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This works proposes location estimation in 5G systems using Reconfigurable Intelligent Surfaces (RIS) to optimize positioning accuracy where LOS is obstructed. Machine Learning techniques are considered for the optimization of the RIS phases. The primary focus is on developing a RIS-aided localization algorithm to improve the accuracy of user positioning using compressed sensing techniques. The integration of a RIS assists the base station in obtaining more accurate location by mitigating the problems caused by blockages of the LoS. The present study suggests a phase optimization method that minimizes the Cramer- Rao Lower Bound (CRLB) in order to find the optimal RIS phase configuration. However, the computation of the CRLB for different scenarios has a high computational cost. To address this challenge, Machine Learning (ML) techniques have been applied to develop a network that can calculate the phases that minimize the CRLB based solely on the estimated position of the user. Moreover, in order to provide a comprehensive comparison of the results, the optimization of the RIS phases based on SNR criteria has also been considered., Este trabajo propone la estimación de ubicación en sistemas 5G utilizando Superficies Inteligentes Reconfigurables (RIS) para optimizar la precisión de posicionamiento cuando la línea de visión (LOS) está obstruida. Se consideran técnicas de Machine Learning para la optimización de las fases de la RIS. El enfoque principal se centra en desarrollar un algoritmo de localización asistido por RIS para mejorar la precisión del posicionamiento del usuario utilizando técnicas de compresión de señales (CS). La integración de una RIS ayuda a la estación base a obtener una ubicación más precisa al mitigar los problemas causados por los bloqueos de la línea de visión. El presente estudio sugiere un método de optimización de fases que minimiza el Límite Inferior de Cramer-Rao (CRLB) para encontrar la configuración óptima de fases de RIS. Sin embargo, el cálculo del CRLB para diferentes escenarios tiene un alto costo computacional. Para abordar este desafío, se han aplicado técnicas de Aprendizaje Automático para desarrollar una red neuronal que pueda calcular las fases que minimizan el CRLB basándose únicamente en la posición estimada del usuario. Además, con el fin de proporcionar una comparación exhaustiva de los resultados, también se ha considerado la optimización de las fases de RIS basada en criterios de Relación Señal-Ruido (SNR)., Aquest treball proposa l'estimació de la ubicació en sistemes 5G utilitzant Superfícies Intel·ligents Reconfigurables (RIS) per optimitzar la precisió de posicionament quan la línia de visió (LOS) està obstruïda. Es consideren tècniques de Machine Learning per a l'optimització de les fases de la RIS. L'enfocament principal es centra en desenvolupar un algoritme de localització assistit per una RIS per millorar la precisió del posicionament de l'usuari utilitzant tècniques de compressió de senyal (CS). La integració d'una RIS ajuda a l'estació base a obtenir una ubicació més precisa mitigant els problemes causats per bloqueigs de la LOS. L'estudi actual suggereix un mètode d'optimització de fases que minimitza el Límit Inferior de Cramer-Rao (CRLB) per trobar la configuració òptima de fases de la RIS. No obstant això, el càlcul del CRLB per a diferents escenaris té un cost computacional elevat. Per abordar aquest repte, s'han aplicat tècniques de Machine Learning (ML) per desenvolupar una xarxa neuronal que pugui calcular les fases que minimitzen el CRLB basant-se únicament en la posició estimada de l'usuari. A més, per proporcionar una comparació exhaustiva dels resultats, també s'ha tingut en compte l'optimització de les fases de RIS basada en criteris de Relació Senyal-Soroll (SNR).

With Differential GNSS (DGNSS), Single Differentiation (SD) of GNSS pseudorange mea- surements is computed with the aim of correcting harmful errors such as ionospheric and tropospheric delays. These errors can be mitigated to up to very few centimeters, which denotes a performance improvement with respect to the Standard Point Positioning (SPP) solution, widely used in GNSS receivers. However, with DGNSS it is necessary to have a very precise knowledge of the coordinates of a reference station in order to experience this performance improvement. We propose the Massive User-Centric Single Differentiation (MUCSD) algorithm, which is proven to have a comparable performance to DGNSS with- out the need of a reference station. Instead, N cooperative receivers which provide noisy observations of their position and clock bias are introduced in the model. The MUCSD algorithm is mathematically derived with an Iterative Weighted Least Squares (WLS) Estimator. The estimator lower bound is calculated with the Cramér-Rao Bound (CRB). Several scenarios are simulated to test the MUCSD algorithm with the MassiveCoop-Sim simulator. Results show that if the observations provided by the cooperative users have a noise of up to 10 meters, DGNSS performance can be obtained with N = 10. When observations are very noisy, the MUCSD performance still approaches DGNSS for high values of N.

This research was funded by Albora Technologies and Universitat Politècnica de Catalunya with industrial PhD grant number DI 082 from the Generalitat de Catalunya; This research was partially funded by the Spanish Ministry of Science and Innovation project RTI2018-094295-B-I00. P.C. has been partially supported by the NSF under Awards CNS-1815349 and ECCS-1845833., Peer Reviewed, Postprint (author's final draft)

Recently, the Snapshot Real-Time Kinematic (SRTK) technique was demonstrated, which aims at achieving high accuracy navigation solutions with a very short signal collection. The main challenge in implementing SRTK is the generation of valid carrier-phase measurements, which relies on a data bit ambiguity (DBA) resolution process. For pilot signals, this step is equivalent to the correct selection of secondary code indexes (SCIs) from the ambiguous sets obtained from a multi-hypotheses (MH) acquisition process. Currently, SCI ambiguities are solved independently for each satellite. However, this method is ineffective when the snapshot signal is relatively short. In order to tackle this problem, this article proposes a new method that makes use of assistance data and processes information from all satellites to jointly solve the DBA issue. This new method is shown to be more effective in determining the correct SCI and enabling valid snapshot carrier-phase measurements, largely expanding the scope of high-accuracy snapshot positioning., This research was supported by the Albora Technologies and Universitat Politècnica de Catalunya with industrial PhD grant number DI 082 from the Generalitat de Catalunya and the project RTI2018-094295-B-I00 funded by the MCIN/AEI 10.13039/501100011033 which is co-funded by the FEDER programme. P.C. has been partially supported by the NSF under Awards CNS-1815349 and ECCS-1845833., Peer Reviewed, Postprint (published version)

With great potential for being applied to Internet of Things (IoT) applications, the concept of cloud-based Snapshot Real Time Kinematics (SRTK) was proposed and its feasibility under zero-baseline configuration was confirmed recently by the authors. This article first introduces the general workflow of the SRTK engine, as well as a discussion on the challenges of achieving an SRTK fix using actual snapshot data. This work also describes a novel solution to ensure a nanosecond level absolute timing accuracy in order to compute highly precise satellite coordinates, which is required for SRTK. Parameters such as signal bandwidth, integration time and baseline distances have an impact on the SRTK performance. To characterize this impact, different combinations of these settings are analyzed through experimental tests. The results show that the use of higher signal bandwidths and longer integration times result in higher SRTK fix rates, while the more significant impact on the performance comes from the baseline distance. The results also show that the SRTK fix rate can reach more than 93% by using snapshots with a data size as small as 255 kB. The positioning accuracy is at centimeter level when phase ambiguities are resolved at a baseline distance less or equal to 15 km., This research was funded by Albora Technologies and Universitat Politècnica de Catalunya with industrial PhD grant number DI 082 from the Generalitat de Catalunya; This research was partially funded by the Spanish Ministry of Science and Innovation project RTI2018-094295-B-I00. P.C. has been partially supported by the NSF under Awards CNS-1815349 and ECCS-1845833, Peer Reviewed, Postprint (published version)

With snapshot positioning becoming popular for various applications, the present contribution focuses on the feasibility of achieving Real Time Kinematics (RTK) positioning using snapshot data, i.e. a very brief interval of the received satellite signal. This method is termed as Snapshot RTK (SRTK). We first introduce the general workflow of snapshot positioning and the SRTK engine functioning blocks. Their differences from traditional receivers and challenges brought by the short duration of data are explained. Since a major difference of this positioning method is the generation of code and carrier-phase GNSS observables, we go through this procedure in details. In order to explore the feasibility of achieving RTK under different scenarios, the rate of Integer Ambiguity Resolution (IAR) is assessed by using snapshot measurements generated with different integration times and signal bandwidths under zero-baseline configuration. Under these assumptions, the key factor that influences the RTK fix rate is the code measurement noise. Double Difference (DD) code measurement errors are evaluated and plotted together with the resulting IAR fix rates in order to find the relationship between them. The performance of using multi-constellation and multi-frequency signals is tested as well. The fix rate can reach 100% when multiple constellations are used. The achieved positioning accuracy is shown to be less than 5 mm in horizontal domain when IAR is achieved successfully. Finally, some conclusions and thoughts about future research steps on SRTK are given., The author would like to acknowledge Albora Technologies for the technical support during the whole course of this research, including collection of raw data and developments of related software and libraries. The authors would like to thank Everis Aeroespacial y Defensa, S.L.U. for lending the Septentrio base station receiver for this research. The research reported in this paper has been partially supported by the Doctorat Industrial Grant 2018 DI 082 from the Generalitat de Catalunya, and the Spanish Ministry of Science, Innovation and Universities project RTI2018- 094295-B-I00. P. Closas was partially supported by the National Science Foundation under Awards CNS-1815349 and ECCS-1845833., Peer Reviewed, Postprint (published version)

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2017/2018

2017/2018

El motiu principal d’aquest text és estudiar el principals senyals dels sistemes electrònics que es troben en un vaixell. Aquests senyals duen informació que traslladem d’un lloc a un altre. La importància de l’estudi dels senyals dels sistemes electrònics rau en del fet de el seu coneixement permet una millor utilització d’aquests sistemes. Primerament proposarem una definició de la quantitat d’informació d’un missatge. Els missatges que fem servir per comunicar estan formats per senyals analògics o per senyals digitals. Atès els senyals va d’un punt a un altre, agafen soroll i poden desfigurar el missatge. Aquest soroll el podem suposar com a soroll blanc (té igual amplitud per a totes les freqüències), el soroll blanc el trobem si treballem amb senyals analògics. Si treballem amb senyals digitals tenim soroll blanc i soroll de quantificació. El soroll de quantificació es genera en transmissió al fer un tractament digital del senyal. Per pogué fer una transmissió acceptable d’un senyal analògic, hem de modular, variant les característiques d’una portadora amb el senyal a transmetre amb una portadora. Compararem els diferents modes de modulació de del punt de vista de la seva eficiència per transferir informació. En aquest llibre posarem les bases del tractament dels senyals digitals. També, analitzarem el senyals de Radar, Sonar i el filtre “Chirp” que treballen amb uns nivells de senyal molt dèbils. Dins d’aquests senyals de nivells molt baixos, també estudiarem el senyal del GPS que fa sevir la modulació CDMA que és adequada per treballar amb senyals molt dèbils., Postprint (published version)

Navigation and location technologies have been reaching in a major interest where Global Navigation Satellite System (GNSS) is mostly adopted. The limitation of this technology is that direct sky view is needed for reliable positioning. In indoor environments, however, it is difficult for GNSS technology to provide a reliable performance in positioning due to the signal attenuation and blocking caused by buildings and construction materials. For this reason, the growth in indoor applications has focused the research in new techniques for attempting mitigate the poor GNSS performance on this type of environments In the context of indoor positioning, multitude of emerging technologies for localization based on ultrasound, infrared, Ultra Wide Band (UWB), Zigbee, inertial navigation and other non-GNSS technologies have been proposed but special equipment is required and a large number of signal sources are needed. However, Wireless Local Area Network (WLAN) technology is widely used in indoor positioning. While the same requirements are also needed as the other technologies in order to improve the positioning accuracy, in terms of cost and ability, Wireless-based indoor location is widely used due to the already deployment of Anchor Points (AP) in urban and indoor areas. There are several methods for indoor positioning purposes e.g ToA (Time of Arrival), Received Signal Strength (RSS) measurements, AoA (Angle of Arrival), fingerprinting and so on. Most of the network-based location estimations use RSS measurements because almost all mobile devices are afforded to use this type of measurements. So, this thesis is centered in WLAN RSS-based positioning systems. The first step for indoor positioning is the distance estimation between the user and the AP. Theoretical and empirical propagation channel models are used to translate the difference between the transmitted and Received Signal Strength into an estimated range. A Propagation channel model built the radio map and a, Las tecnologías en navegación y localización han estado obteniendo un gran interés en los últimos años donde el Sistema Global de Navegación por Satélite (GNSS) aparece como el más utilizado para estos fines. No obstante, una de las limitaciones del GNSS es la necesidad de tener una visión directa al cielo para así garantizar un posicionamiento bastante fiable. También, al utilizar solamente tecnología GNSS en espacios interiores (más conocidos en el mundo científico por entornos indoor), se es complicado conseguir un buen desempeño en términos de posicionamiento debido a la atenuación e interferencia de la señal causada por los edificios y materiales de construcción. Por esta razón, y debido al crecimiento en aplicaciones dentro de entornos indoor, la investigación de nuevas tecnologías para posicionamiento en interiores se ha centrado en intentar mitigar el mal desempeño de la tecnología GNSS en este tipo de ambientes. En el contexto de posicionamiento en interiores (indoor positioning), se han propuesto multitud de tecnologías emergentes para localización basadas en ultrasonido, infrarrojo, Banda Ultra Ancha (UWB), Zigbee,navegación inercial y otras tecnologías que no sean GNSS. Sin embargo, se requiere de equipo especial y un gran número de fuentes de señal. A pesar de ello, la tecnología en Redes de Área Local Inalámbricas (WLAN) es ampliamente utilizada en el posicionamiento en interiores. Aunque la tecnología WLAN tenga los mismos requerimentos que el resto de tecnologías, en términos de coste y practicidad, los sistemas de posicionamiento basados en redes inalámbricas se utilizan con mayor frecuencia debido al ya existente despliegue de estaciones base (AP) en áreas urbanas e interiores. Existen varias técnicas que sirven para fines de posicionamiento en interiores. Por ejemplo, utilizando el tiempo de llegada de la señal (TOA), las mediciones de la potencia de la señal recibida ( RSS), el ángulo de llegada (AoA), la técnica fingerprinting entre otras. Esta, Postprint (published version)

In Wireless Sensor Networks (WSN), the ability of sensor nodes to know its position is an enabler for a wide variety of applications for monitoring, control, and automation. Often, sensor data is meaningful only if its position can be determined. Many WSN are deployed indoors or in areas where Global Navigation Satellite System (GNSS) signal coverage is not available, and thus GNSS positioning cannot be guaranteed. In these scenarios, WSN may be relied upon to achieve a satisfactory degree of positioning accuracy. Typically, batteries power sensor nodes in WSN. These batteries are costly to replace. Therefore, power consumption is an important aspect, being performance and lifetime of WSN strongly relying on the ability to reduce it. It is crucial to design effective strategies to maximize battery lifetime. Optimization of power consumption can be made at different layers. For example, at the physical layer, power control and resource optimization may play an important role, as well as at higher layers through network topology and MAC protocols. The objective of this Thesis is to study the optimization of resources in WSN that are employed for positioning purposes, with the ultimate goal being the minimization of power consumption. We focus on anchor-based positioning, where a subset of the WSN nodes know their location (anchors) and send ranging signals to nodes with unknown position (targets) to assist them in estimating it through distance-related measurements. Two well known of such measurements are received signal strength (RSS) and time of arrival (TOA), in which this Thesis focuses. In order to minimize power consumption while providing a certain quality of positioning service, in this dissertation we research on the problems of power control and node selection. Aiming at a distributed implementation of the proposed techniques, we resort to the tools of non-cooperative game theory. First, transmit power allocation is addressed for RSS based ranging. Using gam, En les xarxes de sensors sense fils (WSN), l'habilitat dels nodes sensors per conèixer la seva posició facilita una gran varietat d'aplicacions per la monitorització, el control i l'automatització. Així, les dades que proporciona un sensor tenen sentit només si la posició pot ésser determinada. Moltes WSN són desplegades en interiors o en àrees on la senyal de sistemes globals de navegació per satèl.lit (GNSS) no té prou cobertura, i per tant, el posicionament basat en GNSS no pot ésser garantitzat. En aquests escenaris, les WSN poden proporcionar una bona precisió en posicionament. Normalment, en WSN els nodes són alimentats amb bateries. Aquestes bateries són difícils de reemplaçar. Per tant, el consum de potència és un aspecte important i és crucial dissenyar estratègies efectives per maximitzar el temps de vida de la bateria. L'optimització del consum de potència pot ser fet a diferents capes del protocol. Per exemple, en la capa física, el control de potència i l'optimització dels recursos juguen un rol important, igualment que la topologia de xarxa i els protocols MAC en les capes més altes. L'objectiu d'aquesta tesi és estudiar l¿optimització de recursos en WSN que s'utilitzen per fer posicionament, amb el propòsit de minimitzar el consum de potència. Ens focalitzem en el posicionament basat en àncora, en el qual un conjunt de nodes coneixen la seva localització (nodes àncora) i envien missatges als nodes que no saben la seva posició per ajudar-los a estimar les seves coordenades amb mesures de distància. Dues classes de mesures són la potència de la senyal rebuda (RSS) i el temps d'arribada (TOA) en les quals aquesta tesi està focalitzada. Per minimitzar el consum de potència mentre que es proporciona suficient qualitat en el posicionament, en aquesta tesi estudiem els problemes de control de potència i selecció de nodes. Tenint en compte una implementació distribuïda de les tècniques proposades, utilitzem eïnes de teoria de jocs no cooperatius. Primer, l'as, Postprint (published version)

Smartphones containing multi-core central processing units (CPUs) and powerful many-core graphics processing units (GPUs) bring supercomputing technology into your pocket (or into our embedded devices). This can be exploited to produce power-efficient, customized receivers with flexible correlation schemes and more advanced positioning techniques. For example, promising techniques such as the Direct Position Estimation paradigm or usage of tracking solutions based on particle filtering, seem to be very appealing in challenging environments but are likewise computationally quite demanding. This article sheds some light onto recent embedded processor developments, benchmarks Fast Fourier Transform (FFT) and correlation algorithms on representative embedded platforms and relates the results to the use in GNSS software radios. The use of embedded CPUs for signal tracking seems to be straight forward, but more research is required to fully achieve the nominal peak performance of an embedded GPU for FFT computation. Also the electrical power consumption is measured in certain load levels., Peer Reviewed, Postprint (published version)

Un dels reptes més difícils de la neurociència és el d'entendre la connectivitat del cervell. Aquest problema es pot tractar des de diverses perspectives, aquí ens centrem en els fenòmens locals que ocorren en una sola neurona. L'objectiu final és, doncs, entendre la dinàmica de les neurones i com la interconnexió amb altres neurones afecta al seu estat. Les observacions de traces del potencial de membrana constitueixen la principal font d'informació per a derivar models matemàtics d'una neurona, amb cert sentit biofísic. En particular, la dinàmica de les variables auxiliars i els paràmetres del model són estimats a partir d'aquestes traces de voltatge. El procés és en general costós i típicament implica una gran varietat de blocatges químics de canals iònics, així com una certa incertesa en els valors dels paràmetres a causa del soroll de mesura. D'altra banda, les traces de potencial de membrana també són útils per obtenir informació valuosa sobre l'entrada sinàptica, un problema invers sense solució satisfactòria a hores d'ara. En aquesta Tesi, estem interessats en mètodes d'estimació seqüencial, que permetin evitar la necessitat de repeticions que podrien ser contaminades per la variabilitat neuronal. En particular, ens concentrem en mètodes per extreure l'activitat intrínseca dels canals iònics, és a dir, les probabilitats d'obertura i tancament de canals iònics, i la contribució de les conductàncies sinàptiques. Hem dissenyat un mètode basat en la teoria Bayesiana de filtrat per inferir seqüencialment aquestes quantitats a partir d'una única traça de voltatge, potencialment sorollosa. El mètode d'estimació proposat està basat en la suposició d'un model de neurona conegut. Això és cert fins a cert punt, però la majoria dels paràmetres en el model han de ser estimats per endavant (això és valid per a qualsevol model). Per tant, el mètode s'ha millorat pel cas de models amb paràmetres desconeguts, incloent-hi un procediment per estimar conjuntament els paràmetres

This paper addresses the problem of determining the Cramér-Rao lower bound (CRLB) for the parameters and breakpoint distance in a Path-Loss Channel model for Received Signal Strength (RSS) measurements. The path loss model is usually assumed for corrupted RSS measurements due to the shadow fading channel feature. In this paper the two-slope path loss model is considered, in which RSS measurements are modeled differently for close and far distances. Closed-form expressions for the CRLB parameters are derived for unknown breakpoint distance. For unknown parameters and breakpoint distance value, a Bayesian estimation method is proposed. The CRLB is then compared with the performance of the herein proposed method. The comparison illustrates convergence and efficiency of the Bayesian estimator., Postprint (published version)

In this paper, we focus on the application of Compressive Sensing (CS) techniques to Impulse Radio (IR) Ultra-WideBand (UWB) positioning systems under indoor propagation environments. Direct Position Estimation (DPE) approaches can potentially improve the position estimation accuracy of conventional two-step techniques by directly estimating the position coordinates from the observed signal in a single step. Furthermore, DPE does not require a threshold selection upon which accuracy of two-step approaches depend on. Although in the presence of multipath the actual gains are not straight forward, recent evaluation of DPE positioning in IR-UWB system proved accurate positioning estimate gains. However it comes at a cost of higher computational complexity. This paper exploits the sparseness of the problem to reduce the computational load of the positioning estimation process and relax the requirements of the Analog to Digital Converter (ADC) when sampling UWB signals. Based on the fact that the number of unknown targets is small in the discrete spatial domain, this paper incorporates the multiple location hypotheses into an overcomplete basis, which highlights the sparseness of the spatial domain. This fact motivates the use of CS-based sampling and sparsity-based reconstruction techniques to jointly evaluate all possible hypotheses, thus avoiding the traditional position-by-position scanning where the multiple location hypotheses are evaluated independently. In so doing, we not only achieve a significant reduction in computational time but also we relax the sampling requirements., Postprint (published version)

Bayesian ltering appears in many signal processing problems,reason why it attracted the attention of many researchers to develop efficient algorithms, yet computationally a ordable. In many real systems, it is appropriate to consider α-stable noise distributions to model possible outliers or impulsive behavior in the measurements. In this paper, we consider a nonlinear state-space model with Gaussian process noise and symmetric α-stable measurement noise. To obtain a robust estimation framework we consider that both process and measurement noise statistics are unknown. Using the product property of α-stable distributions we rewrite the measurement noise in a conditionally Gaussian form. Within this framework, we propose an hybrid sigma-point/Monte Carlo approach to solve the Bayesian ltering problem, what leads to a robust method against both outliers and a weak knowledge of the system., Peer Reviewed, Postprint (published version)

Peer Reviewed, Postprint (published version)

This chapter presents several signal processing strategies to combine together, in a seamless estimation process, position-related measurements coming from different technologies and/or systems (e.g., TOA and TDOA measurements in terrestrial networks, TOA and RSS measurements, or even satellite and terrestrial systems, or satellite and inertial navigation systems). This approach, generally indicated as “hybridization”, promises to provide better accuracy with respect to its stand-alone counterparts, or better availability thanks to the diversity of the employed technologies. For example, hybridization between satellite and inertial systems is expected to compensate for the respective fragilities of the two systems, namely the relatively high error variance of the former and the drift of the latter. The mathematical framework where hybridization is developed is Bayesian filtering: the generic structure is reviewed and the well-known Kalman filter and its variants are inserted in the framework, with examples of applications to positioning problems. Then the particle filter approach is explained, with its most used variants. Examples of hybrid localization algorithms are then shown, starting from a hybrid terrestrial architecture, then passing to the architectures that blend GNSS and inertial measurements, using either the Kalman filter approach or the direct position estimation approach. Finally, an example of hybrid localization based on GNSS and peer-to-peer terrestrial signaling is presented., Postprint (published version)

This chapter presents the results of a testing and validation activity carried out to analyze the performance of signal-processing techniques related to positioning and navigation. The steps included the setup of a measurement campaign and the setup of a shared database, the usage of this database to test algorithms, and the development of a software defined radio (SDR)-based architecture for a GNSS receiver, to be used for advanced laboratory tests on innovative GNSS-related signal processing algorithms. During the measurement campaign, a total of 22 ZigBee-based devices, model CC2430 made by Texas Instruments, were used to measure RSS values. Each of them is a single chip solution which integrates microprocessor and radio interface compliant with the IEEE 802.15.4 standard at 2.4 GHz. Two UWB-based devices, model PulsOn220 made by Time Domain, were used to perform TOA ranging measurements in both static and dynamic scenarios. During the test, the receiver in light-indoor condition could autonomously track only one satellite, identified as PRN 9. This PRN was also tracked by the aiding user; therefore, it was used to estimate the clock offset among the two PCs., Postprint (published version)

In this paper, the issue of network topology control in wireless networks using a fully distributed algorithm is considered. Whereas the proposed distributed algorithm is designed applying game theory concepts to design a non-cooperative game, network connectivity is guaranteed based on asymptotic results of network connectivity. Simulations show that for a relatively low node density, the probability that the proposed algorithm leads to a connected network is close to one., Peer Reviewed, Postprint (published version)

Aquesta tesi gira al voltant del disseny de receptors per a sistemes globals de navegació per satèl·lit (Global Navigation Satellite Systems, GNSS). El terme GNSS fa referència a tots aquells sistemes de navegació basats en una constel·lació de satèl·lits que emeten senyals de navegació útils per a posicionament. El més popular és l'americà GPS, emprat globalment. Els esforços d'Europa per a tenir un sistema similar veuran el seu fruit en un futur proper, el sistema s'anomena Galileo. Altres sistemes globals i regionals existeixen dissenyats per al mateix objectiu: calcular la posició dels receptors. Inicialment la tesi presenta l'estat de l'art en GNSS, a nivell de l'estructura dels actuals senyals de navegació i pel que fa a l'arquitectura dels receptors. El disseny d'un receptor per a GNSS consta d'un seguit de blocs funcionals. Començant per l'antena receptora fins al càlcul final de la posició del receptor, el disseny proporciona una gran motivació per a la recerca en diversos àmbits. Tot i que la cadena de Radiofreqüència del receptor també és comentada a la tesis, l'objectiu principal de la recerca realitzada recau en els algorismes de processament de senyal emprats un cop realitzada la digitalització del senyal rebut. En un receptor per a GNSS, aquests algorismes es poden dividir en dues classes: els de sincronisme i els de posicionament. Aquesta classificació correspon als dos grans processos que típicament realitza el receptor. Primer, s'estima la distancia relativa entre el receptor i el conjunt de satèl·lits visibles. Aquestes distancies es calculen estimant el retard patit pel senyal des de que és emès pel corresponent satèl·lit fins que és rebut pel receptor. De l'estimació i seguiment del retard se n'encarrega l'algorisme de sincronisme. Un cop calculades la distancies relatives als satèl·lits, multiplicant per la velocitat de la llum el retards estimats, l'algorisme de posicionament pot operar. El posicionament es realitza típicament pel pro, This dissertation deals with the design of satellite-based navigation receivers. The term Global Navigation Satellite Systems (GNSS) refers to those navigation systems based on a constellation of satellites, which emit ranging signals useful for positioning. Although the american GPS is probably the most popular, the european contribution (Galileo) will be operative soon. Other global and regional systems exist, all with the same objective: aid user's positioning. Initially, the thesis provides the state-of-the-art in GNSS: navigation signals structure and receiver architecture. The design of a GNSS receiver consists of a number of functional blocks. From the antenna to the final position calculation, the design poses challenges in many research areas. Although the Radio Frequency chain of the receiver is commented in the thesis, the main objective of the dissertation is on the signal processing algorithms applied after signal digitation. These algorithms can be divided into two: synchronization and positioning. This classification corresponds to the two main processes typically performed by a GNSS receiver. First, the relative distance between the receiver and the set of visible satellites is estimated. These distances are calculated after estimating the delay suffered by the signal traveling from its emission at the corresponding satellite to its reception at the receiver's antenna. Estimation and tracking of these parameters is performed by the synchronization algorithm. After the relative distances to the satellites are estimated, the positioning algorithm starts its operation. Positioning is typically performed by a process referred to as trilateration: intersection of a set of spheres centered at the visible satellites and with radii the corresponding relative distances. Therefore, synchronization and positioning are processes performed sequentially and in parallel. The thesis contributes to both topics, as expressed by the subtitle of the dissertation.

This work is part of UPC contribution to the CORPA (Cost-Optimised high Performance Active Receive Phase Array antenna for mobile terminals) project of ESA (European Space Agency), The objective of the work presented is to implement a Digital Beamforming (DBF) platform for an antenna array receiver designed for the S-DMB system. Our project deals with the design of antenna arrays from a hardware point of view, in contrast to other theo- retic studies regarding DBF algorithms. Hence, we will study practical aspects of DBF implementation such as signal quantization and required computational resources.

In this letter, we obtain the Maximum Likelihood Estimator of position in the framework of Global Navigation Satellite Systems. This theoretical result is the basis of a completely different approach to the positioning problem, in contrast to the conventional two-steps position estimation, consisting of estimating the synchronization parameters of the in-view satellites and then performing a position estimation with that information. To the authors’ knowledge, this is a novel approach which copes with signal fading and it mitigates multipath and jamming interferences. Besides, the concept of Position–based Synchronization is introduced, which states that synchronization parameters can be recovered from a user position estimation. We provide computer simulation results showing the robustness of the proposed approach in fading multipath channels. The Root Mean Square Error performance of the proposed algorithm is compared to those achieved with state-of-the-art synchronization techniques. A Sequential Monte–Carlo based method is used to deal with the multivariate optimization problem resulting from the ML solution in an iterative way., Peer Reviewed