Directional propagation channel estimation and analysis in urban environment with panoramic photography

International audienceThis article aims to provide readers with a physical understanding of the propagation channel that is complementary to mathematical channel modeling. It presents an analysis of the directional propagation channel based on radiophotos. Radiophotos are graphical objects where directions of arrival are superimposed on three-dimensional (3D) panoramic photographs.The interaction between electro magnetic waves and the environment is immediately identified with these representations. This paper focuses on the direction of arrival at mobile in an urban macrocell environment. The first radiophoto collection illustrates the major propagation phenomena such as reflection, diffraction, or street canyoning. The second collection illustrates typical propagation channel profiles that are classified according to delay, azimuth, and elevation spread values. The paper also describes an original panorama-based method for estimating noise level in the azimuth–elevation domain

Correlation Properties of Large Scale Parameters from 2.66 GHz Multi-Site Macro Cell Measurements

Multi-site measurements for urban macro cells at 2.66 GHz are performed with three base stations and one mobile station. In order to analyze the correlation properties of large scale parameters, we split up the routes into subsets, where it can be assumed that wide-sense stationarity (WSS) applies. The autocorrelation distance and correlation properties of large scale parameters for each link are analyzed. By comparing these properties with the corresponding parameters from the COST 2100 and WINNER II models, we can see that the measured autocorrelation distance of the shadow fading as well the autocorrelation distance of delay spread have similar properties as in the two models. The shadow fading and delay spread from the same link are negatively correlated and match the two models well. Based on the WSS subsets, we can see that large scale parameters for different links can be correlated, also when two BSs are far away from each other. In those cases the correlation of different links tends to be positively correlated when both base stations are in the same direction compared to the movement of the MS, otherwise the two links are usually negatively correlated

Geometry-based Radio Channel Characterization and Modeling: Parameterization, Implementation and Validation

The propagation channel determines the fundamental basis of wireless communications, as well as the actual performance of practical systems. Therefore, having good channel models is a prerequisite for developing the next generation wireless systems. This thesis first investigates one of the main channel model building blocks, namely clusters. To understand the concept of clusters and channel characterization precisely, a measurement based ray launching tool has been implemented (Paper I). Clusters and their physical interpretation are studied by using the implemented ray launching tool (Paper II). Also, this thesis studies the COST 2100 channel model, which is a geometry-based channel model using the concept of clusters. A complete parameter set for the outdoor sub-urban scenario is extracted and validated for the COST 2100 channel model (Paper III). This thesis offers valuable insights on multi-link channel modeling, where it will be widely used in the next generation wireless systems (Paper IV and Paper V). In addition, positioning and localization by using the phase information of multi-path components, which are estimated and tracked from the radio channels, are investigated in this thesis (Paper VI). Clusters are extensively used in geometry-based stochastic channel models, such as the COST 2100 and WINNER II channel models. In order to gain a better understanding of the properties of clusters, thus the characteristics of wireless channels, a measurement based ray launching tool has been implemented for outdoor scenarios in Paper I. With this ray launching tool, we visualize the most likely propagation paths together with the measured channel and a detail floor plan of the measured environment. The measurement based ray launching tool offers valuable insights of the interacting physical scatterers of the propagation paths and provides a good interpretation of propagation paths. It shows significant advantages for further channel analysis and modeling, e.g., multi-link channel modeling. \par The properties of clusters depend on how clusters are identified. Generally speaking, there are two kinds of clusters: parameter based clusters are characterized with the parameters of the associated multi-path components; physical clusters are determined based on the interacting physical scatterers of the multi-path components. It is still an open issue on how the physical clusters behave compared to the parameter based clusters and therefore we analyze this in more detail in Paper II. In addition, based on the concept of physical clusters, we extract modeling parameters for the COST 2100 channel model with sub-urban and urban micro-cell measurements. Further, we validate these parameters with the current COST 2100 channel model MATLAB implementation. The COST 2100 channel model is one of the best candidates for the next generation wireless systems. Researchers have made efforts to extract the parameters in an indoor scenario, but the parameterization of outdoor scenarios is missing. Paper III fills this blank, where, first, cluster parameters and cluster time-variant properties are obtained from the 300~MHz measurements by using a joint clustering and tracking algorithm. Parameterization of the COST 2100 channel model for single-link outdoor MIMO communication at 300~MHz is conducted in Paper III. In addition, validation of the channel model is performed for the considered scenario by comparing simulated and measured delay spreads, spatial correlations, singular value distributions and antenna correlations. Channel modeling for multi-link MIMO systems plays an important role for the developing of the next generation wireless systems. In general, it is essential to capture the correlations between multi-link as well as their correlation statistics. In Paper IV, correlation between large-scale parameters for a macro cell scenario at 2.6 GHz has been analyzed. It has been found that the parameters of different links can be correlated even if the base stations are far away from each other. When both base stations were in the same direction compared to the movement, the large-scale parameters of the different links had a tendency to be positively correlated, but slightly negatively correlated when the base stations were located in different directions compared to the movement of the mobile terminal. Paper IV focuses more on multi-site investigations, and paper V gives valuable insights for multi-user scenarios. In the COST 2100 channel model, common clusters are proposed for multi-link channel modeling. Therefore, shared scatterers among the different links are investigated in paper V, which reflects the physical existence of common clusters. We observe that, as the MS separation distance is increasing, the number of common clusters is decreasing and the cross-correlation between multiple links is decreasing as well. Multi-link MIMO simulations are also performed using the COST 2100 channel model and the parameters of the extracted common clusters are detailed in paper V. It has been demonstrated that the common clusters can represent multi-link properties well with respect to inter-link correlation and sum rate capacity. Positioning has attracted a lot of attention both in the industry and academia during the past decades. In Paper VI, positioning with accuracy down to centimeters has been demonstrated, where the phase information of multi-path components from the measured channels is used. First of all, an extended Kalman filter is implemented to process the channel data, and the phases of a number of MPCs are tracked. The tracked phases are converted into relative distance measures. Position estimates are obtained with a method based on so called structure-of-motion. In Paper VI, circular movements have been successfully tracked with a root-mean-square error around 4 cm when using a bandwidth of 40 MHz. It has been demonstrated that phase based positioning is a promising technique for positioning with accuracy down to centimeters when using a standard cellular bandwidth. In summary, this thesis has made efforts for the implementation of the COST 2100 channel model, including providing model parameters and validating such parameters, investigating multi-link channel properties, and suggesting implementations of the channel model. The thesis also has made contributions to the tools and algorithms that can be used for general channel characterizations, i.e., clustering algorithm, ray launching tool, EKF algorithm. In addition, this thesis work is the first to propose a practical positioning method by utilizing the distance estimated from the phases of the tracked multi-path components and showed a preliminary and promising result

Quasi-deterministic channel modeling and experimental validation in cooperative and massive MIMO deployment topologies

Das enorme Wachstum des mobilen Datenaufkommens wird zu substantiellen Veränderungen in mobilen Netzwerken führen. Neue drahtlose Funksysteme müssen alle verfügbaren Freiheitsgrade des Übertragungskanals ausnutzen um die Kapazität zu maximieren. Dies beinhaltet die Nutzung größerer Bandbreiten, getrennter Übertragungskanäle, Antennenarrays, Polarisation und Kooperation zwischen Basisstationen. Dafür benötigt die Funkindustrie Kanalmodelle, welche das wirkliche Verhalten des Übertragungskanals in all diesen Fällen abbilden. Viele aktuelle Kanalmodelle unterstützen jedoch nur einen Teil der benötigten Funktionalität und wurden nicht ausreichend durch Messungen in relevanten Ausbreitungsszenarien validiert. Es ist somit unklar, ob die Kapazitätsvorhersagen, welche mit diesen Modellen gemacht werden, realistisch sind. In der vorliegenden Arbeit wird ein neuen Kanalmodell eingeführt, welches korrekte Ergebnisse für zwei wichtige Anwendungsfälle erzeugt: Massive MIMO und Joint-Transmission (JT) Coordinated Multi-Point (CoMP). Dafür wurde das häufig verwendete WINNER Kanalmodell um neue Funktionen erweitert. Dazu zählen 3-D Ausbreitungseffekte, sphärische Wellenausbreitung, räumliche Konsistenz, die zeitliche Entwicklung von Kanälen sowie ein neues Modell für die Polarisation. Das neue Kanalmodell wurde unter dem Akronym "QuaDRiGa" (Quasi Deterministic Radio Channel Generator, dt.: quasideterministischer Funkkanalgenerator) eingeführt. Um das Modell zu validieren wurden Messungen in Dresden und Berlin durchgeführt. Die Messdaten wurden zunächst verwendet um die Modellparameter abzuleiten. Danach wurden die Messkampagnen im Modell nachgestellt um die Reproduzierbarkeit der Ergebnisse nachzuweisen. Essentielle Leistungsindikatoren wie z.B. der Pfadverlust, die Laufzeitstreuung, die Winkelstreuung, der Geometriefaktor, die MIMO Kapazität und die Dirty-Paper-Coding Kapazität wurden für beide Datensätze berechnet. Diese wurden dann miteinander sowie mit Ergebnissen aus dem Rayleigh i.i.d. Modell und dem 3GPP-3D Kanalmodell verglichen. Für die Messungen in Dresden erzeugt das neue Modell nahezu identische Ergebnisse wenn die nachsimulierten Kanäle anstatt der Messdaten für die Bestimmung der Modellparameter verwendet werden. Solch ein direkter Vergleich war bisher nicht möglich, da die vorherigen Modelle keine ausreichend langen Kanalsequenzen erzeugen können. Die Kapazitätsvorhersagen des neuen Modells sind zu über 90% korrekt. Im Vergleich dazu konnte das 3GPP-3D Model nur etwa 80% Genauigkeit aufweisen. Diese Vorhersagen konnten auch für das Messszenario in Berlin gemacht werden, wo mehrere Basisstationen zeitgleich vermessen wurden. Dadurch konnten die gegenseitigen Störungen mit in die Bewertung eingeschlossen werden. Die Ergebnisse bestätigen die generelle Annahme, dass es möglich ist den Ausbreitungskanal sequenziell für einzelne Basisstationen zu vermessen und danach Kapazitätsvorhersagen für ganze Netzwerke mit der Hilfe von Modellen zu machen. Das neue Modell erzeugt Kanalkoeffizienten welche ähnliche Eigenschaften wie Messdaten haben. Somit können neue Algorithmen in Funksystemen schneller bewertet werden, da es nun möglich ist realistische Ergebnisse in einem frühen Entwicklungsstadium zu erhalten.The tremendous growth of mobile data traffic will lead to substantial architectural changes in wireless networks. New wireless systems need to exploit all available degrees of freedom in the wireless channel such as wider bandwidth, multi-carrier operation, large antenna arrays, polarization, and cooperation between base stations, in order to maximize the performance. The wireless industry needs channel models that reproduce the true behavior of the radio channel in all these use cases. However, many state-of-the-art models only support parts of the required functionality and have not been thoroughly validated against measurements in relevant propagations scenarios. It is therefore unclear if the performance predictions made by these models are realistic. This thesis introduces a new geometry-based stochastic channel model that creates accurate results for two important use cases: massive multiple-input multiple-output (MIMO) and joint transmission (JT) coordinated multi-point (CoMP). For this, the popular WINNER channel model was extended to incorporate 3-D propagation, spherical wave propagation, spatial consistency, temporal evolution of channels, and a new model for the polarization. This model was introduced under the acronym ``QuaDRiGa'' - quasi deterministic radio channel generator. To validate the model, measurements were done in downtown Dresden, Germany, and downtown Berlin, Germany. Those were used to derive the model parameters. Then, the measurements were resimulated with the new channel model and benchmarked against the Rayleigh i.i.d. model and the 3GPP-3D channel model. Essential performance indicators such as path gain, shadow fading, delay spread, angular spreads, geometry factor, single-link capacity, and the dirty-paper coding capacity were computed from both the measured and resimulated data. In Dresden, the resimulated channels produce almost identical results as the measured channels. When using the resimulated channels to derive the model parameters, the same results can be obtained as when using the measurement data. Such a direct comparison was not possible with the previous models because they cannot produce sufficiently long sequences of channel data. The performance predictions from the new model are more than 90% accurate whereas only 80% accuracy could be achieved with the 3GPP-3D model. In Berlin, accurate performance predictions could also be made in a multi-cellular environment where the mutual interference between the base stations could be studied. This confirms that it is generally sufficient to use single-link measurements to parameterize channel models that are then used to predict the achievable performance in wireless networks. The new model can generate channel traces with similar characteristics as measured data. This might speed up the evaluation of new algorithms because it is now possible to obtain realistic performance results already in an early stage of development

The characterisation and modelling of the wireless propagation channel in small cells scenarios

“A thesis submitted to the University of Bedfordshire, in partial fulfilment of the requirements for the degree of Doctor of Philosophy”.The rapid growth in wireless data traffic in recent years has placed a great strain on the wireless spectrum and the capacity of current wireless networks. In addition, the makeup of the typical wireless propagation environment is rapidly changing as a greater percentage of data traffic moves indoors, where the coverage of radio signals is poor. This dual fronted assault on coverage and capacity has meant that the tradition cellular model is no longer sustainable, as the gains from constructing new macrocells falls short of the increasing cost. The key emerging concept that can solve the aforementioned challenges is smaller base stations such as micro-, pico- and femto-cells collectively known as small cells. However with this solution come new challenges: while small cells are efficient at improving the indoor coverage and capacity; they compound the lack of spectrum even more and cause high levels of interference. Current channel models are not suited to characterise this interference as the small cells propagation environment is vast different. The result is that overall efficiency of the networks suffers. This thesis presents an investigation into the characteristics of the wireless propagation channel in small cell environments, including measurement, analysis, modelling, validation and extraction of channel data. Two comprehensive data collection campaigns were carried out, one of them employed a RUSK channel sounder and featured dual-polarised MIMO antennas. From the first dataset an empirical path loss model, adapted to typical indoor and outdoor scenarios found in small cell environments, was constructed using regression analysis and was validated using the second dataset. The model shows good accuracy for small cell environments and can be implemented in system level simulations quickly without much requirements

Cooperative Radio Communications for Green Smart Environments

The demand for mobile connectivity is continuously increasing, and by 2020 Mobile and Wireless Communications will serve not only very dense populations of mobile phones and nomadic computers, but also the expected multiplicity of devices and sensors located in machines, vehicles, health systems and city infrastructures. Future Mobile Networks are then faced with many new scenarios and use cases, which will load the networks with different data traffic patterns, in new or shared spectrum bands, creating new specific requirements. This book addresses both the techniques to model, analyse and optimise the radio links and transmission systems in such scenarios, together with the most advanced radio access, resource management and mobile networking technologies. This text summarises the work performed by more than 500 researchers from more than 120 institutions in Europe, America and Asia, from both academia and industries, within the framework of the COST IC1004 Action on "Cooperative Radio Communications for Green and Smart Environments". The book will have appeal to graduates and researchers in the Radio Communications area, and also to engineers working in the Wireless industry. Topics discussed in this book include: • Radio waves propagation phenomena in diverse urban, indoor, vehicular and body environments• Measurements, characterization, and modelling of radio channels beyond 4G networks• Key issues in Vehicle (V2X) communication• Wireless Body Area Networks, including specific Radio Channel Models for WBANs• Energy efficiency and resource management enhancements in Radio Access Networks• Definitions and models for the virtualised and cloud RAN architectures• Advances on feasible indoor localization and tracking techniques• Recent findings and innovations in antenna systems for communications• Physical Layer Network Coding for next generation wireless systems• Methods and techniques for MIMO Over the Air (OTA) testin

Cooperative Radio Communications for Green Smart Environments

The demand for mobile connectivity is continuously increasing, and by 2020 Mobile and Wireless Communications will serve not only very dense populations of mobile phones and nomadic computers, but also the expected multiplicity of devices and sensors located in machines, vehicles, health systems and city infrastructures. Future Mobile Networks are then faced with many new scenarios and use cases, which will load the networks with different data traffic patterns, in new or shared spectrum bands, creating new specific requirements. This book addresses both the techniques to model, analyse and optimise the radio links and transmission systems in such scenarios, together with the most advanced radio access, resource management and mobile networking technologies. This text summarises the work performed by more than 500 researchers from more than 120 institutions in Europe, America and Asia, from both academia and industries, within the framework of the COST IC1004 Action on "Cooperative Radio Communications for Green and Smart Environments". The book will have appeal to graduates and researchers in the Radio Communications area, and also to engineers working in the Wireless industry. Topics discussed in this book include: • Radio waves propagation phenomena in diverse urban, indoor, vehicular and body environments• Measurements, characterization, and modelling of radio channels beyond 4G networks• Key issues in Vehicle (V2X) communication• Wireless Body Area Networks, including specific Radio Channel Models for WBANs• Energy efficiency and resource management enhancements in Radio Access Networks• Definitions and models for the virtualised and cloud RAN architectures• Advances on feasible indoor localization and tracking techniques• Recent findings and innovations in antenna systems for communications• Physical Layer Network Coding for next generation wireless systems• Methods and techniques for MIMO Over the Air (OTA) testin

Analysis of the sum rate for massive MIMO using 10 GHz measurements

Orientador: Gustavo FraidenraichTese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Elétrica e de ComputaçãoResumo: Este trabalho apresenta um conjunto de contribuições para caracterização e modelagem de canais reais de rádio abordando aspectos relacionados com as condições favoráveis de propagação para sistemas massive MIMO. Discutiremos como caracterizar canais de rádio em um ambiente real, processamento de dados e análise das condições favoráveis de propagação. Em uma segunda parte, focamos na determinação teórica de alguns aspectos da tecnologia de massive MIMO utilizando propriedades de distribuições matriciais Wishart. Inicialmente, apresentamos uma contribuição sobre a aplicação do algoritmo ESPRIT, para estimar parâmetros de um conjunto de dados multidimensional. Obtivemos dados por varredura em frequência de um Analisador Vetorial de Rede e os adaptamos para o algoritmo ESPRIT. Mostramos como remover a influência do ganho de padrão de antenas e como utilizar um gerador de modelo de canal baseado nas medidas reais de canal de rádio. As medidas foram feitas na frequência de 10.1 GHz com largura de faixa de 500 MHz. Utilizando um gerador de modelo de canal, fomos além do universo das simulações por distribuições Gaussianas. Introduzimos o conceito de propagação favorável e analisamos condições de linha-de-visada usando arranjos lineares uniformes e arranjos retangulares uniformes de antena. Como novidade da pesquisa, mostramos os benefícios de explorar um número extra de graus de liberdade devido à escolha dos formatos de arranjo de antenas e ao aumento do número de elementos. Esta propriedade é observada ao analisarmos a distribuição dos autovalores de matrizes Gramianas. Em seguida, estendemos o mesmo raciocínio para as matrizes de canal geradas a partir de informações reais e verificamos se as propriedades ainda permaneceriam válidas. Na segunda parte deste trabalho, incluímos mais de uma antena no terminal móvel e calculamos a probabilidade de indisponibilidade para várias configurações de antenas e número arbitrário de usuários. Esboçamos inicialmente a formulação para a informação mútua e, em seguida, calculamos os resultados exatos em uma situação com dois usuários e duas antenas, tanto na estação base (EB) como nos terminais de usuário(TU). Visto que as formulações para a derivação exata dos casos com mais antenas e mais usuários mostrou-se muito intrincada, propusemos uma aproximação Gaussiana para simplificar o problema. Esta aproximação foi validada por simulações Monte Carlo para diferentes relações sinal/ruídoAbstract: This thesis presents a set of contributions for channel modeling and characterization of real radio channels delineating aspects related with the favorable propagation for massive MIMO systems. We will discuss about how to proceed for characterizing radio channels in an real environment , data processing, and analysis of favorable conditions. In a second part, we focused on determination of some theoretical aspects of the Massive MIMO technology using properties of Wishart distribution matrices. We initially present a contribution on the application of ESPRIT algorithm for estimating a multidimensional set of measured data. We have obtained data by frequency sweep carried out by a vector network analyzer(VNA) and adapted it to fit in the ESPRIT algorithm. We show how to remove antenna pattern gain using virtual antenna arrays and how to use a channel model generator based on radio channel measurements of real environments. The measurements were conducted at the frequency of 10.1 GHz and 500 MHz bandwidth. By using a channel model generator, we have explored beyond the simulation of Gaussian Distributions. We will introduce the concept of favorable propagation and analyze the line-of-sight conditions using ULA and URA array shapes. As a research novelty, we will show the benefits of exploiting an extra degree of freedom due to the choice of the antenna shapes and amount of antenna elements. We observe these properties through the distribution of the Gramian Matrices. Next, we extend the same rationale to channel matrices generated from real channels and we verify that the properties are still valid. In a second part of the research work, we included more than one antenna in the mobile terminals and calculated the outage probability for several antenna configurations and arbitrary number users. We introduce a formulation for mutual information and then we calculate exact results in a case with two users with two antennas in both Base Station (BS) and User Terminals (UT). Since the formulations to the exact derivation for cases with more antennas and users seems to be intricate, we propose a Gaussian approximation solution to simplify the problem. We validated this approximation with Monte Carlo simulations for different signal-to-noise ratiosDoutoradoTelecomunicações e TelemáticaDoutor em Engenharia Elétrica248416/2013-8CNPQCAPE