Minimization of IEEE 802.11p Packet Collision Interference through Transmission Time Shifting

V2I communications are characterized by the presence of network nodes in vehicles and in the infrastructures that these vehicles use, as well as by the wireless interactions among them. Safety-related applications demand stringent requirements in terms of latency and packet delivery probability, especially when safety messages have to be delivered to vehicles by the infrastructure. Interference issues stem from the typical characteristics of wireless communications, i.e., the noise of the wireless medium, the limited communication range of the wireless entities, and the receiver passivity of all the conventional wireless transceivers during transmissions. This paper presents a synchronization mechanism to artificially replicate at a host premises destructive interference due to hidden terminals, together with an application-level technique to minimize that interference by shifting the packet transmission time, similarly to the MAC TDMA channel access method. As both have been field-tested, the paper also analyzes the results of these tests, all performed with real hardware on IEEE 802.11p over different frequencies and transmission powers, and with repeatability in mind. The resulting figures attest that interference effects due to hidden terminals may indeed take place on real IEEE 802.11p networks, and that carefully designed time-shifting mechanisms can actively mitigate them

Indoor Positioning Using the Modified Fingerprint Technique

The Wi-Fi positioning systems available for enclosed spaces use the existing network infrastructure to calculate the position of the mobile device (MD). The most commonly used parameter is RSSI (Received Signal Strength Indicator). In this paper, we analyze the Fingerprint technique considering some variations aimed at improving the accuracy of the technique and minimizing calculation time. Significant field work is carried out, analyzing the accuracy achieved with each technique.Fil: Kornuta, Carlos Antonio. Universidad Nacional del Centro de la Pcia.de Bs.as.. Facultad de Cs.exactas. Instituto de Invest.en Tecnologia Informatica Avanzada; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Tandil; ArgentinaFil: Acosta, Héctor Nelson. Universidad Nacional del Centro de la Pcia.de Bs.as.. Facultad de Cs.exactas. Instituto de Invest.en Tecnologia Informatica Avanzada; ArgentinaFil: Toloza, Juan Manuel. Universidad Nacional del Centro de la Pcia.de Bs.as.. Facultad de Cs.exactas. Instituto de Invest.en Tecnologia Informatica Avanzada; Argentina. Consejo Nacional de Investigaciones Cientificas y Tecnicas. Ctro Cientifico Tecnologico Conicet - Tandil. Unidad de Adm. Territorial; Argentin

Fingerprint Database Variations for WiFi Positioning

Indoor positioning systems calculate the position of a mobile device (MD) in an enclosed environment with relative precision. Most systems use WiFi infrastructure and several positioning techniques, where the most commonly used parameter is RSSI (Received Signal Strength Indicator). In this paper, we analyze the fingerprinting technique to calculate the error window obtained with the Euclidian distance as main metric. Build variations are presented for the Fingerprint database analyzing various statistical values to compare the precision achieved with different indicators.Fil: Acosta, Nelson. Universidad Nacional del Centro de la Provincia.de Buenos Aires. Facultad de Ciencias Exactas. Instituto de Investigaciones en Tecnologia Informatica Avanzada; ArgentinaFil: Toloza, Juan Manuel. Universidad Nacional del Centro de la Provincia.de Buenos Aires. Facultad de Ciencias Exactas. Instituto de Investigaciones en Tecnologia Informatica Avanzada; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Tandil; ArgentinaFil: Kornuta, Carlos Antonio. Universidad Nacional del Centro de la Provincia.de Buenos Aires. Facultad de Ciencias Exactas. Instituto de Investigaciones en Tecnologia Informatica Avanzada; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Tandil; Argentin

An Adaptive Multimedia-Oriented Handoff Scheme for IEEE 802.11 WLANs

Previous studies have shown that the actual handoff schemes employed in the IEEE 802.11 Wireless LANs (WLANs) do not meet the strict delay constraints placed by many multimedia applications like Voice over IP. Both the active and the passive supported scan modes in the standard handoff procedure have important delay that affects the Quality of Service (QoS) required by the real-time communications over 802.11 networks. In addition, the problem is further compounded by the fact that limited coverage areas of Access Points (APs) occupied in 802.11 infrastructure WLANs create frequent handoffs. We propose a new optimized and fast handoff scheme that decrease both handoff latency and occurrence by performing a seamless prevent scan process and an effective next-AP selection. Through simulations and performance evaluation, we show the effectiveness of the new adaptive handoff that reduces the process latency and adds new context-based parameters. The Results illustrate a QoS delay-respect required by applications and an optimized AP-choice that eliminates handoff events that are not beneficial.Comment: 20 pages, 14 figures, 4 table

Localisation en intérieur et gestion de la mobilité dans les réseaux sans fils hétérogènes émergents

Au cours des dernières décennies, nous avons été témoins d'une évolution considérable dans l'informatique mobile, réseau sans fil et des appareils portatifs. Dans les réseaux de communication à venir, les utilisateurs devraient être encore plus mobiles exigeant une connectivité omniprésente à différentes applications qui seront de préférence au courant de leur contexte. Certes, les informations de localisation dans le cadre de leur contexte est d'une importance primordiale à la fois la demande et les perspectives du réseau. Depuis l'application ou de point de vue utilisateur, la fourniture de services peut mettre à jour si l'adaptation au contexte de l'utilisateur est activée. Du point de vue du réseau, des fonctionnalités telles que le routage, la gestion de transfert, l'allocation des ressources et d'autres peuvent également bénéficier si l'emplacement de l'utilisateur peuvent être suivis ou même prédit. Dans ce contexte, nous nous concentrons notre attention sur la localisation à l'intérieur et de la prévision transfert qui sont des composants indispensables à la réussite ultime de l'ère de la communication omniprésente envisagé. Alors que les systèmes de positionnement en plein air ont déjà prouvé leur potentiel dans un large éventail d'applications commerciales, le chemin vers un système de localisation à l'intérieur de succès est reconnu pour être beaucoup plus difficile, principalement en raison des caractéristiques difficiles à l'intérieur et l'exigence d'une plus grande précision. De même, la gestion de transfert dans le futur des réseaux hétérogènes sans fil est beaucoup plus difficile que dans les réseaux traditionnels homogènes. Régimes de procédure de transfert doit être sans faille pour la réunion strictes de qualité de service (QoS) des applications futures et fonctionnel malgré la diversité des caractéristiques de fonctionnement des différentes technologies. En outre, les décisions transfert devraient être suffisamment souples pour tenir compte des préférences utilisateur d'un large éventail de critères proposés par toutes les technologies. L'objectif principal de cette thèse est de mettre au point précis, l'heure et l'emplacement de puissance et de systèmes efficaces de gestion de transfert afin de mieux satisfaire applications sensibles au contexte et mobiles. Pour obtenir une localisation à l'intérieur, le potentiel de réseau local sans fil (WLAN) et Radio Frequency Identification (RFID) que l'emplacement autonome technologies de détection sont d'abord étudiés par des essais plusieurs algorithmes et paramètres dans un banc d'essai expérimental réel ou par de nombreuses simulations, alors que leurs lacunes sont également été identifiés. Leur intégration dans une architecture commune est alors proposée afin de combiner leurs principaux avantages et surmonter leurs limitations. La supériorité des performances du système de synergie sur le stand alone homologues est validée par une analyse approfondie. En ce qui concerne la tâche de gestion transfert, nous repérer que la sensibilité au contexte peut aussi améliorer la fonctionnalité du réseau. En conséquence, deux de tels systèmes qui utilisent l'information obtenue à partir des systèmes de localisation sont proposées. Le premier schéma repose sur un déploiement tag RFID, comme notre architecture de positionnement RFID, et en suivant la scène WLAN analyse du concept de positionnement, prédit l'emplacement réseau de la prochaine couche, c'est à dire le prochain point de fixation sur le réseau. Le second régime repose sur une approche intégrée RFID et sans fil de capteur / actionneur Network (WSAN) de déploiement pour la localisation des utilisateurs physiques et par la suite pour prédire la prochaine leur point de transfert à deux couches de liaison et le réseau. Etre indépendant de la technologie d'accès sans fil principe sous-jacent, les deux régimes peuvent être facilement mises en œuvre dans des réseaux hétérogènes [...]Over the last few decades, we have been witnessing a tremendous evolution in mobile computing, wireless networking and hand-held devices. In the future communication networks, users are anticipated to become even more mobile demanding for ubiquitous connectivity to different applications which will be preferably aware of their context. Admittedly, location information as part of their context is of paramount importance from both application and network perspectives. From application or user point of view, service provision can upgrade if adaptation to the user's context is enabled. From network point of view, functionalities such as routing, handoff management, resource allocation and others can also benefit if user's location can be tracked or even predicted. Within this context, we focus our attention on indoor localization and handoff prediction which are indispensable components towards the ultimate success of the envisioned pervasive communication era. While outdoor positioning systems have already proven their potential in a wide range of commercial applications, the path towards a successful indoor location system is recognized to be much more difficult, mainly due to the harsh indoor characteristics and requirement for higher accuracy. Similarly, handoff management in the future heterogeneous wireless networks is much more challenging than in traditional homogeneous networks. Handoff schemes must be seamless for meeting strict Quality of Service (QoS) requirements of the future applications and functional despite the diversity of operation features of the different technologies. In addition, handoff decisions should be flexible enough to accommodate user preferences from a wide range of criteria offered by all technologies. The main objective of this thesis is to devise accurate, time and power efficient location and handoff management systems in order to satisfy better context-aware and mobile applications. For indoor localization, the potential of Wireless Local Area Network (WLAN) and Radio Frequency Identification (RFID) technologies as standalone location sensing technologies are first studied by testing several algorithms and metrics in a real experimental testbed or by extensive simulations, while their shortcomings are also identified. Their integration in a common architecture is then proposed in order to combine their key benefits and overcome their limitations. The performance superiority of the synergetic system over the stand alone counterparts is validated via extensive analysis. Regarding the handoff management task, we pinpoint that context awareness can also enhance the network functionality. Consequently, two such schemes which utilize information obtained from localization systems are proposed. The first scheme relies on a RFID tag deployment, alike our RFID positioning architecture, and by following the WLAN scene analysis positioning concept, predicts the next network layer location, i.e. the next point of attachment to the network. The second scheme relies on an integrated RFID and Wireless Sensor/Actuator Network (WSAN) deployment for tracking the users' physical location and subsequently for predicting next their handoff point at both link and network layers. Being independent of the underlying principle wireless access technology, both schemes can be easily implemented in heterogeneous networks. Performance evaluation results demonstrate the advantages of the proposed schemes over the standard protocols regarding prediction accuracy, time latency and energy savingsEVRY-INT (912282302) / SudocSudocFranceF

Context-aware Self-Optimization in Small-Cell Networks

Most mobile communications take place at indoor environments, especially in commercial and corporate scenarios. These places normally present coverage and capacity issues due to the poor signal quality, which degrade the end-user Quality of Experience (QoE). In these cases, mobile operators are offering small cells to overcome the indoor issues, being femtocells the main deployed base stations. Femtocell networks provide significant benefits to mobile operators and their clients. However, the massive integration and the particularities of femtocells, make the maintenance of these infrastructures a challenge for engineers. In this sense, Self-Organizing Networks (SON) techniques play an important role. These techniques are a key feature to intelligently automate network operation, administration and management procedures. SON mechanisms are based on the analysis of the mobile network alarms, counters and indicators. In parallel, electronics, sensors and software applications evolve rapidly and are everywhere. Thanks to this, valuable context information can be gathered, which properly managed can improve SON techniques performance. Within possible context data, one of the most active topics is the indoor positioning due to the immediate interest on indoor location-based services (LBS). At indoor commercial and corporate environments, user densities and traffic vary in spatial and temporal domain. These situations lead to degrade cellular network performance, being temporary traffic fluctuations and focused congestions one of the most common issues. Load balancing techniques, which have been identified as a use case in self-optimization paradigm for Long Term Evolution (LTE), can alleviate these congestion problems. This use case has been widely studied in macrocellular networks and outdoor scenarios. However, the particularities of femtocells, the characteristics of indoor scenarios and the influence of users’ mobility pattern justify the development of new solutions. The goal of this PhD thesis is to design and develop novel and automatic solutions for temporary traffic fluctuations and focused network congestion issues in commercial and corporate femtocell environments. For that purpose, the implementation of an efficient management architecture to integrate context data into the mobile network and SON mechanisms is required. Afterwards, an accurate indoor positioning system is developed, as a possible inexpensive solution for context-aware SON. Finally, advanced self-optimization methods to shift users from overloaded cells to other cells with spare resources are designed. These methods tune femtocell configuration parameters based on network information, such as ratio of active users, and context information, such as users’ position. All these methods are evaluated in both a dynamic LTE system-level simulator and in a field-trial

Evaluating Filtering Strategies for Decentralized Handover Prediction in the Wireless Internet

The rapid diffusion of heterogeneous forms of wireless connectivity is pushing the tremendous growth of the commercial interest in mobile services, i.e., distributed applications to portable wireless terminals that roam during service provisioning. In the case of both location-dependent mobile services and mobile services with session continuity requirements, there is a growing need for decentralized and lightweight solutions to predict cell handovers, in order to enable proactive service management operations that anticipate actual terminal reconnections at their newly visited cells. The paper discusses how to predict client handovers between IEEE 802.11 cells in a portable and completely decentralized way, only by exploiting RSSI monitoring and with no need of external global positioning systems. In particular, the paper focuses on proposing and comparing different filtering techniques for mitigating Received Signal Strength Indication abrupt fluctuations. Experimental results point out that i) filtering techniques can relevantly improve the efficiency and effectiveness of handover prediction, and ii) the choice of the most appropriate filtering solution to adopt should be made at provisioning time depending on specific service/system requirements, e.g., privileging minimum overhead vs. greater prediction proactivity

Metoda za določanje položaja v prostoru na osnovi signalov WiFi in modela zgradbe

WiFi indoor localization is a difficult task due to the variability of the WiFi signal. Consequently, there have been many attempts to develop WiFi-based methods which were aided by some other means to provide accurate indoor localization. Technologies like dead reckoning and IMU sensors, crowd utilization and pattern matching, specialized Li-Fi hardware and directional antennas, etc. were used to aid the WiFi in order to develop more accurate and stable methods. The main disadvantage of such methods lies in difficult deployments due to technologies and requirements: Dead-reckoning-aided methods are not suitable for stationary objects, methods leveraging groups of people and many individuals are not best suited for home environment, Li-Fi assisted methods require mobile terminals to provide Li-Fi connectivity and therefore rule out mobile phones as the most common terminal. In the past, many fingerprinting methods were proposedthese require a survey in the area of localization during the setup phase. Unfortunately, the majority of fingerprinting-based methods do not address issues of long-term stability of the WiFi signals. Thus, they face accuracy issues a few days after the calibrationfrequent, costly and time-consuming recalibration procedures are used to address these issues. Model-based methods try to eliminate calibration procedures by simulating signal propagation. Many of the methods assume at least some parameters of propagation as fixed and therefore poorly address the issues of WiFi’s variability and long-term stability. A pure WiFi model-based method that successfully addresses these issues and requires a mobile terminal only for emitting or receiving the WiFi signals is the ultimate goal of the WiFi indoor localization. This thesis presents a novel indoor localization method, with the main intent of addressing the issues of real-world applicability. Therefore, we focused on developing a method with accuracy comparable to the state-of-the-art methods, while reducing the complexity of deployment and minimizing the required maintenance for long-term deployments. The presented method is a model-based method, implementing self-adaptive operability, i.e. it does not require any human intervention. The thesis discusses in detail the topics of the long-term stability of the WiFi signal, receiving vs. transmitting methods, the future WiFi standards, comparability of the methods and architectural aspects with respect to real-world applicability of the localization methods. Our presented method estimates the parameters of signal propagation, by knowing the positions of the access points, the architectural floor plan with the dividing walls and by monitoring power of the packets travelling between the access points. From this data propagation parameters defined in propagation model are inferred in an online manner. A device trying to define its position captures power information of the packets sent by the access points. Devices’ information on the observed power is used to determine its position by an algorithm run on the localization server. The presented WiFi method is primarily developed and evaluated in single- and multi-room office environments. The method’s ability to be easily applicable in any environment is emphasized by its evaluation in two different environments – office and residential. Between the two, no parameters were modified, thus evaluations indicate universality of the method. Furthermore, we provide evaluation also in narrow hallway because in the field of indoor localization such evaluation environments are common practice. During the evaluation of our proposed method in the office environment, we obtained an average error of 2.63 m and 3.22 m for the single- and multi-room environments respectively. Second evaluation was performed in the residential environment, for which the method or any of the parameters were not modified. Our method achieved an average evaluation error of 2.65 m with standard deviation of 1.51 m, during the four independent evaluations, each consisting of 17 localization points. High accuracy of localization, with acknowledgement to the intricate and realistic multi-room floor plan with different types of walls, realistic furniture and real-world signal interference from the neighboring apartments, proves the method’s applicability to the real-world environment. Evaluation accuracy can be compared to the state-of-the-art methods, while our easily-applicable method requires far less complicated setup procedures and/or hardware requirements. In the second part of the thesis, we generalize the WiFi method to be applicable to the frequencies other than 2.4 GHz WiFi. By defining a fusion algorithm which considers accuracy of the individual frequencies, we have defined the MFAM method: Multiple Frequency Adaptive Model-Based Indoor Localization Method. The MFAM is one of the first purely model-based approaches capable of utilizing multiple frequencies simultaneously. The MFAM method was evaluated in residential environment on two frequency bands: 868 MHz and 2.4 GHz. The method retained positive properties of our WiFi approach (e.g. pure model-based, self-adaptive operability, wide applicability on affordable hardware), while improving the accuracy due to multi-frequency fusion. The usage of multiple frequencies improved the average error of localization from 2.65 m, while using only the WiFi, down to 2.16 m, in the case of multi-frequency fusion, thus improving localization accuracy for 18%. Similar improvements were observed also for the standard deviation. Although the accuracy of the presented WiFi and MFAM methods is comparable if not better than the state-of-the-art methods, one of the most important achievements of our work is the applicability of the method to the real-world situations and its long-term stability. The definition of our method ensures that the accuracy of the method will be the same at the time it is initialized, as well as days later, without any human interaction.Določanje lokacije znotraj prostorov na podlagi WiFi signalov je zaradi variabilnosti signala WiFi težka naloga. Posledično je bilo v preteklosti veliko poizkusov razvoja WiFi metod, ki uporabljajo dodatne informacije za natančno lokalizacijo. Ocena prehojene poti in inercijski senzorji, uporaba množice ljudi in ujemanje vzorcev, tehnologija Li-Fi in usmerjene antene itd. je le nekaj v preteklosti uporabljenih načinov za dopolnitev WiFi signalov pri razvoju natančnih in stabilnih metod. Glavna slabost takih metod se kaže v zahtevnem uvajanju zaradi uporabljenih tehnologij in zahtev: metode ocene prehojene poti niso primerne za stacionarne predmete, metode, ki uporabljajo množice ljudi, niso primerne za domače okolje, Li-Fi metode zahtevajo, da so mobilni terminali opremljeni z ustreznimi sprejemniki in tako izključijo mobilne telefone kot terminale. V preteklosti so bile predlagane številne metode, ki bazirajo na prstnih odtisih signalov. Te metode zahtevajo kalibracijske meritve v prostoru v fazi implementacije metode. Večina teh metod ne naslovi vprašanj dolgoročne stabilnosti WiFi signalov, posledično se soočajo s težavami zaradi natančnosti nekaj dni po kalibraciji. Pogoste, drage in časovno potratne ponovne kalibracije so potrebne za reševanje teh težav. Metode, temelječe na matematičnih modelih, poskušajo eliminirati kalibracijske postopke s simulacijo širjenja signala. Večina teh metod vseeno privzame vsaj nekatere parametre propagacije kot fiksne in tako slabo naslovi variabilnost WiFi signalov in dolgoročno stabilnost. Izključno WiFi modelna metoda, ki uspešno naslovi te težave in zahteva, da mobilni terminal samo oddaja ali sprejema WiFi signale, je končni cilj WiFi metod za določanje položaja v zaprtih prostorih. Ta doktorska dizertacija predstavlja novo metodo za določanje pozicije znotraj prostorov, z glavnim ciljem, da naslovi težave pri realni uporabi. Zato smo se osredotočili na razvoj metode z natančnostjo, ki je primerljiva z najsodobnejšimi metodami, hkrati pa je cilj zmanjšati kompleksnost implementacije in vzdrževanje za dolgoročno uporabnost. Predstavljena metoda je modelnega tipa in implementira prilagodljivo delovanje, zato ne zahteva nobenega človeškega posredovanja. Dizertacija podrobno razpravlja o temah dolgoročne stabilnosti WiFi signalov, o metodah, temelječih na sprejemanju in oddajanju signalov, prihodnjih standardih WiFi, primerljivosti sorodnih metod in arhitekturnih vplivih z ozirom na realno uporabnost. Naša metoda predstavljena v tej nalogi oceni prametre propagacije signala iz poznavanja pozicije dostopnih točk, arhitekturnega načrta z informacijami o predelnih stenah in s pomočjo opazovanja moči paketov, ki potujejo med dostopnimi točkami. Iz teh podatkov se propagacijski parametri definirani v modelu določijo v realnem času. Naprava, ki želi določiti pozicijo zajame informacijo o moči paketov, ki jih pošiljajo dostopne točke. Te meritve so uporabljene v algoritmu za določanje pozicije naprave, ki teče na strežniku. Predstavljena metoda je bila primarno razvita in evalvirana v enosobni in večsobni postavitvi pisarniškega okolja. Sposobnost metode, da se enostavno prilagodi vsakemu okolju, je poudarjena z evalvacijo v dveh okoljih – pisarniškem in stanovanjskem. Med obema evalvacijama nismo spremenili nobenega parametra metode, kar indicira njeno univerzalnost. V nadaljevanju predstavimo tudi evalvacijo metode v dolgem hodniku, ker je v raziskovalnem področju lokalizacije znotraj prostorov tako okolje pogosto uporabljeno. Evalvacija predlagane metode v pisarniškem okolju je rezultirala v povprečni napaki 2,63 m in 3,22 m za enosobno in večsobno postavitev. Druga evalvacija je bila opravljena v stanovanjskem okolju, za katerega nismo spreminjali metode ali njenih parametrov. Naša metoda je tekom evalvacije štirih neodvisnih setov meritev, od katerih je vsak sestavljen iz 17 lokalizacijskih točk, dosegla povprečno napako lokalizacije 2,65 m s standardno deviacijo 1,51 m. Visoka natančnost lokalizacije ob upoštevanju zapletenega in realističnega večsobnega tlorisa, ki vsebuje več vrst sten, realistično pohištvo in motnje signalov iz sosednjih stanovanj, dokazuje uporabnost metode v praksi. Natančnost je primerljiva z najsodobnejšimi metodami, medtem ko naša metoda zahteva veliko manj zapletene postopke namestitve in/ali strojne zahteve. V drugem delu teze posplošimo WiFi metodo, da lahko uporablja tudi druge frekvence poleg 2,4 GHz WiFi. Z definicijo fuzijskega algoritma, ki upošteva natančnost posameznih frekvenc, smo definirali MFAM metodo – večfrekvenčno prilagodljivo modelno metodo za določanje lokacije znotraj stavb (ang. multiple frequency adaptive model-based indoor localization method). MFAM metoda predstavlja eno prvih modelnih metod, ki lahko hkrati uporablja več frekvenc. MFAM metoda je bila evalvirana v stanovanjskem okolju na dveh frekvenčnih pasovih: 868 MHz in 2,4 GHz. Metoda je ohranila pozitivne lastnosti predlagane WiFi metode (tj. izključno modelni pristop, prilagodljivo delovanje, možnost široke uporabe na dosegljivi strojni opremi), hkrati pa rezultira v boljši natančnosti zaradi fuzije signalov več frekvenc. Uporaba več frekvenc je izboljšala povprečno napako iz 2,65 m pri uporabi WiFi na 2,16 m, s čimer se izboljša natančnost lokalizacije za 18%podobne izboljšave smo opazili tudi pri standardnemu odklonu. Čeprav je natančnost predstavljenih WiFi in MFAM metod primerljiva, če ne boljša, kot trenutno najsodobnejše metode, je eden najpomembnejših dosežkov našega dela uporabnost metode v realnih situacijah in njena dolgoročna stabilnost. Definicija naše metode zagotavlja, da bo natančnost metode ob času postavitve enaka kot dneve kasneje brez človeške interakcije