A SURVEY OF THE EFFECT OF NETWORK PARAMETERS ON COMMUNICATION LINKS IN WIRELESS SENSOR NETWORKS

In the wireless sensor networks, the communication links between sensor nodes is important. This paper presents the analysis on the effect of parameters of network size, number of nodes and communication ranges on the number of communication links in the sensor network systems. The MATLAB tool is used for deployment of sensor nodes in various area fields

Real-time localization using received signal strength

Locating and tracking assets in an indoor environment is a fundamental requirement for several applications which include for instance network enabled manufacturing. However, translating time of flight-based GPS technique for indoor solutions has proven very costly and inaccurate primarily due to the need for high resolution clocks and the non-availability of reliable line of sight condition between the transmitter and receiver. In this dissertation, localization and tracking of wireless devices using radio signal strength (RSS) measurements in an indoor environment is undertaken. This dissertation is presented in the form of five papers. The first two papers deal with localization and placement of receivers using a range-based method where the Friis transmission equation is used to relate the variation of the power with radial distance separation between the transmitter and receiver. The third paper introduces the cross correlation based localization methodology. Additionally, this paper also presents localization of passive RFID tags operating at 13.56MHz frequency or less by measuring the cross-correlation in multipath noise from the backscattered signals. The fourth paper extends the cross-correlation based localization algorithm to wireless devices operating at 2.4GHz by exploiting shadow fading cross-correlation. The final paper explores the placement of receivers in the target environment to ensure certain level of localization accuracy under cross-correlation based method. The effectiveness of our localization methodology is demonstrated experimentally by using IEEE 802.15.4 radios operating in fading noise rich environment such as an indoor mall and in a laboratory facility of Missouri University of Science and Technology. Analytical performance guarantees are also included for these methods in the dissertation --Abstract, page iv

Received Signal Strength Quantization for Secure Indoor Positioning via Fingerprinting

Peer reviewe

Distributed Location Estimation of a Moving Target Characterized by a Spatial Poisson Field

Wireless Sensor Networks (WSNs) are traditionally employed to collect spatial and temporal data characterizing various events. These data are then used to solve inference problems such as object detection, counting, classification, estimation and tracking. Distributed solutions provided by WSNs are often cost effective and characterized by high performance indices.;In this work, we model and simulate a distributed sensor network composed of radiation detectors and analyze its ability to make inferences. Radiation detectors are deployed over a known area. A radiological point source is positioned in the interior of the area. Detectors take measurements of the field generated by the point source and transmit them (without any interaction with one another) to a remotely installed super computer (called here Fusion Center) for a joint processing. To minimize consumption of resources such as power in the network and transmission bandwidth, the measurements are locally preprocessed prior to transmission. Our model assumes two Gaussian channels, observation and transmission. The first channel distorts data at the receiver end of each sensor during data acquisition. The second channel distorts data during transmission. Sensor measurements are modeled as an inhomogeneous spatial counting random process (Poisson process). The location of the radiological point source in the area and the strength of the field generated by the substance are unknown parameters. The goal of the FC is to estimate these parameters from the distributed measurements provided by the WSN. To find the distributed estimates, we adopt the Maximum Likelihood approach. This approach requires knowledge of the joint probability density function of the distributed measurements observed by the FC. Since the joint probability density of the data observed at the FC is nonlinear in unknown parameters, we propose an iterative approach to solve for the maximum likelihood estimates of these parameters. The solution is a combination of the Bisection and Secant approaches adjusted to seek solution in a multidimensional parameter space. The performance of the distributed estimator is measured in terms of the mean square error. It is analyzed with respect to various parameters of the WSN. We vary the following parameters of the network: (1) the number of sensors in the WSN, (2) signal to noise ratio in observation and transmission channels, (3) the strength of the original field, and (4) the number of quantization levels used by a sensor to convert an analog measurement into a digital signal. We also propose a distributed tracking algorithm for monitoring position of the object in real time

Co-operative sensor localization using maximum likelihood estimation algorithm

In wireless sensor networks, self-localizing sensors are required in a wide variety of applications, from environmental monitoring and manufacturing logistics to geographic routing. In sensor networks which measure high-dimensional data, data localization is also a means to visualize the relationships between sensors’ high dimensional data in a low-dimensional display.This thesis considers both to be part of the general problem of estimating the coordinates of networked sensors. Sensor network localization is ‘cooperative’ in the sense that sensors work locally, with neighboring sensors in the network, to measure relative location, and then estimate a global map of the network.The choice of sensor measurement technology plays a major role in the network’s localization accuracy, energy and bandwidth efficiency, and device cost. This thesis considers measurements of time-of-arrival(TOA), received signal strength (RSS), quantized received signal strength (QRSS), and connectivity. I have taken the simulated data taking varity position of the sensor. From these different position the Cram´er-Rao lower bounds on the variance possible from unbiased location estimators are derived and studied. In this CRB calculation I have taken the RSS case only. Maximum Likelihood estimation algorithm is studied and applied for a particular node position