derived the theoretical limits of the framework. This paper extends the authors previous work on the theoretical performance bounds of the joint localization framework with appropriate geometric interpretation of the overall problem exploiting the properties of semi-definiteness and symmetry of the Fisher Information Matrix and the Cram{\`e}r-Rao Lower Bound and using Information and Error Ellipses, respectively. The numerical results aim to illustrate and discuss the usefulness of the geometric interpretation. They provide in-depth insight into the geometrical properties of the joint localization problem underlining the various possibilities for practical design of efficient localization algorithms.Comment: 30 pages, 15 figure

Research on Wireless Multi-hop Networks: Current State and Challenges

Wireless multi-hop networks, in various forms and under various names, are being increasingly used in military and civilian applications. Studying connectivity and capacity of these networks is an important problem. The scaling behavior of connectivity and capacity when the network becomes sufficiently large is of particular interest. In this position paper, we briefly overview recent development and discuss research challenges and opportunities in the area, with a focus on the network connectivity.Comment: invited position paper to International Conference on Computing, Networking and Communications, Hawaii, USA, 201

Efficient Wireless Security Through Jamming, Coding and Routing

There is a rich recent literature on how to assist secure communication between a single transmitter and receiver at the physical layer of wireless networks through techniques such as cooperative jamming. In this paper, we consider how these single-hop physical layer security techniques can be extended to multi-hop wireless networks and show how to augment physical layer security techniques with higher layer network mechanisms such as coding and routing. Specifically, we consider the secure minimum energy routing problem, in which the objective is to compute a minimum energy path between two network nodes subject to constraints on the end-to-end communication secrecy and goodput over the path. This problem is formulated as a constrained optimization of transmission power and link selection, which is proved to be NP-hard. Nevertheless, we show that efficient algorithms exist to compute both exact and approximate solutions for the problem. In particular, we develop an exact solution of pseudo-polynomial complexity, as well as an epsilon-optimal approximation of polynomial complexity. Simulation results are also provided to show the utility of our algorithms and quantify their energy savings compared to a combination of (standard) security-agnostic minimum energy routing and physical layer security. In the simulated scenarios, we observe that, by jointly optimizing link selection at the network layer and cooperative jamming at the physical layer, our algorithms reduce the network energy consumption by half

Indoor wireless communications and applications

Chapter 3 addresses challenges in radio link and system design in indoor scenarios. Given the fact that most human activities take place in indoor environments, the need for supporting ubiquitous indoor data connectivity and location/tracking service becomes even more important than in the previous decades. Specific technical challenges addressed in this section are(i), modelling complex indoor radio channels for effective antenna deployment, (ii), potential of millimeter-wave (mm-wave) radios for supporting higher data rates, and (iii), feasible indoor localisation and tracking techniques, which are summarised in three dedicated sections of this chapter