Signal-Strength Based Localization in Wireless Fading Channels

We develop maximum likelihood (ML) methods for location estimation using spatio-temporal received-signal strength (RSS) measurements in wireless fading channels. Fading and composite fading-shadowing scenarios with completely unknown and partially known source signals are considered. We adopt gamma (Nakagami-m) and lognormal models to describe fading and shadowing effects, respectively. We also derive Cram´er-Rao bounds (CRBs) for the location parameters and discuss initialization of the proposed algorithms. Numerical simulations demonstrate the performance of our estimators

Cellular Underwater Wireless Optical CDMA Network: Potentials and Challenges

Underwater wireless optical communications is an emerging solution to the expanding demand for broadband links in oceans and seas. In this paper, a cellular underwater wireless optical code division multiple-access (UW-OCDMA) network is proposed to provide broadband links for commercial and military applications. The optical orthogonal codes (OOC) are employed as signature codes of underwater mobile users. Fundamental key aspects of the network such as its backhaul architecture, its potential applications and its design challenges are presented. In particular, the proposed network is used as infrastructure of centralized, decentralized and relay-assisted underwater sensor networks for high-speed real-time monitoring. Furthermore, a promising underwater localization and positioning scheme based on this cellular network is presented. Finally, probable design challenges such as cell edge coverage, blockage avoidance, power control and increasing the network capacity are addressed.Comment: 11 pages, 10 figure

Robotic Wireless Sensor Networks

In this chapter, we present a literature survey of an emerging, cutting-edge, and multi-disciplinary field of research at the intersection of Robotics and Wireless Sensor Networks (WSN) which we refer to as Robotic Wireless Sensor Networks (RWSN). We define a RWSN as an autonomous networked multi-robot system that aims to achieve certain sensing goals while meeting and maintaining certain communication performance requirements, through cooperative control, learning and adaptation. While both of the component areas, i.e., Robotics and WSN, are very well-known and well-explored, there exist a whole set of new opportunities and research directions at the intersection of these two fields which are relatively or even completely unexplored. One such example would be the use of a set of robotic routers to set up a temporary communication path between a sender and a receiver that uses the controlled mobility to the advantage of packet routing. We find that there exist only a limited number of articles to be directly categorized as RWSN related works whereas there exist a range of articles in the robotics and the WSN literature that are also relevant to this new field of research. To connect the dots, we first identify the core problems and research trends related to RWSN such as connectivity, localization, routing, and robust flow of information. Next, we classify the existing research on RWSN as well as the relevant state-of-the-arts from robotics and WSN community according to the problems and trends identified in the first step. Lastly, we analyze what is missing in the existing literature, and identify topics that require more research attention in the future

Dial It In: Rotating RF Sensors to Enhance Radio Tomography

A radio tomographic imaging (RTI) system uses the received signal strength (RSS) measured by RF sensors in a static wireless network to localize people in the deployment area, without having them to carry or wear an electronic device. This paper addresses the fact that small-scale changes in the position and orientation of the antenna of each RF sensor can dramatically affect imaging and localization performance of an RTI system. However, the best placement for a sensor is unknown at the time of deployment. Improving performance in a deployed RTI system requires the deployer to iteratively "guess-and-retest", i.e., pick a sensor to move and then re-run a calibration experiment to determine if the localization performance had improved or degraded. We present an RTI system of servo-nodes, RF sensors equipped with servo motors which autonomously "dial it in", i.e., change position and orientation to optimize the RSS on links of the network. By doing so, the localization accuracy of the RTI system is quickly improved, without requiring any calibration experiment from the deployer. Experiments conducted in three indoor environments demonstrate that the servo-nodes system reduces localization error on average by 32% compared to a standard RTI system composed of static RF sensors.Comment: 9 page