Design and implementation of a positioning service in the context of smart cities

In recent decades, cities have become the global hubs of commerce, culture, science and society, being also the largest consumers of energy and the largest carbon emitters. With the objective of solving this problem, sustainable cities or "Smart Cities" are one of the objectives to be fulfilled in the 2030 Agenda. With this objective in mind and in the context of the project "Navigation and GNSS in Smart Cities -Testbed Concept Definition" (HANSEL), the student intends to design and develop a service in charge of sensor positioning based on GNSS and Cellular technologies for the subsequent treatment of the information generated for various purposes, such as the detection and location of sources of interference or GNSS and Cellular hybridization, obtaining hybrid positions, more precise than those of each system separately. This system or service is intended to be accessible to the general public via Internet (as a Software as a Service orSaaS), and takes advantage of the all the features cloud computing has to offer, both at performance and energy consumption level.En les últimes dècades, les ciutats s'han convertit en els nuclis mundials de comerç, cultura, ciència i societat, sent també les majors consumidores d'energia i les més grans emissores de carboni. Amb l'objectiu de solucionar aquesta problemàtica, les ciutats sostenibles o "SmartCities" són un dels objectius a complir en l'Agenda 2030. Amb aquest objectiu en ment i en el context del projecte "Navigation and GNSS in Smart Cities - Testbed Concept Definition"(HANSEL), l'estudiant pretén dissenyar i desenvolupar un servei a càrrec del posicionament de sensors basats en tecnologies GNSS i cel·lular per al posterior tractament de la informació generada per a diverses finalitats, com la detecció i localització de fonts d'interferència o la hibridació GNSS i cel·lular, donant lloc a posicions híbrides, més precises que les de cada sistema per separat. Aquest servei pretén ser accessible mitjançant Internet al públic general (com un Software com a servei o SaaS), i aprofita els avantatges que la computació en el núvol és capaç d'oferir tant a nivell de prestacions com a nivell d'estalvi d'energia respecte als dispositius de navegació actuals.En las últimas décadas, las ciudades se han convertido en los núcleos mundiales de comercio, cultura, ciencia y sociedad, siendo también las mayores consumidoras de energía y las más grandes emisoras de carbono. Con el objetivo de solucionar esta problemática, las ciudades sostenibles o "Smart Cities" son uno de los objetivos a cumplir en la Agenda 2030. Con este objetivo en mente y en el contexto del proyecto "Navigation and GNSS in Smart Cities - Testbed Concept Definition" (HANSEL), el estudiante pretende diseñar y desarrollar un servicio a cargo del posicionamiento de sensores basados en tecnologías GNSS y celular para el posterior tratamiento de la información generada para diversos fines, como la detección y localización de fuentes de interferencia o la hibridación GNSS y celular, dando lugar a posiciones híbridas, más precisas que las de cada sistema por separado. Dicho servicio pretende ser accesible mediante Internet al público general (como un Software como servicio o SaaS), y aprovecha las ventajas que la computación en la nube es capaz de ofrecer tanto a nivel de prestaciones como a nivel de ahorro de energía con respecto a los dispositivos de navegación actuales

3GPP LTE Release 9 and 10 requirement analysis to physical layer UE testing

The purpose of this thesis was to analyze the testing requirements to physical layer features which are used in LTE Release 9 and 10 timeframe. The aim of the analysis was to define test case requirements for new features from the physical layer point of view. This analysis can then be utilized to implement and design test cases using commercial eNB simulators. The analysis was carried out by studying the 3GPP specifications and by investigating the integration and system level testing requirements. Different feature specific parameters were evaluated and different testing aspects were studied in order to verify the functionalities and performance of the UE. Also, different conformance test case scenarios and field testing aspects were investigated in order to improve the test case planning in the integration and system testing phase. The analysis showed that in Rel-9 there are two main features which have a great impact on the Rel-9 physical layer testing. These two features are the dual-layer beamforming and UE positioning which is done with OTDOA and E-CID methods. It was analyzed that the requirements for the downlink dual-layer beamforming focus on TDD side and the test plan must contain especially throughput performance testing in integration and system phase testing. OTDOA and E-CID methods, on the other hand, need test plans which are concentrating on the positioning accuracy. In Rel-10, the analysis showed that there are plenty of new features on physical layer to ensure the transition from LTE to LTE-Advanced. The main requirements were assigned for the CA feature which has testing activities especially on the UE feedback operations. Also, different kinds of CA deployment scenarios were analyzed to evaluate more closely the initial CA testing scenarios in integration and system testing. Analysis continued with downlink multi-layer beamforming where the requirements were seen to concentrate on new CSI-RS aspects and to throughput performance testing. Uplink MIMO aspects were analyzed at the end and the studies showed that this feature may have a minor role in Rel-10 timeframe and therefore it does not have any important testing requirements which should be taken into account in test plans

Time of Arrival and Angle of Arrival Estimation of LTE Signals for Positioning Applications

With the increase of services that need accurate location of the user, new techniques that cooperate with the Global Navigation Satellite System (GNSS) are necessary. Toward this objective, this thesis presents our research work about the estimation of the time of arrival (TOA) and of the angle of arrival (AOA) exploiting modern cellular signals. In particular, we focus on the Third Generation Partnership Project (3GPP) Long Term Evolution (LTE) standard, and in particular uplink and downlink reference signals are exploited to this purposes. The current release of the 3GPP LTE specification supports a UTDOA localization technique based on the Sounding Reference Signal (SRS). In real environments, however, user equipments (UE) are rarely set up to transmit this particular signal. The main original contribution of this thesis consists in a new TOA estimation method based on uplink transmission. In particular, we explore the possibility of performing radio localization exploiting the uplink Demodulation Reference Signal (DM-RS), which is always sent by UEs during data transmission. Real uplink transmissions are modeled in simulations and the performance of known algorithms like SAGE and IAA-APES are evaluated for TOA estimation. A new method to estimate the initial conditions of the SAGE algorithm is proposed and the estimation performance in uplink scenarios is evaluated. The analysis revealed that the proposed method outperforms the non-coherent initial conditions estimation proposed in the literature, when uplink transmission are used. Then, the benefits of our proposal are evaluated and the feasibility of TOA estimation exploiting the DM-RS is demonstrated by means of experiments using real DM-RS signals generated by an LTE module. A second original contribution is given by AOA estimation. In particular, the independence of AOA estimation with respect to uplink and downlink transmission is verified. According to this result, the performance of IAA-APES and SAGE in real-world AOA experiments is evaluated in the downlink scenarios. Based on the overall results, we conclude that the proposed radio localization method, exploiting the uplink Demodulation Reference Signal (DM-RS), can be extended also to joint TOA, AOA using SAGE, for hybrid localization techniques. We can also conclude that the proposed method can be easily extended to downlink transmission exploiting the cell specific reference signal (CRS)

Enabling self organisation for future cellular networks.

The rapid growth in mobile communications due to the exponential demand for wireless access is causing the distribution and maintenance of cellular networks to become more complex, expensive and time consuming. Lately, extensive research and standardisation work has been focused on the novel paradigm of self-organising network (SON). SON is an automated technology that allows the planning, deployment, operation, optimisation and healing of the network to become faster and easier by reducing the human involvement in network operational tasks, while optimising the network coverage, capacity and quality of service. However, these SON autonomous features cannot be achieved with the current drive test coverage assessment approach due to its lack of automaticity which results in huge delays and cost. Minimization of drive test (MDT) has recently been standardized by 3GPP as a key self- organising network (SON) feature. MDT allows coverage to be estimated at the base station using user equipment (UE) measurement reports with the objective to eliminate the need for drive tests. However, most MDT based coverage estimation methods recently proposed in literature assume that UE position is known at the base station with 100% accuracy, an assumption that does not hold in reality. In this work, we develop a novel and accurate analytical model that allows the quantification of error in MDT based autonomous coverage estimation (ACE) as a function of error in UE as well as base station (user deployed cell) positioning. We first consider a circular cell with an omnidirectional antenna and then we use a three-sectored cell and see how the system is going to be affected by the UE and the base station (user deployed cell) geographical location information errors. Our model also allows characterization of error in ACE as function of standard deviation of shadowing in addition to the path-loss

Practical Experiences of a Smart Livestock Location Monitoring System leveraging GNSS, LoRaWAN and Cloud Services.

Livestock farming is, in most cases in Europe, unsupervised, thus making it difficult to ensure adequate control of the position of the animals for the improvement of animal welfare. In addition, the geographical areas involved in livestock grazing usually have difficult access with harsh orography and lack of communications infrastructure, thus the need to provide a low-power livestock localization and monitoring system is of paramount importance, which is crucial not for a sustainable agriculture, but also for the protection of native breeds and meats thanks to their controlled supervision. In this context, this work presents an Internet of things (IoT)-based system integrating low-power wide area (LPWA) technology, cloud and virtualization services to provide real-time livestock location monitoring. Taking into account the constraints coming from the environment in terms of energy supply and network connectivity, our proposed system is based on a wearable device equipped with inertial sensors, Global Positioning System (GPS) receiver and LoRaWAN transceiver, which can provide a satisfactory compromise between performance, cost and energy consumption. At first, this article provides the state-of-the-art localization techniques and technologies applied to smart livestock. Then, we proceed to provide the hardware and firmware co-design to achieve very low energy consumption, thus providing a significant positive impact to the battery life. The proposed platform has been evaluated in a pilot test in the Northern part of Italy, evaluating different configurations in terms of sampling period, experimental duration and number of devices. The results are analyzed and discussed for packe delivery ratio, energy consumption, localization accuracy, battery discharge measurement and delay

Location-Based Sensor Fusion for UAS Urban Navigation.

For unmanned aircraft systems (UAS) to effectively conduct missions in urban environments, a multi-sensor navigation scheme must be developed that can operate in areas with degraded Global Positioning System (GPS) signals. This thesis proposes a sensor fusion plug and play capability for UAS navigation in urban environments to test combinations of sensors. Measurements are fused using both the Extended Kalman Filter (EKF) and Ensemble Kalman Filter (EnKF), a type of Particle Filter. A Long Term Evolution (LTE) transceiver and computer vision sensor each augment the traditional GPS receiver, inertial sensors, and air data system. Availability and accuracy information for each sensor is extracted from the literature. LTE positioning is motivated by a perpetually expanding network that can provide persistent measurements in the urban environment. A location-based logic model is proposed to predict sensor availability and accuracy for a given type of urban environment based on a map database as well as real-time sensor inputs and filter outputs. The simulation is executed in MATLAB where the vehicle dynamics, environment, sensors, and filters are user-customizable. Results indicate that UAS horizontal position accuracy is most dependent on availability of high sampling rate position measurements along with GPS measurement availability. Since the simulation is able to accept LTE sensor specifications, it will be able to show how the UAS position accuracy can be improved in the future with this persistent measurement, even though the accuracy is not improved using current LTE state-of-the-art. In the unmatched true propagation and filter dynamics model scenario, filter tuning proves to be difficult as GPS availability varies from urban canyon to urban canyon. The main contribution of this thesis is the generation of accuracy data for different sensor suites in both a homogeneous urban environment (solid walls) using matched dynamics models and a heterogeneous urban environment layout using unmatched models that necessitate filter tuning. Future work should explore the use of downward facing VISION sensors and LiDAR, integrate real-time map information into sensor availability and measurement weighting decisions, including the use of LTE for approximate localization, and more finely represent expected measurement accuracies in the GPS and LTE networks.PhDAerospace EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/110361/1/jrufa_1.pd