A wide range of services and applications become possible when accurate position information for a radio terminal is available. These include: location-based services; navigation; safety and security applications. The commercial, industrial and military value of radio-location is such that considerable research effort has been directed towards developing related technologies, using satellite, cellular or local area network infrastructures or stand-alone equipment. This work studies and investigates two location techniques. The first one presents an implementation scheme for a wideband transmission and direction finding system using OFDM multi-carrier communications systems. This approach takes advantage of delay discrimination to improve angle-of-arrival estimation in a multipath channel with high levels of additive white Gaussian noise. A new methodology is interpreted over the multi carrier modulation scheme in which the simulation results of the estimated channel improves the performance of OFDM signal by mitigating the effect of frequency offset synchronization to give error-free data at the receiver, good angle of arrival accuracy and improved SNR performance. The full system simulation to explore optimum values such as channel estimation and AoA including the antenna array model and prove the operational performance of the OFDM system as implemented in MATLAB. The second technique proposes a low cost-effective method of tracking and monitoring objects (examples: patient, device, medicine, document) by employing passive radio frequency identification (RFID) systems. A multi-tag, (totalling fifty-six tags) with known ID values are attached to the whole patient’s body to achieve better tracking and monitoring precision and higher accuracy. Several tests with different positions and movements are implemented on six patients. The aim is to be able to track the patient if he/she is walking or sitting; therefore, the tests considered six possible movements for the patient including walking, standing, sitting, resting, laying on the floor and laying on the bed, these placements are important to monitor the status of the patient like if he collapsed and fall on the ground so that the help will be quick. The collected data from the RFID Reader in terms of Time Stamp, RSS, Tag ID, and a number of channels are processed using the MATLAB code.

The objective of this work is to enhance the awareness of the indoor propagation behaviour, by a set of investigations including simulations and measurements. These investigations include indoor propagation behaviour, local mean power estimation, proposing new indoor path loss model and introducing a case study on 60 GHz propagation in indoor environments using ray tracing and measurements. A summary of propagation mechanisms and manifestations in the indoor environment is presented. This comprises the indoor localization techniques using channel parameters in terms of angle of arrival (AOA), time of arrival (TOA) and received signal strength (RSS). Different models of path loss, shadowing and fast fading mechanisms are explored. The concept of MIMO channels is studied using many types of deterministic channel modelling such as Finite Difference Time Domain, Ray tracing and Dominant path model. A comprehensive study on estimating local average of the received signal strength (RSS) for indoor multipath propagation is conducted. The effect of the required number of the RSS data and their Euclidian distances between the neighbours samples are investigated over 1D, 2D and 3D configurations. It was found that the effect of fast fading was reduced sufficiently using 2D horizontal’s arrangement with larger spacing configuration. A modified indoor path loss prediction model is presented namely effective wall loss model (EWLM). The modified model with wall correction factors is compared to other indoor path loss prediction models using simulation data (for 2.4, 5, 28, 60 and 73.5 GHz) and real-time measurements (for 2.4 and 5 GHz). Different operating frequencies and antenna polarizations are considered to verify the observations. In the simulation part, EWLM shows the best performance among other models. Similar observations were recorded from the experimental results. Finally, a detailed study on indoor propagation environment at 60 GHz is conducted. The study is supported by Line of Sight (LoS) and Non-LoS measurements data. The results were compared to the simulated ones using Wireless-InSite ray tracing software. Several experiments have confirmed the reliability of the modelling process based on adjusted material properties values from measurements.

This project investigates developing and implementing innovative indoornavigation systems by leveraging repurposed Wi-Fi infrastructure anddedicated RFM69HCW transceivers. Aimed at enhancing indoor positioningaccuracy, the study explores the viability of using Received Signal StrengthIndicator (RSSI) and dedicated device localization techniques to overcomethe limitations of existing Global Positioning System (GPS) technology inindoor environments. Through the design and testing of a printed circuit board(PCB) prototype that connects Raspberry Pi Pico (RPP) to RFM69HCWmodules and the development of custom drivers for the RP2040 processor,this research addresses the challenges of indoor navigation, such as signalvariability and environmental interference. The project also emphasizes theimportance of sustainable technology development by repurposing electronicwaste for innovative applications. Findings from the study reveal the potentialof these methodologies to improve indoor positioning accuracy despitechallenges related to hardware compatibility and the dynamic nature of indoorspaces. This research contributes to indoor navigation by demonstrating thefeasibility of using repurposed and dedicated hardware solutions, offeringinsights into future directions for enhancing indoor navigation systems, andhighlighting the role of sustainability in technological innovation.

L'objectif de la thèse est d'étudier la variation temporelle de la qualité des liens dans les réseaux de capteurs sans fil à grande échelle, de concevoir des estimateurs permettant la différenciation, à court terme et long terme, entre liens de qualité hétérogène. Tout d'abord, nous étudions les caractéristiques de deux paramètres de la couche physique: RSSI (l'indicateur de puissance du signal reçu) et LQI (l'indicateur de la qualité de liaison) sur SensLab, une plateforme expérimentale de réseau de capteurs à grande échelle situé à l'intérieur de bâtiments. Nous observons que le RSSI et le LQI permettent de discriminer des liens de différentes qualités. Ensuite, pour obtenir un estimateur de PRR, nous avons approximé le diagramme de dispersion de la moyenne et de l'écart-type du LQI et RSSI par une fonction Fermi-Dirac. La fonction nous permet de trouver le PRR à partir d'un niveau donné de LQI. Nous avons évalué l'estimateur en calculant le PRR sur des fenêtres de tailles variables et en le comparant aux valeurs obtenues avec l'estimateur. Par ailleurs, nous montrons en utilisant le modèle de Gilbert-Elliot (chaîne de Markov à deux états) que la corrélation des pertes de paquets dépend de la catégorie de lien. Le modèle permet de distinguer avec précision les différentes qualités des liens, en se basant sur les probabilités de transition dérivées de la moyenne et de l'écart-type du LQI. Enfin, nous proposons un modèle de routage basé sur la qualité de lien déduite de la fonction de Fermi-Dirac approximant le PRR et du modèle Markov Gilbert-Elliot à deux états. Notre modèle est capable de distinguer avec précision les différentes catégories de liens ainsi que les liens fortement variables. / The goal of the thesis is to investigate the issues related to the temporal link quality variation in large scale WSN environments, to design energy efficient link quality estimators able to distinguish among links with different quality on a short and a long term. First, we investigate the characteristics of two physical layer metrics: RSSI (Received Signal Strength Indication) and LQI (Link Quality Indication) on SensLAB, an indoor large scale wireless sensor network testbed. We observe that RSSI and LQI have distinct values that can discriminate the quality of links. Second, to obtain an estimator of PRR, we have fitted a Fermi-Dirac function to the scatter diagram of the average and standard variation of LQI and RSSI. The function enables us to find PRR for a given level of LQI. We evaluate the estimator by computing PRR over a varying size window of transmissions and comparing with the estimator. Furthermore, we show using the Gilbert-Elliot two-state Markov model that the correlation of packet losses and successful receptions depend on the link category. The model allows to accurately distinguish among strongly varying intermediate links based on transition probabilities derived from the average and the standard variation of LQI. Finally, we propose a link quality routing model driven from the F-D fitting functions and the Markov model able to discriminate accurately link categories as well as high variable links.

This report evaluates various methods that can be used to position a smartphone running the Android platform, without the use of any special hardware or infrastructure and in conditions where GPS is unavailable or unreliable; such as indoors. Furthermore, it covers the implementation of such a system with the use of a deterministic fingerprinting method that is reasonably device independent, a method which involves measuring a series of reference points, called fingerprints, in an area and using those to locate the user. The project was carried on behalf of Sigma, a Swedish software consulting company. / Denna rapport evaluerar olika metoder för att bestämma positionen av en smartphone som använder sig av Android-plattformen. Metoden skall inte använda sig av någon speciell hårdvara eller infrastruktur samt kunna hantera förhållanden där GPS är otillgängligt eller opålitligt, som till exempel inomhus. Den beskriver också implementation av ett sådant system som använder sig av en deterministisk fingerprinting-metod som någorlunda väl kan hantera enheter av olika modeller, en metod som innebär att man mäter upp en mängd med referenspunkter, kallade fingerprints, och använder dessa för att placera användaren. Projektet utfördes på uppdrag av Sigma, ett svenskt mjukvarukonsultbolag.

Various applications of Wireless Sensor Networks (WSNs) require accurate localization of sensor nodes. The quantity and locations of anchor nodes, which serve as reference points for distance estimates, as well as the localization process itself, affect the localization accuracy. Furthermore, because numerous communications are sent between nodes for localization, energy consumption must be considered. This work presents an energy-aware and accurate localization method. It is based on a combined anchor deployment and energy-aware localization. The proper number and distribution of anchors have been investigated to achieve full network coverage and connectivity based on an efficient and heterogeneous hexagonal deployment. Later, energy-aware localization is performed in three stages: Initialization, signal acquisition, and anchor selection. The initialization step allows the network to be adaptable to sudden changes by establishing anchor connectivity and creating the neighbors' list. Meanwhile, the Received Signal Strength Indicator (RSSI) is used for distance measurements between nodes, with the implementation of a Kalman filter to reduce signal attenuation and noise. Later, the anchor selection is done using fuzzy logic with inference parameters: RSSI, node density, and residual energy. This step ensures that only operable anchors engage in localization, while anchors with inadequate energy sources remain intact to ensure their future availability.:1 Introduction 2 Theoretical background 3 Energy-aware outdoor deployment and localization 4 Proposed anchor deployment method 5 Proposed energy-aware localization method 6 Experimental validation of the proposed localization method / Verschiedene Anwendungen von drahtlosen Sensornetzwerken (WSNs) erfordern eine genaue Lokalisierung von Sensorknoten. Die Anzahl und Standorte der Ankerknoten, die als Referenzpunkte für Entfernungsschätzungen dienen, sowie der Lokalisierungsprozess selbst beeinflussen die Lokalisierungsgenauigkeit. Da für die Lokalisierung zahlreiche Nachrichten zwischen den Knoten gesendet werden, muss außerdem der Energieverbrauch berücksichtigt werden. In dieser Arbeit wird eine energiebewusste und genaue Lokalisierungsmethode vorgestellt. Sie basiert auf einer Kombination aus effizienter Ankerknotennutzung und energiebewusster Lokalisierung. Die richtige Anzahl und Verteilung von Ankern wurde untersucht, um eine vollständige Netzabdeckung und Konnektivität auf der Grundlage einer effizienten und heterogenen hexagonalen Verteilung zu erreichen. Später wird die energiebewusste Lokalisierung in drei Stufen durchgeführt: Initialisierung, Signalerfassung und Ankerauswahl. Der Initialisierungsschritt ermöglicht es dem Netzwerk, sich an plötzliche Veränderungen anzupassen, indem es die Verbindung zu den Ankern und die Liste der Nachbarn erstellt. Zunächst wird der Received Signal Strength Indicator (RSSI) für die Entfernungsmessung zwischen den Knoten verwendet, wobei ein Kalman-Filter implementiert wird, um Signalabschwächung und Rauschen zu reduzieren. Später erfolgt die Ankerauswahl mit Hilfe von Fuzzy-Logik und Inferenzparametern: RSSI, Knotendichte und Restenergie. Dieser Schritt stellt sicher, dass nur funktionsfähige Anker an der Lokalisierung teilnehmen, während Anker mit unzureichenden Energiequellen intakt bleiben, um ihre zukünftige Verfügbarkeit zu gewährleisten.:1 Introduction 2 Theoretical background 3 Energy-aware outdoor deployment and localization 4 Proposed anchor deployment method 5 Proposed energy-aware localization method 6 Experimental validation of the proposed localization method