A GPU-Based Parallel-Agent Optimization Approach for the Service Coverage Problem in UMTS Networks

In the context of coverage planning and control, the power of the common pilot channel signal determines the coverage area of a network cell. It also impacts the network capacity and thus the quality of service. We consider the problem of minimizing the total amount of pilot power subject to a full coverage constraint. Our optimization approach, based on parallel autonomous agents, gives very good solutions within an acceptable amount of time. The parallel implementation takes full advantage of GPU hardware in order to achieve impressive speed-up. We report the results of our experiments for three UMTS networks of different sizes based on a real network currently deployed in Slovenia

Cognition-Based Networks: A New Perspective on Network Optimization Using Learning and Distributed Intelligence

IEEE Access Volume 3, 2015, Article number 7217798, Pages 1512-1530 Open Access Cognition-based networks: A new perspective on network optimization using learning and distributed intelligence (Article) Zorzi, M.a , Zanella, A.a, Testolin, A.b, De Filippo De Grazia, M.b, Zorzi, M.bc a Department of Information Engineering, University of Padua, Padua, Italy b Department of General Psychology, University of Padua, Padua, Italy c IRCCS San Camillo Foundation, Venice-Lido, Italy View additional affiliations View references (107) Abstract In response to the new challenges in the design and operation of communication networks, and taking inspiration from how living beings deal with complexity and scalability, in this paper we introduce an innovative system concept called COgnition-BAsed NETworkS (COBANETS). The proposed approach develops around the systematic application of advanced machine learning techniques and, in particular, unsupervised deep learning and probabilistic generative models for system-wide learning, modeling, optimization, and data representation. Moreover, in COBANETS, we propose to combine this learning architecture with the emerging network virtualization paradigms, which make it possible to actuate automatic optimization and reconfiguration strategies at the system level, thus fully unleashing the potential of the learning approach. Compared with the past and current research efforts in this area, the technical approach outlined in this paper is deeply interdisciplinary and more comprehensive, calling for the synergic combination of expertise of computer scientists, communications and networking engineers, and cognitive scientists, with the ultimate aim of breaking new ground through a profound rethinking of how the modern understanding of cognition can be used in the management and optimization of telecommunication network

Recent Advances in Wireless Communications and Networks

This book focuses on the current hottest issues from the lowest layers to the upper layers of wireless communication networks and provides "real-time" research progress on these issues. The authors have made every effort to systematically organize the information on these topics to make it easily accessible to readers of any level. This book also maintains the balance between current research results and their theoretical support. In this book, a variety of novel techniques in wireless communications and networks are investigated. The authors attempt to present these topics in detail. Insightful and reader-friendly descriptions are presented to nourish readers of any level, from practicing and knowledgeable communication engineers to beginning or professional researchers. All interested readers can easily find noteworthy materials in much greater detail than in previous publications and in the references cited in these chapters

Thirty Years of Machine Learning: The Road to Pareto-Optimal Wireless Networks

Future wireless networks have a substantial potential in terms of supporting a broad range of complex compelling applications both in military and civilian fields, where the users are able to enjoy high-rate, low-latency, low-cost and reliable information services. Achieving this ambitious goal requires new radio techniques for adaptive learning and intelligent decision making because of the complex heterogeneous nature of the network structures and wireless services. Machine learning (ML) algorithms have great success in supporting big data analytics, efficient parameter estimation and interactive decision making. Hence, in this article, we review the thirty-year history of ML by elaborating on supervised learning, unsupervised learning, reinforcement learning and deep learning. Furthermore, we investigate their employment in the compelling applications of wireless networks, including heterogeneous networks (HetNets), cognitive radios (CR), Internet of things (IoT), machine to machine networks (M2M), and so on. This article aims for assisting the readers in clarifying the motivation and methodology of the various ML algorithms, so as to invoke them for hitherto unexplored services as well as scenarios of future wireless networks.Comment: 46 pages, 22 fig

Network reputation-based quality optimization of video delivery in heterogeneous wireless environments

The mass-market adoption of high-end mobile devices and increasing amount of video traffic has led the mobile operators to adopt various solutions to help them cope with the explosion of mobile broadband data traffic, while ensuring high Quality of Service (QoS) levels to their services. Deploying small-cell base stations within the existing macro-cellular networks and offloading traffic from the large macro-cells to the small cells is seen as a promising solution to increase capacity and improve network performance at low cost. Parallel use of diverse technologies is also employed. The result is a heterogeneous network environment (HetNets), part of the next generation network deployments. In this context, this thesis makes a step forward towards the “Always Best Experience” paradigm, which considers mobile users seamlessly roaming in the HetNets environment. Supporting ubiquitous connectivity and enabling very good quality of rich mobile services anywhere and anytime is highly challenging, mostly due to the heterogeneity of the selection criteria, such as: application requirements (e.g., voice, video, data, etc.); different device types and with various capabilities (e.g., smartphones, netbooks, laptops, etc.); multiple overlapping networks using diverse technologies (e.g., Wireless Local Area Networks (IEEE 802.11), Cellular Networks Long Term Evolution (LTE), etc.) and different user preferences. In fact, the mobile users are facing a complex decision when they need to dynamically select the best value network to connect to in order to get the “Always Best Experience”. This thesis presents three major contributions to solve the problem described above: 1) The Location-based Network Prediction mechanism in heterogeneous wireless networks (LNP) provides a shortlist of best available networks to the mobile user based on his location, history record and routing plan; 2) Reputation-oriented Access Network Selection mechanism (RANS) selects the best reputation network from the available networks for the mobile user based on the best trade-off between QoS, energy consumptions and monetary cost. The network reputation is defined based on previous user-network interaction, and consequent user experience with the network. 3) Network Reputation-based Quality Optimization of Video Delivery in heterogeneous networks (NRQOVD) makes use of a reputation mechanism to enhance the video content quality via multipath delivery or delivery adaptation

A Vision and Framework for the High Altitude Platform Station (HAPS) Networks of the Future

A High Altitude Platform Station (HAPS) is a network node that operates in the stratosphere at an of altitude around 20 km and is instrumental for providing communication services. Precipitated by technological innovations in the areas of autonomous avionics, array antennas, solar panel efficiency levels, and battery energy densities, and fueled by flourishing industry ecosystems, the HAPS has emerged as an indispensable component of next-generations of wireless networks. In this article, we provide a vision and framework for the HAPS networks of the future supported by a comprehensive and state-of-the-art literature review. We highlight the unrealized potential of HAPS systems and elaborate on their unique ability to serve metropolitan areas. The latest advancements and promising technologies in the HAPS energy and payload systems are discussed. The integration of the emerging Reconfigurable Smart Surface (RSS) technology in the communications payload of HAPS systems for providing a cost-effective deployment is proposed. A detailed overview of the radio resource management in HAPS systems is presented along with synergistic physical layer techniques, including Faster-Than-Nyquist (FTN) signaling. Numerous aspects of handoff management in HAPS systems are described. The notable contributions of Artificial Intelligence (AI) in HAPS, including machine learning in the design, topology management, handoff, and resource allocation aspects are emphasized. The extensive overview of the literature we provide is crucial for substantiating our vision that depicts the expected deployment opportunities and challenges in the next 10 years (next-generation networks), as well as in the subsequent 10 years (next-next-generation networks).Comment: To appear in IEEE Communications Surveys & Tutorial

Applications of Internet of Things

This book introduces the Special Issue entitled “Applications of Internet of Things”, of ISPRS International Journal of Geo-Information. Topics covered in this issue include three main parts: (I) intelligent transportation systems (ITSs), (II) location-based services (LBSs), and (III) sensing techniques and applications. Three papers on ITSs are as follows: (1) “Vehicle positioning and speed estimation based on cellular network signals for urban roads,” by Lai and Kuo; (2) “A method for traffic congestion clustering judgment based on grey relational analysis,” by Zhang et al.; and (3) “Smartphone-based pedestrian’s avoidance behavior recognition towards opportunistic road anomaly detection,” by Ishikawa and Fujinami. Three papers on LBSs are as follows: (1) “A high-efficiency method of mobile positioning based on commercial vehicle operation data,” by Chen et al.; (2) “Efficient location privacy-preserving k-anonymity method based on the credible chain,” by Wang et al.; and (3) “Proximity-based asynchronous messaging platform for location-based Internet of things service,” by Gon Jo et al. Two papers on sensing techniques and applications are as follows: (1) “Detection of electronic anklet wearers’ groupings throughout telematics monitoring,” by Machado et al.; and (2) “Camera coverage estimation based on multistage grid subdivision,” by Wang et al

Radio Communications

In the last decades the restless evolution of information and communication technologies (ICT) brought to a deep transformation of our habits. The growth of the Internet and the advances in hardware and software implementations modified our way to communicate and to share information. In this book, an overview of the major issues faced today by researchers in the field of radio communications is given through 35 high quality chapters written by specialists working in universities and research centers all over the world. Various aspects will be deeply discussed: channel modeling, beamforming, multiple antennas, cooperative networks, opportunistic scheduling, advanced admission control, handover management, systems performance assessment, routing issues in mobility conditions, localization, web security. Advanced techniques for the radio resource management will be discussed both in single and multiple radio technologies; either in infrastructure, mesh or ad hoc networks

Optimisation de la gestion des interférences inter-cellulaires et de l'attachement des mobiles dans les réseaux cellulaires LTE

Driven by an exponential growth in mobile broadband-enabled devices and a continue dincrease in individual data consumption, mobile data traffic has grown 4000-fold over the past 10 years and almost 400-million-fold over the past 15 years. Homogeneouscellular networks have been facing limitations to handle soaring mobile data traffic and to meet the growing end-user demand for more bandwidth and betterquality of experience. These limitations are mainly related to the available spectrumand the capacity of the network. Telecommunication industry has to address these challenges and meet exploding demand. At the same time, it has to guarantee a healthy economic model to reduce the carbon footprint which is caused by mobile communications.Heterogeneous Networks (HetNets), composed of macro base stations and low powerbase stations of different types, are seen as the key solution to improve spectral efficiency per unit area and to eliminate coverage holes. In such networks, intelligent user association and interference management schemes are needed to achieve gains in performance. Due to the large imbalance in transmission power between macroand small cells, user association based on strongest signal received is not adapted inHetNets as only few users would attach to low power nodes. A technique based onCell Individual Offset (CIO) is therefore required to perform load balancing and to favor some Small Cell (SC) attraction against Macro Cell (MC). This offset is addedto users’ Reference Signal Received Power (RSRP) measurements and hence inducing handover towards different eNodeBs. As Long Term Evolution (LTE) cellular networks use the same frequency sub-bands, mobile users may experience strong inter-cellxv interference, especially at cell edge. Therefore, there is a need to coordinate resource allocation among the cells and minimize inter-cell interference. To mitigate stronginter-cell interference, the resource, in time, frequency and power domain, should be allocated efficiently. A pattern for each dimension is computed to permit especially for cell edge users to benefit of higher throughput and quality of experience. The optimization of all these parameters can also offer gain in energy use. In this thesis,we propose a concrete versatile dynamic solution performing an optimization of user association and resource allocation in LTE cellular networks maximizing a certainnet work utility function that can be adequately chosen. Our solution, based on gametheory, permits to compute Cell Individual Offset and a pattern of power transmission over frequency and time domain for each cell. We present numerical simulations toillustrate the important performance gain brought by this optimization. We obtain significant benefits in the average throughput and also cell edge user through put of40% and 55% gains respectively. Furthermore, we also obtain a meaningful improvement in energy efficiency. This work addresses industrial research challenges and assuch, a prototype acting on emulated HetNets traffic has been implemented.Conduit par une croissance exponentielle dans les appareils mobiles et une augmentation continue de la consommation individuelle des données, le trafic de données mobiles a augmenté de 4000 fois au cours des 10 dernières années et près de 400millions fois au cours des 15 dernières années. Les réseaux cellulaires homogènes rencontrent de plus en plus de difficultés à gérer l’énorme trafic de données mobiles et à assurer un débit plus élevé et une meilleure qualité d’expérience pour les utilisateurs.Ces difficultés sont essentiellement liées au spectre disponible et à la capacité du réseau.L’industrie de télécommunication doit relever ces défis et en même temps doit garantir un modèle économique pour les opérateurs qui leur permettra de continuer à investir pour répondre à la demande croissante et réduire l’empreinte carbone due aux communications mobiles. Les réseaux cellulaires hétérogènes (HetNets), composés de stations de base macro et de différentes stations de base de faible puissance,sont considérés comme la solution clé pour améliorer l’efficacité spectrale par unité de surface et pour éliminer les trous de couverture. Dans de tels réseaux, il est primordial d’attacher intelligemment les utilisateurs aux stations de base et de bien gérer les interférences afin de gagner en performance. Comme la différence de puissance d’émission est importante entre les grandes et petites cellules, l’association habituelle des mobiles aux stations de bases en se basant sur le signal le plus fort, n’est plus adaptée dans les HetNets. Une technique basée sur des offsets individuelles par cellule Offset(CIO) est donc nécessaire afin d’équilibrer la charge entre les cellules et d’augmenter l’attraction des petites cellules (SC) par rapport aux cellules macro (MC). Cette offset est ajoutée à la valeur moyenne de la puissance reçue du signal de référence(RSRP) mesurée par le mobile et peut donc induire à un changement d’attachement vers différents eNodeB. Comme les stations de bases dans les réseaux cellulaires LTE utilisent les mêmes sous-bandes de fréquences, les mobiles peuvent connaître une forte interférence intercellulaire, en particulier en bordure de cellules. Par conséquent, il est primordial de coordonner l’allocation des ressources entre les cellules et de minimiser l’interférence entre les cellules. Pour atténuer la forte interférence intercellulaire, les ressources, en termes de temps, fréquence et puissance d’émission, devraient être alloués efficacement. Un modèle pour chaque dimension est calculé pour permettre en particulier aux utilisateurs en bordure de cellule de bénéficier d’un débit plus élevé et d’une meilleure qualité de l’expérience. L’optimisation de tous ces paramètres peut également offrir un gain en consommation d’énergie. Dans cette thèse, nous proposons une solution dynamique polyvalente effectuant une optimisation de l’attachement des mobiles aux stations de base et de l’allocation des ressources dans les réseaux cellulaires LTE maximisant une fonction d’utilité du réseau qui peut être choisie de manière adéquate.Notre solution, basée sur la théorie des jeux, permet de calculer les meilleures valeurs pour l’offset individuelle par cellule (CIO) et pour les niveaux de puissance à appliquer au niveau temporel et fréquentiel pour chaque cellule. Nous présentons des résultats des simulations effectuées pour illustrer le gain de performance important apporté par cette optimisation. Nous obtenons une significative hausse dans le débit moyen et le débit des utilisateurs en bordure de cellule avec 40 % et 55 % de gains respectivement. En outre, on obtient un gain important en énergie. Ce travail aborde des défis pour l’industrie des télécoms et en tant que tel, un prototype de l’optimiseur a été implémenté en se basant sur un trafic HetNets émulé

Serious Game Engineering and Lighting Models for the Realistic Emulation of 5G Systems

[ES] La quinta generación de comunicaciones móviles, 5G, promete ser una revolución tecnológica que vaya más allá de multiplicar la velocidad de transmisión de datos de sus predecesoras. Pretende soportar una gran cantidad de dispositivos y alcanzar latencias muy cercanas a 1 milisegundo. Para satisfacer estos ambiciosos requisitos, se han investigado nuevas tecnologías habilitadoras. Una de ellas es el uso de las bandas de ondas milimétricas (mmW) en las cuales hay una gran cantidad de espectro disponible. Para predecir las características del canal radio y evaluar las prestaciones de la 5G de forma fiable en las bandas mmW se requieren modelos de canal complejos. Concretamente, los modelos de propagación más precisos son los basados en trazado de rayos, pero su alto costo computacional los hacen inviables para la caracterización del canal radio en escenarios complejos. Por otro lado, en los últimos años, la tecnología de videojuegos ha desarrollado potentes herramientas para modelar la propagación de la luz en escenarios superrealistas. Dada la cercanía espectral entre el espectro visible y las ondas mmW, la presente Tesis ha estudiado la aplicación de las herramientas de modelado de propagación de la luz de los motores de juego para el modelado del canal radio en mmW. Esta Tesis propone un modelo de estimación de las pérdidas de propagación en mmW llamado "Modelo de Intensidad de Luz'' (LIM). Usando este modelo, basado en los procesos de iluminación realizados por los motores de juego, los transmisores de señal se sustituyen por focos de luz y la intensidad lumínica recibida en un punto se traduce a potencia de señal en milimétricas a través de una función polinómica sencilla. Una de las ventajas de usar los motores de juego es su gran capacidad y la facilidad que tiene el usuario para crear escenarios superrealistas que representen fielmente la geometría de escenarios donde se quiera evaluar el canal radio. De esta forma se pueden obtener estimaciones precisas de las pérdidas de propagación. La estimación de las pérdidas de propagación con LIM ha sido comparada con campañas de medida en las bandas de 28 GHz y 73 GHz y con otros modelos de propagación. Como resultado, el error de estimación de LIM es menor que los modelos estocásticos actuales y es comparable con el modelo de trazado de rayos. Y, además, el coste computacional de LIM comparado con el trazado de rayos es 130 veces menor, lo que posibilita el uso de LIM en escenarios altamente complejos para la estimación del canal radio en tiempo real. Los motores de juego permiten caracterizar de forma diferente la interacción de los materiales con la luz configurando el mapa de normales de sus superficies y sus funciones de dispersión y reflexión. En esta Tesis se ha determinado la caracterización de varios materiales que mejor se ajusta a medidas de laboratorio realizadas en un escenario controlado en la banda de 28 GHz. El modelo de LIM empleando materiales con esta caracterización óptima reduce más de un 50\% su error de estimación con respecto a la aplicación de LIM con los materiales por defecto, mientras que su coste computacional sigue siendo 26 veces menor que el modelo de trazado de rayos. Finalmente, se ha desarrollado sobre un motor de juego una primera versión de plataforma para la emulación de los sistemas 5G que es el punto de partida para un emulador completo de 5G. Esta plataforma no sólo contiene el modelo de LIM sino que incluye varios casos de uso de la 5G en entornos superrealistas. La plataforma, que se basa en el concepto de "Serious Game Engineering", rompe las limitaciones de los simuladores de redes móviles en cuanto a las capacidades de visualización e interacción del usuario con los componentes de la red en tiempo real.[CA] La cinquena generació de comunicacions mòbils, 5G, promet ser una revolució tecnològica que vaja més enllà de multiplicar la velocitat de transmissió de dades de les seues predecessores. Pretén suportar una gran quantitat de dispositius i aconseguir latències molt pròximes a 1 mil·lisegon. Per a satisfer aquests ambiciosos requisits, s'han investigat noves tecnologies habilitadores. Una d'elles és l'ús de les bandes d'ones mil·limètriques (mmW) en les quals hi ha una gran quantitat d'espectre disponible. Per a predir les característiques del canal ràdio i avaluar les prestacions de la 5G de forma fiable en les bandes mmW es requereixen models de canal complexos. Concretament, els models de propagació més precisos són els basats en traçat de rajos, però el seu alt cost computacional els fan inviables per a la caracterització del canal ràdio en escenaris complexos. D'altra banda, en els últims anys, la tecnologia de videojocs ha desenvolupat potents eines per a modelar la propagació de la llum en escenaris superrealistes. Donada la proximitat espectral entre l'espectre visible i les ones mmW, la present Tesi ha estudiat l'aplicació de les eines de modelatge de propagació de la llum dels motors de joc per al modelatge del canal radie en mmW. Aquesta Tesi proposa un model d'estimació de les pèrdues de propagació en mmW anomenat "Model d'Intensitat de Llum'' (LIM). Usant aquest model, basat en els processos d'il·luminació realitzats pels motors de joc, els transmissors de senyal se substitueixen per focus de llum i la intensitat lumínica rebuda en un punt es tradueix a potència de senyal en mil·limètriques a través d'una funció polinòmica senzilla. Una dels avantatges d'usar els motors de joc és la seua gran capacitat i la facilitat que té l'usuari per a crear escenaris superrealistes que representen fidelment la geometria d'escenaris on es vulga avaluar el canal ràdio. D'aquesta forma es poden obtindre estimacions precises de les pèrdues de propagació. L'estimació de les pèrdues de propagació amb LIM ha sigut comparada amb campanyes de mesura en les bandes de 28~GHz i 73~GHz i amb altres models de propagació. Com a resultat, l'error d'estimació de LIM és menor que els models estocàstics actuals i és comparable amb el model de traçat de rajos. I, a més, el cost computacional de LIM comparat amb el traçat de rajos és 130 vegades menor, la qual cosa possibilita l'ús de LIM en escenaris altament complexos per a l'estimació del canal ràdio en temps real. Els motors de joc permeten caracteritzar de forma diferent la interacció dels materials amb la llum configurant el mapa de normals de les seues superfícies i les seues funcions de dispersió i reflexió. En aquesta Tesi s'ha determinat la caracterització de diversos materials que s'ajusta millor a mesures de laboratori realitzades en un escenari controlat en la banda de 28 GHz. El model de LIM emprant materials amb aquesta caracterització òptima redueix més d'un 50 % el seu error d'estimació respecte a l'aplicació de LIM amb els materials per defecte, mentre que el seu cost computacional continua sent 26 vegades menor que el model de traçat de rajos. Finalment, s'ha desenvolupat sobre un motor de joc una primera versió de plataforma per a l'emulació dels sistemes 5G que és el punt de partida per a un emulador complet de 5G. Aquesta plataforma no solament conté el model de LIM sinó que inclou diversos casos d'ús de la 5G en entorns superrealistes. La plataforma, que es basa en el concepte de "Serious Game Engineering", trenca les limitacions dels simuladors de xarxes mòbils quant a les capacitats de visualització i interacció de l'usuari amb els components de la xarxa en temps real.[EN] The fifth generation of mobile communications, 5G, promises to be a technological revolution that goes beyond multiplying the data transmission speed of its predecessors. It aims to support a large number of devices and reach latencies very close to 1 millisecond. To meet these ambitious requirements, new enabling technologies have been researched. One of these is the use of millimetre-wave bands (mmW) in which a large amount of spectrum is available. Complex channel models are required to predict radio channel characteristics and reliably evaluate 5G performance in the mmW bands. Specifically, the most accurate propagation models are those based on ray tracing, but their high computational cost makes them unfeasible for radio channel characterization in complex scenarios. On the other hand, in recent years, video game technology has developed powerful tools to model the propagation of light in super realistic scenarios. Given the spectral closeness between the visible spectrum and the mmW waves, the present Thesis has studied the application of light propagation modeling tools from game engines for radio channel modeling in mmW. This Thesis proposes a model for estimating propagation losses in mmW called "Light Intensity Model'' (LIM). Using this model, based on the lighting processes performed by the game engines, the signal transmitters are replaced by light sources and the light intensity received at a point is translated into signal strength in mmW through a simple polynomial function. One of the advantages of using the game engines is their great capacity and the ease with which the user can create super realistic scenarios that faithfully represent the geometry of scenarios where the radio channel is to be evaluated. In this way, accurate estimates of propagation losses can be obtained. The estimation of propagation losses with LIM has been compared with measurement campaigns in the 28 GHz and 73 GHz bands and with other propagation models. As a result, the LIM estimation error is smaller than the current stochastic models and is comparable with the ray tracing model. In addition, the computational cost of LIM compared to ray tracing is 130 times lower, allowing the use of LIM in highly complex scenarios for real-time radio channel estimation. The game engines allow to characterize in a different way the interaction of the materials with the light configuring the normal map of their surfaces and their scattering and reflection functions. In this Thesis it has been determined the characterization of several materials that best fits to laboratory measurements made in a controlled scenario in the 28 GHz band. The LIM model using materials with this optimal characterization reduces by more than 50% its estimation error with respect to the application of LIM with default materials, while its computational cost remains 26 times lower than the ray tracing model. Finally, a first version of a platform for the emulation of 5G systems has been developed on a game engine, which is the starting point for a complete 5G emulator. This platform not only contains the LIM model but also includes several 5G use cases in super realistic environments. The platform, which is based on the concept of "`Serious Game Engineering", breaks the limitations of mobile network simulators in terms of visualization capabilities and user interaction with network components in real time.Inca Sánchez, SA. (2019). Serious Game Engineering and Lighting Models for the Realistic Emulation of 5G Systems [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/132695TESI