Spatial consistency of 3D channel models

Abweichender Titel nach Übersetzung der Verfasserin/des VerfassersZusammenfassung in deutscher SpracheDie Entwicklung realistischer Kanalmodelle ist eine der größten Herausforderungen für die Beschreibung der drahtlosen Kommunikation. Ihre Qualität ist entscheidend für die genaue Vorhersage der Leistungsfähigkeit eines drahtlosen Systems. Einerseits müssen die Kanalmodelle die physikalischen Eigenschaften der Wellenausbreitung genau beschreiben, andererseits müssen sie so unkompliziert wie möglich sein. Mit dem jüngsten Aufkommen von Antennen mit einer großen Anzahl von Elementen als vielversprechende Technologie zur weiteren Verbesserung der spektralen Effizienz werden neue Kanalmodelle erforderlich, die die Ausbreitungsumgebung sowohl im Azimut als auch in die Elevation charakterisieren. Da Standardisierungsgremien wie 3rd Generation Partnership Project (3GPP) und International Telecommunications Unit (ITU) ein 3-dimensional (3D) geometriebasiertes stochastisches Kanalmodell eingeführt haben, fehlt eine "System-Level" Modellierung, um weitere Analysen und Bewertungen durchführen zu können. Darüber hinaus ist es bei einer solchen Kanalcharakterisierung, bei der Geometrie und Statistik gemeinsam kombiniert werden, entscheidend, dass die räumliche Konsistenz in das Modell einbezogen wird. Angesichts der Herausforderung, dass die Kanalparameter sowohl orts- als auch zeitabhängig sind, sowie der fehlenden räumlichen Konsistenz, präsentiert diese Dissertation ein "System-Level" Framework und das Design der 3D geometriebasierten stochastischen Kanalmodelle, die mit räumlichen Konsistenz erweitert sind. Im ersten Teil dieser Dissertation wird das Design von 3D geometry-based stochastic channel models (GSCMs) auf einem vorhandenen Tool auf "System-Level" behandelt. Der Schwerpunkt liegt auf der Modellierung von Aspekten des orts- und zeitabhängigen großräumiges und kleinräumiges Fading, eine Herausforderung für die ohnehin komplexe Struktur auf "System-level" Tools. Es wird ein neuartiges Design für die räumliche Granularität und Zeitlinienstruktur von Simulationstool vorgeschlagen, das die Komplexität der Simulation verringert und die Erzeugung der Kanalimpulsantwort zur Laufzeit ermöglicht. Darüber hinaus erleichtert das vorgeschlagene Design die Schlüsselfunktionalität der drahtlosen Kommunikationen, die Mobilität des Benutzers und eine zeitliche Entwicklung der Kanalimpulsantwort, während der Benutzer in Bewegung ist. Es wird gezeigt, dass diese Struktur ein Schlüsselelement bei der Gestaltung des Designs der System-Level Tools für die kommente fünfte Generation (5G) und darüber hinaus. Die Modellierung der räumlichen Konsistenz wird im zweiten Teil dieser Dissertation diskutiert. Es werden zwei neue Modelle vorgeschlagen: Das erste erstellt räumliche Korrelationseigenschaften zwischen Ausbreitungsbedingungen wie line of sight (LOS), non line of sight (NLOS), drinnen und draußen basierend auf 2-dimensional (2D) räumlicher Filterung. Des Weiteren wird gezeigt, dass dieses Modell ein realistisches Verhalten liefert, das die Auswirkungen von Abschattungen in 3D nachahmt. Das zweite Modell führt ein räumlich gleichmäßiges kleinräumiges Fading ein. Eine Korrelation zwischen Zufallsvariablen wird vorgeschlagen, basierend auf einer bestimmten Auflösung, sogenannte Dekorrelationsentfernung, die den Bereich angibt, in dem Zufallsvariablen unabhängig sind. Darüber hinaus wird das Modell durch Vergleich mit statistischen Maßen validiert, die aus umfangreichen Ray-Tracing Simulationen extrahiert wurden. Das vorgeschlagene Modell stimmt sehr gut mit den statistischen Kanaleigenschaften überein, die durch Ray-Tracing erhalten wurden. Am Ende wird das vorgeschlagene Modell parametrisiert und anhand von Hypothesentests die Dekorrelationsentfernungswerte für verschiedene Szenarien ermittelt.Developing realistic channel models is one of the greatest challenges for describing wireless communications. Their quality is crucial for accurately predicting the performance of a wireless system. While on the one hand, channel models have to be accurate in describing the physical properties of wave propagation, on the other hand, they have to be as least complex as possible. With the recent emergence of antennas with a massive amount of elements as a promising technology for a further enhancement of spectral efficiency, new channel models that characterize the propagation environment in both azimuth and elevation become necessary. While standardization bodies such as 3rd Generation Partnership Project (3GPP) and International Telecommunications Unit (ITU) have introduced a 3-dimensional (3D) geometry-based stochastic channel model, a system-level modeling has been missing to serve the purpose of further analysis and evaluations. Furthermore, with such a channel characterization, where both geometry and statistics are jointly combined, it is crucial that spatial consistency is included in the model. Facing the challenge of channel parameters being both position- and time-dependent, as well as the lack of spatial consistency, this dissertation presents a system-level framework and design of the 3D geometry-based stochastic channel models enhanced with spatial consistency. In the first part of this dissertation, the design of the 3D geometry-based stochastic channel models (GSCMs) on an existing system-level tool is considered. The focus is put on modeling aspects of large-scale and small-scale fading being both position- and time-dependent, a challenge for the already complex structure of system-level tools. A novel design is proposed for spatial granularity and time line structure of simulation tools that reduces the simulation complexity and enables the generation of the channel impulse response at runtime. Furthermore, the proposed design facilitates the key functionality of wireless communications, mobility of the user and a time evolution of the channel impulse response while the user is on the move. It is shown that this structure is a key element in shaping the design of the upcoming fifth generation (5G) and beyond system-level tools. Modeling of the spatial consistency is discussed in the second part of this dissertation. Two novel models are proposed: The first one establishes spatial correlation properties among propagation conditions such as line of sight (LOS), non line of sight (NLOS), indoors and outdoors based on 2- dimensional spatial filtering. Further it is shown that this model yields a realistic behavior mimicking the effects of blockages in 3D. The second model introduces spatially consistent small-scale fading. A correlation among random variables is proposed based on a specific resolution, namely the decorrelation distance, that indicates the range in which random variables are independent. Further, the model is validated by comparing to statistical measures extracted from extensive ray-tracing simulations. The proposed model is in a very good agreement with statistical channel properties obtained from ray-tracing. At the end, the proposed model is parametrized, and based on hypothesis testing the de-correlation distance values for various scenarios are determined.11

A Spatial Consistency Model for Geometry-Based Stochastic Channels

Antennas with a massive amount of elements at one end are among 5G mobile communication key technologies for which spectral efficiency is enhanced by serving many users in parallel over tailored minimally interfering beams. This requires channel models that characterize the propagation environment in both azimuth and elevation. Additionally, the channel model has to capture spatial correlation effects among closely located positions, knowing that the propagation characteristics change gradually over the network area. In order to simulate mobile users or advanced beamforming strategies based on user location or angular information, it is crucial that spatial consistency is included in the applied channel models. This paper introduces a novel model for spatial consistency that is applicable to all prevalent geometry-based stochastic channel models. We provide a detailed explanation of the model and analyze its statistical properties and show its behavior when applied to the 3GPP 3D channel model as an example. To validate our model, we perform extensive ray-tracing simulations and show that our model is in a very good agreement with the statistical channel properties from ray-tracing. Following hypothesis testing over obtained ray-tracing statistics, we are able to parametrize our model for various 3GPP scenarios under LOS and NLOS propagation conditions. Finally, complementary aspects such as simulation complexity are discussed and a guideline on model implementation is provided.Austrian Federal Ministry for Digital and Economic AffairsNational Foundation for Research, Technology and DevelopmentTU Wien Bibliothe

A spatially consistent MIMO channel model with adjustable K factor

In the area of research on massive multiple-input multiple-output (MIMO), two assumptions on the wireless channel dominate channel modeling. Either, a rich scattering environment is assumed and the channel is modeled as i.i.d. Rayleigh fading, or, a line of sight (LOS) channel is assumed, enabling geometric channel modeling under a farfield assumption. However, either of these assumptions represents an extreme case that is unlikely to be observed in practice. While there is a variety of MIMO channel models in literature, most of them, and even very popular geometry based stochastic channel models, are not spatially consistent. This is especially problematic for technologies in which channel correlation of adjacent users is an important factor, such as massive MIMO. In this work, we introduce a simple but spatially consistent MIMO channel model based on multiple scattering theory. Our proposed channel model allows to adjust the Rician K factor by controlling the number and strength of scattering elements. This allows to perform spatially consistent simulations of wireless communications systems for a large range of scattering environments in between an i.i.d. Rayleigh fading assumption and pure LOS channels. A statistical analysis in terms of the Rician K factor for the introduced model is provided and verified by simulations. By comparison to other channel models, we show that non spatially consistent channel models lead to an underestimation of inter-user correlation and therefore to an overestimation of achievable sum rate

Flexible multi-node simulation of cellular mobile communications: the Vienna 5G System Level Simulator

Abstract The investigation and prediction of new trends and technologies for mobile cellular networks is of utmost importance for researchers and network providers to quickly identify promising developments. With the verge of the fifth generation of mobile communications (5G), networks become more and more heterogeneous and dynamic while the amount of active users within a cell keeps ever increasing. Therefore, the search for more efficient network layouts and configurations attracts massive attention while on the other hand becomes more and more complex. In this contribution, we present the Vienna 5G system level simulator, which allows to perform numerical performance evaluation of large-scale multi-tier networks, with numerous types of network nodes. The simulator is based on Matlab and is implemented in a modular fashion, to conveniently investigate arbitrary network and parameter constellations, which can be enhanced effortlessly. We first discuss the distinguishing aspects of our simulator platform, describe its structure, and then showcase its functionality by demonstrating the key aspects in more detail