Self-Organized Coverage and Capacity Optimization for Cellular Mobile Networks

Die zur Erfüllung der zu erwartenden Steigerungen übertragener Datenmengen notwendige größere Heterogenität und steigende Anzahl von Zellen werden in der Zukunft zu einer deutlich höheren Komplexität bei Planung und Optimierung von Funknetzen führen. Zusätzlich erfordern räumliche und zeitliche Änderungen der Lastverteilung eine dynamische Anpassung von Funkabdeckung und -kapazität (Coverage-Capacity-Optimization, CCO). Aktuelle Planungs- und Optimierungsverfahren sind hochgradig von menschlichem Einfluss abhängig, was sie zeitaufwändig und teuer macht. Aus diesen Grnden treffen Ansätze zur besseren Automatisierung des Netzwerkmanagements sowohl in der Industrie, als auch der Forschung auf groes Interesse.Selbstorganisationstechniken (SO) haben das Potential, viele der aktuell durch Menschen gesteuerten Abläufe zu automatisieren. Ihnen wird daher eine zentrale Rolle bei der Realisierung eines einfachen und effizienten Netzwerkmanagements zugeschrieben. Die vorliegende Arbeit befasst sich mit selbstorganisierter Optimierung von Abdeckung und Übertragungskapazität in Funkzellennetzwerken. Der Parameter der Wahl hierfür ist die Antennenneigung. Die zahlreichen vorhandenen Ansätze hierfür befassen sich mit dem Einsatz heuristischer Algorithmen in der Netzwerkplanung. Im Gegensatz dazu betrachtet diese Arbeit den verteilten Einsatz entsprechender Optimierungsverfahren in den betreffenden Netzwerkknoten. Durch diesen Ansatz können zentrale Fehlerquellen (Single Point of Failure) und Skalierbarkeitsprobleme in den kommenden heterogenen Netzwerken mit hoher Knotendichte vermieden werden.Diese Arbeit stellt einen "Fuzzy Q-Learning (FQL)"-basierten Ansatz vor, ein einfaches Maschinenlernverfahren mit einer effektiven Abstraktion kontinuierlicher Eingabeparameter. Das CCO-Problem wird als Multi-Agenten-Lernproblem modelliert, in dem jede Zelle versucht, ihre optimale Handlungsstrategie (d.h. die optimale Anpassung der Antennenneigung) zu lernen. Die entstehende Dynamik der Interaktion mehrerer Agenten macht die Fragestellung interessant. Die Arbeit betrachtet verschiedene Aspekte des Problems, wie beispielsweise den Unterschied zwischen egoistischen und kooperativen Lernverfahren, verteiltem und zentralisiertem Lernen, sowie die Auswirkungen einer gleichzeitigen Modifikation der Antennenneigung auf verschiedenen Knoten und deren Effekt auf die Lerneffizienz.Die Leistungsfähigkeit der betrachteten Verfahren wird mittels eine LTE-Systemsimulators evaluiert. Dabei werden sowohl gleichmäßig verteilte Zellen, als auch Zellen ungleicher Größe betrachtet. Die entwickelten Ansätze werden mit bekannten Lösungen aus der Literatur verglichen. Die Ergebnisse zeigen, dass die vorgeschlagenen Lösungen effektiv auf Änderungen im Netzwerk und der Umgebung reagieren können. Zellen stellen sich selbsttätig schnell auf Ausfälle und Inbetriebnahmen benachbarter Systeme ein und passen ihre Antennenneigung geeignet an um die Gesamtleistung des Netzes zu verbessern. Die vorgestellten Lernverfahren erreichen eine bis zu 30 Prozent verbesserte Leistung als bereits bekannte Ansätze. Die Verbesserungen steigen mit der Netzwerkgröße.The challenging task of cellular network planning and optimization will become more and more complex because of the expected heterogeneity and enormous number of cells required to meet the traffic demands of coming years. Moreover, the spatio-temporal variations in the traffic patterns of cellular networks require their coverage and capacity to be adapted dynamically. The current network planning and optimization procedures are highly manual, which makes them very time consuming and resource inefficient. For these reasons, there is a strong interest in industry and academics alike to enhance the degree of automation in network management. Especially, the idea of Self-Organization (SO) is seen as the key to simplified and efficient cellular network management by automating most of the current manual procedures. In this thesis, we study the self-organized coverage and capacity optimization of cellular mobile networks using antenna tilt adaptations. Although, this problem is widely studied in literature but most of the present work focuses on heuristic algorithms for network planning tool automation. In our study we want to minimize this reliance on these centralized tools and empower the network elements for their own optimization. This way we can avoid the single point of failure and scalability issues in the emerging heterogeneous and densely deployed networks.In this thesis, we focus on Fuzzy Q-Learning (FQL), a machine learning technique that provides a simple learning mechanism and an effective abstraction level for continuous domain variables. We model the coverage-capacity optimization as a multi-agent learning problem where each cell is trying to learn its optimal action policy i.e. the antenna tilt adjustments. The network dynamics and the behavior of multiple learning agents makes it a highly interesting problem. We look into different aspects of this problem like the effect of selfish learning vs. cooperative learning, distributed vs. centralized learning as well as the effect of simultaneous parallel antenna tilt adaptations by multiple agents and its effect on the learning efficiency.We evaluate the performance of the proposed learning schemes using a system level LTE simulator. We test our schemes in regular hexagonal cell deployment as well as in irregular cell deployment. We also compare our results to a relevant learning scheme from literature. The results show that the proposed learning schemes can effectively respond to the network and environmental dynamics in an autonomous way. The cells can quickly respond to the cell outages and deployments and can re-adjust their antenna tilts to improve the overall network performance. Additionally the proposed learning schemes can achieve up to 30 percent better performance than the available scheme from literature and these gains increases with the increasing network size

Optimizing Signal Behavior of Femtocells for Improved Network

The high demand for network coverage in an indoor setting brought about the acceptance of femtocell technology as a solution using the backhaul connectivity in the existing network. The quality of signal, voice calling, Internet, security and data are improved through the use femtocell at the indoor environment. Here the service provider attempts to reduce their operation cost by presenting self-organizing mechanisms for optimization of the network. The remarkable part is that, femtocells improves coverage, enhances the data rate at the indoor environment. Therefore, the challenges of the femtocell also known as interference deteriorates the capacity and quality performance of the whole cellular network. In this paper we simulate the bit error rate against signal behaviour at the indoor environment and we also simulate the transmitting power over signal for both macrocells and femtocells. We focus on the transmitting power that might cause interference within the cellular network

Radio network planning and optimisation for WCDMA

The present thesis introduces the radio network planning process and optimisation for WCDMA (FDD mode), as defined by 3GPP. This thesis consists of three parts: modelling and tools for radio network planning, process for pre-operational network control and optimisation for the operational network. General challenges to face in 3G network control are based on the fact that many issues are interconnected and should be simultaneously considered, such as Planning means not only to meet current status and demands, but the solution should also comply with the future requirements by providing an acceptable development path. Traffic modelling is not only the question about the total amount of traffic growth, but also the question about the future service distribution and performance demands. All CDMA systems have a relation between capacity and coverage. Consequently, the network planning itself is not only based on propagation estimation but also on the interference situation in the network. Ideally, site selection consideration will be done based on the network analysis with planned load and traffic/service portfolio, taking possible co-siting constraints into account. Provision of multiple services and seamless management of at least two multiple access systems require rapid evolution of the management tools and processes. The network performance in terms of capacity, quality, and implementation and operational costs forms a multidimensional space. Operators' task will be to convert the business strategy to an operating point in the performance space in a cost efficient manner. The contribution of this thesis in terms of modelling and tools is as follows: Improvement of the accuracy of radio link budget by introducing power control headroom (also called fast fading margin). Improvement of loading equation by introducing a transmit power increase term. Development of theory and modelling for a planning tool capable of multi-service and multi-carrier interference, capacity and coverage analysis. Development and implementation an interface taking into account the true traffic distribution (not uniform) and terminal speed. In the area of pre-operational planning process the contribution of this thesis is as follows: Development of dimensioning methodology for multi-service network site density estimation, utilising the modelling of power control headroom, transmit power increase, soft handover and Eb/N0. Development of radio network planning process for multi-service environment including capacity and coverage evaluation for a given traffic mixture, quality and area requirements. Analysis of means to improve radio network performance with Mast Head Amplifier (MHA), diversity reception, sectorisation and proper antenna selection. In the area of optimisation of the operational network the contribution of this thesis is as follows: Definition for optimisation target in the case of 3G. The optimisation will be capacity-quality trade-off management instead of plain quality improvement process. Introduction of Self Organizing Map (SOM) in the analysis of cellular networks. Analysis of the applicability of SOM in WCDMA cellular network optimisation. Introduction of SOM based applications to support network capacity-quality trade-off management. It is worth noting that process and methods described in this work are not limited to 3G systems with WCDMA radio access technology, but they are applicable to other CDMA standards as well.reviewe

Optimization of Mobility Parameters using Fuzzy Logic and Reinforcement Learning in Self-Organizing Networks

In this thesis, several optimization techniques for next-generation wireless networks are proposed to solve different problems in the field of Self-Organizing Networks and heterogeneous networks. The common basis of these problems is that network parameters are automatically tuned to deal with the specific problem. As the set of network parameters is extremely large, this work mainly focuses on parameters involved in mobility management. In addition, the proposed self-tuning schemes are based on Fuzzy Logic Controllers (FLC), whose potential lies in the capability to express the knowledge in a similar way to the human perception and reasoning. In addition, in those cases in which a mathematical approach has been required to optimize the behavior of the FLC, the selected solution has been Reinforcement Learning, since this methodology is especially appropriate for learning from interaction, which becomes essential in complex systems such as wireless networks. Taking this into account, firstly, a new Mobility Load Balancing (MLB) scheme is proposed to solve persistent congestion problems in next-generation wireless networks, in particular, due to an uneven spatial traffic distribution, which typically leads to an inefficient usage of resources. A key feature of the proposed algorithm is that not only the parameters are optimized, but also the parameter tuning strategy. Secondly, a novel MLB algorithm for enterprise femtocells scenarios is proposed. Such scenarios are characterized by the lack of a thorough deployment of these low-cost nodes, meaning that a more efficient use of radio resources can be achieved by applying effective MLB schemes. As in the previous problem, the optimization of the self-tuning process is also studied in this case. Thirdly, a new self-tuning algorithm for Mobility Robustness Optimization (MRO) is proposed. This study includes the impact of context factors such as the system load and user speed, as well as a proposal for coordination between the designed MLB and MRO functions. Fourthly, a novel self-tuning algorithm for Traffic Steering (TS) in heterogeneous networks is proposed. The main features of the proposed algorithm are the flexibility to support different operator policies and the adaptation capability to network variations. Finally, with the aim of validating the proposed techniques, a dynamic system-level simulator for Long-Term Evolution (LTE) networks has been designed

Modeling and design for future wireless cellular networks: coverage, rate, and security

Accompanied by the wide penetration of smartphones and other personal mobile devices in recent years, the foremost demand for cellular communications has been transformed from offering subscribers a way to communicate through low data rate voice call connections initially, into providing connectivity with good coverage, high data rate, as well as strong security for sensitive data transmission. To satisfy the demands for improved coverage and data rate, the cellular network is undergoing a significant transition from conventional macrocell-only deployment to heterogeneous network (HetNet), in which a multitude of radio access technologies can be co-deployed intelligently and flexibly. However, the small cells newly introduced in HetNet, such as picocells and femtocells, have complicated the network topology and the interference environment, thus presenting new challenges in network modeling and design. In recent studies, performance analyses were carried out accurately and tractably with the help of Poisson point process (PPP)-based base station (BS) model. This PPP-based model is extended in this work with the impact of directional antennas taken into account. The significance of this extension is emphasized by the wide usage of directional antennas in sectorized macrocell cells. Moreover, studies showed that little coverage improvement can be achieved if small cells are randomly deployed in a uniform-distributed way. This fact inspires us to explore the effect of the non-uniform BS deployment. We propose a non-uniform femtocell deployment scheme, in which femtocell BSs are not utilized if they are located close to any macrocell BSs. Based upon our analytical framework, this scheme can provide remarkable improvements on both coverage and data rate, thus stressing the importance of selectively deploying femtocell BSs by considering their relative locations with macrocell BSs. To alleviate the severe interference problem, the uplink attenuation technique is frequently employed in femtocell receivers to reduce the impact of interference from unattached terminals such that femtocell communication can take place. In order to analyze and optimize the femtocell system performance with this technique, we propose an analytical framework and demonstrate the performance tradeoff resulted from higher and lower uplink attenuation levels. Furthermore, we provide two improved uplink attenuation algorithms, which adaptively adjust to the information of the scheduled traffic, data rate requirement, and interference condition. Apart from the cellular coverage and data rate, communication security has been an important issue to be addressed due to the increasing demand for transmitting private and sensitive information over wireless networks. In the last part of the thesis, physical layer security, as a new way to improve wireless secrecy, is studied for cellular networks. By highlighting the unique cellular features offered by the carrier-operated high-speed backhaul, we investigate the probabilistic characterization of the secrecy rate, and identify the performance impacts of cell association and location information exchange between BSs. These results provide necessary network design guidelines for selecting the appropriate cell association method and information exchange range

Inter-RAT Mobility Robustness Optimization in Self-Organizing Networks

The massive growth in mobile data communication requires new more efficient Radio Access Technology (RAT) such as Long Term Evolution (LTE) being deployed on top of legacy mobile communication systems. Inter-RAT handovers are triggered either when the signal level of the serving RAT becomes weak while a sufficiently high signal level is measured from another RAT, or by traffic steering policies for balancing the load among different RATs, for example. Trouble-free operation of inter-RAT handovers requires an optimal setting of the handover parameters which is typically different for each cell and even location. Without knowing the detailed radio propagation conditions, directions and speeds of User Equipments (UEs), network planning can only provide a default setting which needs to be manually optimized during network operation with the aid of drive tests and expert knowledge. This manual optimization requires extensive human intervention which increases Operational Expenses (OPEX) of mobile operators and yields sub-optimal mobility performance due to limited means for more detailed root cause analysis. Therefore, automatic mechanisms have been requested by mobile operators to optimize the inter-RAT handover parameters. This optimization is known as inter-RAT Mobility Robustness Optimization (MRO) which is one of the use cases in Self-Organizing Network (SON). The technical complexities and requirements on MRO are too difficult to be tackled efficiently and properly by existing manual optimization methods. Considering that mobile networks consist of a high number of cells, the number of handover thresholds to be optimized in a network is significant. Moreover, the intricate dependencies and interactions among the handover thresholds of different neighboring cells make MRO problems even more challenging and complicated. Current optimization methods such as the local search method Simulated Annealing, for example, can be used offline in the network planning phase, however, they cannot be applied online in real-time networks to dynamically react on the changes in the environment and traffic. From that perspective, new optimization methods are needed to address the challenges and limitations imposed by MRO. In this thesis, several novel and feasible inter-RAT MRO methods have been proposed and analyzed. New key performance indicators which capture the different types of mobility failure events are proposed by the author of this thesis for the inter-RAT scenario. An inter-RAT handover is triggered by a dual-threshold measurement event where the first threshold corresponds to the serving cell and the second to the neighboring target cell of another RAT. This dual-threshold measurement event requires a more precise analysis of Too Late Handovers (TLHs). A TLH which is caused by the misconfigured serving cell threshold is distinguished from that which can be resolved by the target cell threshold. Thus, there are two types of TLHs in contrast to the intra-RAT case where a single type of TLH handover exists. Inter-RAT handover thresholds of currently standardized RATs are configured and optimized cell-specifically. That is, the same handover thresholds are applied by the UEs irrespective of the neighboring handover target cell. The limitations of a cell-specific optimization approach are analyzed and a new cell-group specific optimization approach where the handover thresholds are differentiated with respect to a group of neighboring target cells is proposed. For both cell-specific and cell-group specific optimization approaches, an automatic algorithm is developed to optimize the inter- RAT handover thresholds. In order to analyze the impact of Time-to-Trigger (TTT), which is a time interval affecting the triggering of handovers, the MRO algorithm is extended to allow a joint optimization of handover thresholds and TTT. Based on findings that even cell-group specific parameters cannot resolve all mobility failure events in some cells where radio conditions are not stationary along the cell border, a more advanced location-specific approach is proposed. Unlike cell-based optimization approaches, the handover thresholds are configured and optimized per cell-area and they can be differentiated with respect to neighboring target cells. Simulative investigations are carried out to evaluate the performance of the different optimization approaches. It has been shown that mobility failure events are rather located in specific cells. Accordingly, the same UEs are probably affected all the time by these mobility failures which leads to high user dissatisfaction. This clearly indicates the need of cell-specific handover thresholds to resolve the mobility problems in some cells. Moreover, it is shown that the optimization of target cell threshold in a cell-group specific manner yields an additional performance improvement compared to cell-specific optimization approach. The joint optimization approach of handover thresholds and TTT has shown advantages only when the handover thresholds are configured cell-specifically rather than cell-group specifically. The mobility failure events that are not resolved by cell-based optimization approaches are mitigated by cell-area based optimization approach. The investigations and concepts in this thesis have directly impacted 3rd Generation Partnership Project (3GPP) standard. Several contributions related to cell-specific and cell-group specific optimization approaches have been submitted and adopted by LTE Release (Rel.) 11 standard

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