Viability of wall-embedded tag antenna for ultra-wideband real-time suitcase localisation

WOS:000335152600007 (Nº de Acesso Web of Science)Viability of a conformal single-layer monopole antenna is studied for a wall-embedded tag in an ultra-wideband (UWB) suitcase localisation application based on impulse radio UWB. The performance of the embedded antenna is simulated and confirmed experimentally in real-time localisation (RTL) experiments carried out in a cluttered laboratory environment. Evaluation in the main planes shows average suitcase positioning error around 8 cm for worst-case conditions. RTL tests are made when the suitcase is empty, when it is filled with common travelling items and also when it is shadowed by a second suitcase. A vector network analyser-based measurement set-up is used for target localisation error evaluation. Additionally, the same tests are repeated using portable commercial time-domain transceivers with similar results

Pushing the Limits of Indoor Localization in Today’s Wi-Fi Networks

Wireless networks are ubiquitous nowadays and play an increasingly important role in our everyday lives. Many emerging applications including augmented reality, indoor navigation and human tracking, rely heavily on Wi-Fi, thus requiring an even more sophisticated network. One key component for the success of these applications is accurate localization. While we have GPS in the outdoor environment, indoor localization at a sub-meter granularity remains challenging due to a number of factors, including the presence of strong wireless multipath reflections indoors and the burden of deploying and maintaining any additional location service infrastructure. On the other hand, Wi-Fi technology has developed significantly in the last 15 years evolving from 802.11b/a/g to the latest 802.11n and 802.11ac standards. Single user multiple-input, multiple-output (SU-MIMO) technology has been adopted in 802.11n while multi-user MIMO is introduced in 802.11ac to increase throughput. In Wi-Fi’s development, one interesting trend is the increasing number of antennas attached to a single access point (AP). Another trend is the presence of frequency-agile radios and larger bandwidths in the latest 802.11n/ac standards. These opportunities can be leveraged to increase the accuracy of indoor wireless localization significantly in the two systems proposed in this thesis: ArrayTrack employs multi-antenna APs for angle-of-arrival (AoA) information to localize clients accurately indoors. It is the first indoor Wi-Fi localization system able to achieve below half meter median accuracy. Innovative multipath identification scheme is proposed to handle the challenging multipath issue in indoor environment. ArrayTrack is robust in term of signal to noise ratio, collision and device orientation. ArrayTrack does not require any offline training and the computational load is small, making it a great candidate for real-time location services. With six 8-antenna APs, ArrayTrack is able to achieve a median error of 23 cm indoors in the presence of strong multipath reflections in a typical office environment. ToneTrack is a fine-grained indoor localization system employing time difference of arrival scheme (TDoA). ToneTrack uses a novel channel combination algorithm to increase effective bandwidth without increasing the radio’s sampling rate, for higher resolution time of arrival (ToA) information. A new spectrum identification scheme is proposed to retrieve useful information from a ToA profile even when the overall profile is mostly inaccurate. The triangle inequality property is then applied to detect and discard the APs whose direct path is 100% blocked. With a combination of only three 20 MHz channels in the 2.4 GHz band, ToneTrack is able to achieve below one meter median error, outperforming the traditional super-resolution ToA schemes significantly

EdgeRIC: Empowering Realtime Intelligent Optimization and Control in NextG Networks

Radio Access Networks (RAN) are increasingly softwarized and accessible via data-collection and control interfaces. RAN intelligent control (RIC) is an approach to manage these interfaces at different timescales. In this paper, we develop a RIC platform called RICworld, consisting of (i) EdgeRIC, which is colocated, but decoupled from the RAN stack, and can access RAN and application-level information to execute AI-optimized and other policies in realtime (sub-millisecond) and (ii) DigitalTwin, a full-stack, trace-driven emulator for training AI-based policies offline. We demonstrate that realtime EdgeRIC operates as if embedded within the RAN stack and significantly outperforms a cloud-based near-realtime RIC (> 15 ms latency) in terms of attained throughput. We train AI-based polices on DigitalTwin, execute them on EdgeRIC, and show that these policies are robust to channel dynamics, and outperform queueing-model based policies by 5% to 25% on throughput and application-level benchmarks in a variety of mobile environments.Comment: 16 pages, 15 figure

LIS: Localization based on an intelligent distributed fuzzy system applied to a WSN

The localization of the sensor nodes is a fundamental problem in wireless sensor networks. There are a lot of different kinds of solutions in the literature. Some of them use external devices like GPS, while others use special hardware or implicit parameters in wireless communications. In applications like wildlife localization in a natural environment, where the power available and the weight are big restrictions, the use of hungry energy devices like GPS or hardware that add extra weight like mobile directional antenna is not a good solution. Due to these reasons it would be better to use the localization’s implicit characteristics in communications, such as connectivity, number of hops or RSSI. The measurement related to these parameters are currently integrated in most radio devices. These measurement techniques are based on the beacons’ transmissions between the devices. In the current study, a novel tracking distributed method, called LIS, for localization of the sensor nodes using moving devices in a network of static nodes, which have no additional hardware requirements is proposed. The position is obtained with the combination of two algorithms; one based on a local node using a fuzzy system to obtain a partial solution and the other based on a centralized method which merges all the partial solutions. The centralized algorithm is based on the calculation of the centroid of the partial solutions. Advantages of using fuzzy system versus the classical Centroid Localization (CL) algorithm without fuzzy preprocessing are compared with an ad hoc simulator made for testing localization algorithms. With this simulator, it is demonstrated that the proposed method obtains less localization errors and better accuracy than the centroid algorithm.Junta de Andalucía P07-TIC-0247

Algorithms and performance analysis for indoor location tracking systems

Ph.DDOCTOR OF PHILOSOPH

Coordinated Resource Management in Networked Embedded Systems

This dissertation shows that with simple programming abstractions, network-wide resource coordination is efficient and useful for programming embedded sensor networks. Existing systems have focused primarily on managing resources for individual nodes, but a sensor network is not merely a collection of nodes operating independently: it must coordinate behavior across multiple nodes to achieve high efficiency. We need tools that can enable system-wide coordination at a higher level of abstraction than what exists today. We present three core contributions. The first is a service called IDEA that enables networkwide energy management for sensor networks. It unites energy monitoring, load modeling, and distributed state sharing into a single service that facilitates distributed decision making. Using simulation and testbed results, we show that IDEA enables improvements in network lifetime of up to 35% over approaches that do not consider energy distribution. Our second contribution is Karma, a system for coordinating insect-sized robotic microaerial vehicle (MAV) swarms, an emerging class of mobile sensor networks. Karmas system architecture simplifies the functionality of an individual MAV to a sequence of sensing and actuation commands called behaviors. Each behavior has an associated progress function, a measure of how much of that behavior has been completed. Programming is done by composing behaviors which are coordinated using input from the progress functions. Through simulation and testbed experiments, we demonstrate Karma applications can run on limited resources, are robust to individual MAV failure, and adapt to changes in the environment. Our final contribution is Simbeeotic, a testbed for MAV coordination algorithms. MAV sensors must be codesigned with the software and coordination algorithms that depend on them. This requires a testbed capable of simulating sensors to evaluate them before actual hardware is available and the ability to test with real flight dynamics for accurate control evaluation. In addition, simulation should be able to scale to hundreds or thousands of MAVs at a reduced level of fidelity in order to test at scale. We demonstrate that Simbeeotic provides the appropriate level of fidelity to evaluate prototype systems while maintaining the ability to test at scale.Engineering and Applied Science

Interference Management in Dense 802.11 Networks

Wireless networks are growing at a phenomenal rate. This growth is causing an overcrowding of the unlicensed RF spectrum, leading to increased interference between co-located devices. Existing decentralized medium access control (MAC) protocols (e.g. IEEE 802.11a/b/g standards) are poorly designed to handle interference in such dense wireless environments. This is resulting in networks with poor and unpredictable performance, especially for delay-sensitive applications such as voice and video. This dissertation presents a practical conflict-graph (CG) based approach to designing self-organizing enterprise wireless networks (or WLANs) where interference is centrally managed by the network infrastructure. The key idea is to use potential interference information (available in the CG) as an input to algorithms that optimize the parameters of the WLAN.We demonstrate this idea in three ways. First, we design a self-organizing enterprise WLAN and show how the system enhances performance over non-CG based schemes, in a high fidelity network simulator. Second, we build a practical system for conflict graph measurement that can precisely measure interference (for a given network configuration) in dense wireless environments. Finally, we demonstrate the practical benefits of the conflict graph system by using it in an optimization framework that manages associations and traffic for mobile VoIP clients in the enterprise. There are a number of contributions of this dissertation. First, we show the practical application of conflict graphs for infrastructure-based interference management in dense wireless networks. A prototype design exhibits throughput gains of up to 50% over traditional approaches. Second, we develop novel schemes for designing a conflict graph measurement system for enterprise WLANs that can detect interference at microsecond-level timescales and with little network overhead. This allows us to compute the conflict graph up to 400 times faster as compared to the current best practice proposed in the literature. The system does not require any modifications to clients or any specialized hardware for its operation. Although the system is designed for enterprise WLANs, the proposed techniques and corresponding results are applicable to other wireless systems as well (e.g. wireless mesh networks). Third, our work opens up the space for designing novel fine-grained interference-aware protocols/algorithms that exploit the ability to compute the conflict graph at small timescales. We demonstrate an instance of such a system with the design and implementation of an architecture that dynamically manages client associations and traffic in an enterprise WLAN. We show how mobile clients sustain uninterrupted and consistent VoIP call quality in the presence of background interference for the duration of their VoIP sessions

Software-Defined Lighting.

For much of the past century, indoor lighting has been based on incandescent or gas-discharge technology. But, with LED lighting experiencing a 20x/decade increase in flux density, 10x/decade decrease in cost, and linear improvements in luminous efficiency, solid-state lighting is finally cost-competitive with the status quo. As a result, LED lighting is projected to reach over 70% market penetration by 2030. This dissertation claims that solid-state lighting’s real potential has been barely explored, that now is the time to explore it, and that new lighting platforms and applications can drive lighting far beyond its roots as an illumination technology. Scaling laws make solid-state lighting competitive with conventional lighting, but two key features make solid-state lighting an enabler for many new applications: the high switching speeds possible using LEDs and the color palettes realizable with Red-Green-Blue-White (RGBW) multi-chip assemblies. For this dissertation, we have explored the post-illumination potential of LED lighting in applications as diverse as visible light communications, indoor positioning, smart dust time synchronization, and embedded device configuration, with an eventual eye toward supporting all of them using a shared lighting infrastructure under a unified system architecture that provides software-control over lighting. To explore the space of software-defined lighting (SDL), we design a compact, flexible, and networked SDL platform to allow researchers to rapidly test new ideas. Using this platform, we demonstrate the viability of several applications, including multi-luminaire synchronized communication to a photodiode receiver, communication to mobile phone cameras, and indoor positioning using unmodified mobile phones. We show that all these applications and many other potential applications can be simultaneously supported by a single lighting infrastructure under software control.PhDElectrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/111482/1/samkuo_1.pd

HORUS: A WLAN-BASED INDOOR LOCATION DETERMINATION SYSTEM

As ubiquitous computing becomes more popular, the need for context-aware applications increases. The context of an application refers to the information that is part of its operating environment. Typically this includes information such as location, activity of people, and the state of other devices. Algorithms and techniques that allow an application to be aware of the location of a device on a map of the environment are a prerequisite for many of these applications. Many systems over the years have tackled the problem of determining and tracking user position. Examples include GPS, wide-area cellular-based systems, infraredbased systems, magnetic tracking systems, various computer vision systems, physical contact systems, and radio frequency (RF) based systems. Of these, the class of RF-based systems that use an underlying wireless data network, such as the IEEE 802.11 wireless network, to estimate user location has gained attention recently, especially for indoor applications. RF-based techniques provide more ubiquitous coverage than other indoor location determination systems and do not require additional hardware for user location determination, thereby enhancing the value of the wireless data network. However, using a wireless network for location determination has the challenge of dealing with the noisy characteristics of the wireless channel. Current location determination techniques for the 802.11 wireless networks suffer from these noisy characteristics, leading to coarse grained accuracy. A key feature of current techniques is the dependence on building a radio map for the area of interest and using this radio map to infer the user location. Using the radio map to infer the user location is a computationally intensive process and may consume the scarce energy resource of the mobile units. The Horus system is concerned with developing accurate methods for determining the user location with low computation requirements. Our goal is to build a location determination system that is capable of determining the user position with high accuracy, is light enough to be implemented on energy-constrained devices such as handheld computers, and is scalable to track a large number of users and to be used with large areas. We identify different causes of the wireless channel variations and we develop techniques to handle these variations. The results show that the Horus system is able to achieve accuracy significantly better than the current WLAN location determination systems. Moreover, the number of operations required to run the algorithm is better than the current systems with more than an order of magnitude