Indoor radio location algorithm using empirical propagation models and probability distribution heuristics

Research is conducted at the Budapest University of Technology in the field of indoor positioning using radio waves, with practical application issues in focus. Our goal is to enhance and combine existing algorithms and create an implementation that is efficient enough to enable real-time operation in 3D space in multi-level office environments while retaining the accuracy of more complex systems. The proposed solution is based on proven empirical propagation models (the Motley-Keenan Model and the New Empirical Model of Cheung, Sau and Murch), with the ability to augment and refine with surveyed radio fingerprint data. The propagation model described in this paper can be used to generate estimated signal strength patterns for locations that were left out of the survey; and the values coming from the two different sources can be further handled in a common way. An algorithm is proposed to calculate a probability distribution over the floor plan using these expected values and the positioning-time measurements. The results from this location algorithm are combined with other probability distributions, generated by heuristics such as the distribution of walls, previous walking directions and typical indoor movement patterns, as well as data from G-sensors and digital compasses built into modern handheld devices. Other real-world issues are investigated like reaction to changes in the placement of radio beacons, and the comparability of various devices with different signal characteristics. The proposed algorithm can achieve an average positioning error of 3 metres in a common office environment using fingerprinting data, and errors are only about 50%greater when relying solely on simulated signal strength values

UWB localization with battery-powered wireless backbone for drone-based inventory management

Current inventory-taking methods (counting stocks and checking correct placements) in large vertical warehouses are mostly manual, resulting in (i) large personnel costs, (ii) human errors and (iii) incidents due to working at large heights. To remedy this, the use of autonomous indoor drones has been proposed. However, these drones require accurate localization solutions that are easy to (temporarily) install at low costs in large warehouses. To this end, we designed a Ultra-Wideband (UWB) solution that uses infrastructure anchor nodes that do not require any wired backbone and can be battery powered. The resulting system has a theoretical update rate of up to 2892 Hz (assuming no hardware dependent delays). Moreover, the anchor nodes have an average current consumption of only 27 mA (compared to 130 mA of traditional UWB infrastructure nodes). Finally, the system has been experimentally validated and is available as open-source software

Human exposure to electromagnetic fields from WLANs and WBANs in the 2.4 GHz band

226 p.En los últimos años, el masivo crecimiento de las comunicaciones inalámbricas ha incrementado la preocupación acerca de la exposición humana a los campos electromagnéticos debido a los posibles efectos sobre la salud. Esta tesis surge de la necesidad de proporcionar información acerca de este tipo de exposición desde un punto de vista técnico. Por una parte, se han estudiado los niveles de exposición causados por señales WiFi, para lo cual ha sido necesario establecer un procedimiento de medida adecuado para tomar muestras de estas emisiones. Además, se han llevado a cabo campañas de medida para evaluar la exposición a señales WiFi y su variabilidad en el interior de un entorno público. Por otra parte, se ha analizado la potencia absorbida por el cuerpo humano a causa de los novedosos dispositivos wearables. Se han implementado dos antenas de este tipo, apropiadas para dispositivos wearables, se ha analizado detalladamente la exposición debida a estos aparatos y finalmente se han comparado los niveles de exposición producidos por estas antenas y por las señales WiFi

A Comprehensive Survey on Networking over TV White Spaces

The 2008 Federal Communication Commission (FCC) ruling in the United States opened up new opportunities for unlicensed operation in the TV white space spectrum. Networking protocols over the TV white spaces promise to subdue the shortcomings of existing short-range multi-hop wireless architectures and protocols by offering more availability, wider bandwidth, and longer-range communication. The TV white space protocols are the enabling technologies for sensing and monitoring, Internet-of-Things (IoT), wireless broadband access, real-time, smart and connected community, and smart utility applications. In this paper, we perform a retrospective review of the protocols that have been built over the last decade and also the new challenges and the directions for future work. To the best of our knowledge, this is the first comprehensive survey to present and compare existing networking protocols over the TV white spaces.Comment: 19 page

The characterisation and modelling of the wireless propagation channel in small cells scenarios

“A thesis submitted to the University of Bedfordshire, in partial fulfilment of the requirements for the degree of Doctor of Philosophy”.The rapid growth in wireless data traffic in recent years has placed a great strain on the wireless spectrum and the capacity of current wireless networks. In addition, the makeup of the typical wireless propagation environment is rapidly changing as a greater percentage of data traffic moves indoors, where the coverage of radio signals is poor. This dual fronted assault on coverage and capacity has meant that the tradition cellular model is no longer sustainable, as the gains from constructing new macrocells falls short of the increasing cost. The key emerging concept that can solve the aforementioned challenges is smaller base stations such as micro-, pico- and femto-cells collectively known as small cells. However with this solution come new challenges: while small cells are efficient at improving the indoor coverage and capacity; they compound the lack of spectrum even more and cause high levels of interference. Current channel models are not suited to characterise this interference as the small cells propagation environment is vast different. The result is that overall efficiency of the networks suffers. This thesis presents an investigation into the characteristics of the wireless propagation channel in small cell environments, including measurement, analysis, modelling, validation and extraction of channel data. Two comprehensive data collection campaigns were carried out, one of them employed a RUSK channel sounder and featured dual-polarised MIMO antennas. From the first dataset an empirical path loss model, adapted to typical indoor and outdoor scenarios found in small cell environments, was constructed using regression analysis and was validated using the second dataset. The model shows good accuracy for small cell environments and can be implemented in system level simulations quickly without much requirements