Extending TDL based non-WSSUS vehicle-to-everything channel model

In den vergangenen Jahrzehnten haben drahtlose Kommunikationssysteme eine rasante Entwicklung durchgemacht und es wurden viele Untersuchungen durchgeführt, seit Maxwell die Existenz von elektromagnetischer Wellen vorausgesagt hat. In den letzten Jahren hat die Forschung im Bereich der vehicle to X (V2X)-Kommunikation stetig zugenommen. V2X beschreibt die Fähigkeit, Daten zwischen einem Fahrzeug oder vehicle (V) und “allem” zu übertragen. In Zukunft könnten Fahrzeuge mit ihrer Umgebung kommunizieren, um Verkehrsunfälle zu vermeiden und Staus zu verringern. Dazu werden sie ihr Geschwindigkeits- und Positionsdaten über Ad-hoc-Fahrzeugnetze senden und empfangen können. Um die Verkehrssicherheit zu erhöhen, ist eine zuverlässige Kommunikationsverbindung notwendig. Die größte Herausforderung bei der Fahrzeugkommunikation besteht darin, dass sich die Eigenschaften des Physical Layers aufgrund der inhärenten Mobilität innerhalb des Kanals, der hohen Fahrzeuggeschwindigkeiten, der unterschiedlichen Antennenpositionen und der vielen Handover aufgrund kleinerer Zellen schnell ändern. Dies bringt eine Reihe von Herausforderungen in Bezug auf die Kanalcharakterisierung mit sich. Es handelt sich um einen Kanal mit starker Zeitvarianz und es treten viele Übergänge auf. Somit handelt es sich um einen nicht-stationärer (non-stationary) Kanal. Das Hauptziel dieser Untersuchung ist es, eine Methode zu finden, mit der der Kanal einer komplexen Umgebung in einer einfachen Form mit weniger strengen Beziehungen zur Geometrie dargestellt werden kann. Dabei werden die statistischen Eigenschaften ähnlich der Messdaten beibehalten. In dieser Arbeit werden nichtstationäre tapped delay line (TDL)-Modelle verwendet, um vehicle to infrastructure (V2I)-Kanäle zu beschreiben. Es wird eine neue Strategie zur Extraktion von TDL-Kanalmodellparametern aus Messdaten vorgeschlagen. Dieser Ansatz basiert auf einer bestehenden Methode zur Ableitung von Parametern für ein TDLModell. Es wird gezeigt, dass mit einer anderen Methode zur Auswahl der Taps die Anzahl der Abgriffe, die zur Rekonstruktion der root mean square delay spread (RMS-DS) eines Kanals erforderlich sind, erheblich reduziert werden kann. Ein neuer Ansatz zur überprüfen der Korrektheit der Ableitung der Kanalmodellparameter wird aufgezeigt. Die Durchführbarkeit der Methode wird anhand von Channel Sounding Messungen bestätigt. In dieser Dissertation wird ein Generator zur Erzeugung von Kanalimpulsantworten entwickelt und das nichtstationäre Verhalten der Kanäle durch die Verwendung eines ON/OFF-Prozesses beschrieben. Es werden Markov-Ketten unterschiedlicher Ordnung modelliert, um das nicht-stationäre Verhalten besser zu erfassen. Die Untersuchung zeigt, dass Markov-Ketten erster Ordnung mit zwei Zuständen vorzuziehen sind, um das häufige ON/OFF-Verhalten von Mehrwegpfaden darzustellen, und dass die Markov-Modelle zweiter und dritter Ordnung keine großen Auswirkungen haben. Eine Methode zur Erweiterung eines single input single output (SISO)-TDL-Modells auf multiple input multiple output (MIMO) unter der non-wide sense stationary uncorrelated scattering (non-WSSUS)-Annahme wird eingeführt, um TDL-Kanalmodelle für V2I MIMO-Systeme zu entwickeln. Die Analyse bewertet die SISO- mit der MIMO-Konfiguration in Bezug auf die Kanalkapazität. Es werden verschiedene MIMO-Konfigurationen untersucht, und es wird gezeigt, dass die Position der Antennen eine wichtige Rolle spielt. Die Verwendung von nur vier Antennen am transmitter (Tx) und receiver (Rx), die in unterschiedliche Richtungen abstrahlen, führt zu einem qualitativen Sprung in der Leistungsfähigkeit des Systems.In the past decades, wireless communication systems have undergone rapid development, and many investigations have been done since Maxwell predicted the existence of electromagnetic waves. In recent years, vehicle to X (V2X) communication research has been growing steadily. V2X describes the ability to transmit data between a vehicle (V) and “everything”. In the future, vehicles might be able to communicate with their environment to prevent traffic accidents and reduce congestion by allowing vehicles to transmit and receive data through a vehicular ad hoc network at their speed and position. In order to achieve the ultimate goal of enhancing transportation safety, it is crucial to establish reliable communication links. The main challenge of vehicular communications introduces new properties because the physical layer properties are rapidly changing due to inherent mobility within the channel, high vehicle speeds, varying antenna positions, and many handovers due to smaller cells. This brings up a number of challenges in terms of channel characterization because it is a strong time-variant channel and many transitions occur; therefore, it is a non-stationary channel. In this thesis, non-stationary tapped delay line (TDL) models are used to describe the vehicle to infrastructure (V2I) channels. This thesis proposes a new strategy to extract TDL channel model parameters from measurement data. The proposed approach is based on an existing method to derive parameters for a TDL model. It will be shown that with a different method of choosing taps, the number of taps necessary to regenerate the root mean square delay spread (RMS-DS) of a channel can be significantly reduced. An approach is proposed to verify the correctness of the channel model parameters derivation. The feasibility of the method will be confirmed using channel-sounding measurements. This dissertation devises a generator to produce channel impulse responses (CIRs) and describes the non-stationary behavior of the channels via employing an ON/OFF process. Different order Markov chains are modeled with the aim of better capturing the non-stationary behavior. The investigation shows that first-order two-state Markov chains are preferable to represent multipath’s frequent ON/OFF behavior, and the second- and third-order Markov models do not make enormous effects. A method for extending a single input single output (SISO)-TDL model to multiple input multiple output (MIMO) under non-wide sense stationary uncorrelated scattering (non-WSSUS) assumption is introduced to develop TDL channel models for the V2I MIMO systems. The analysis evaluates SISO- with MIMO configuration in terms of channel capacity. Different MIMO configurations are explored, and it will be illustrated that the position of antennas plays an important role. Using only four antennas at the transmitter (Tx) and receiver (Rx) that radiate towards different directions will make a qualitative leap in the performance of the system

Modeling of multipath fading channels for network simulation

Development of accurate physical layer models is very important for generating realistic network simulation results. Significant effort has been put into setting up physical layer models for wireless channels that emulate the impact of the channel on the higher layers of the network. Setting up the models is especially difficult for a frequency selective channel. In this thesis the use of non-linear functions to convert the frequency selective channel to an equivalent flat fading channel is examined. The analytical expressions for the statistics of the equivalent flat fading process that are needed to set up the physical layer models are derived. These results are used to set up the physical layer model for the frequency selective channel. Extensive simulations are performed to verify the accuracy of the model against a detailed physical layer implementation. The statistics of the model and the actual channel are seen to match, validating the method of setting up the models

Mac-Phy Cross-Layer analysis and design of Mimo-Ofdm Wlans based on fast link adaptation

The latestWLAN standard, known as IEEE 802.11n, has notably increased the network capacity with respect to its predecessors thanks to the incorporation of the multipleinput multiple-output (MIMO) technology. Nonetheless, the new amendment, as its previous ones, does not specify how crucial configuration mechanisms, most notably the adaptive modulation and coding (AMC) algorithm should be implemented. The AMC process has proved essential to fully exploit the system resources in light of varying channel conditions. In this dissertation, a closed-loop AMC technique, referred to as fast link adaption (FLA) algorithm, that effectively selects themodulation and coding scheme (MCS) for multicarriermultiantennaWLAN networks is proposed. The FLA algorithm determines the MCS that maximizes the throughput while satisfying a quality of service (QoS) constraint, usually defined in the form of an objective packet error rate (PER). To this end, FLA uses a packet/bit error rate prediction methodology based on the exponential effective SNRmetric (EESM). The FLA algorithm performance has been evaluated under IEEE 802.11n systems that thanks to the incorporation of a feedbackmechanismare able to implement closed- loop AMC mechanisms. Initially, this AMC technique relies only on physical layer information but it is subsequently extended to also take into account themediumaccess control (MAC) sublayer performance. At the physical layer, the FLA algorithm has demonstrated its effectivity by performing very close to optimality in terms of throughput, while satisfying a prescribed PER constraint. The FLA algorithm has also been evaluated using imperfect channel information. It has been observed that the proposed FLA technique is rather robust against imperfect channel information, and only in highly-frequency selective channels, imperfect channel knowledge causes a noticeable degradation in throughput. At the MAC sublayer, the FLA algorithm has been complemented with a timeout strategy that weighs down the influence of the available channel information as this becomes outdated. This channel information outdate is caused by the MAC sublayer whose user multiplexing policy potentially results in large delays between acquiring the instant in which the channel state information is acquired and that in which the channel is accessed. Results demonstrate the superiority of FLA when compared to open-loop algorithms under saturated and non-saturated conditions and irrespective of the packet length, number of users, protocol (CSMA/CA or CDMA/E2CA) and access scheme (Basic Access or RTS/CTS). Additionally, several analytical models have been developed to estimate the system performance at the MAC sublayer. These models account for all operational details of the IEEE 802.11n MAC sublayer, such as finite number of retries, anomalous slot or channel errors. In particular, a semi-analytical model that assesses the MAC layer throughput under saturated conditions, considering the AMC performance is first introduced. Then, an analytical model that allows the evaluation of the QoS performance under non-saturated conditions is presented. This model focuses on single MCS and it is able to accurately predict very important system performance metrics such as blocking probability, delay, probability of discard or goodput thanks to the consideration of the finite queues on each station. Finally, the previous non-saturated analytical approach is used to define a semi-analytical model in order to estimate the system performance when considering AMC algorithms (i.e. whenmultiple MCSs are available)La darrera versió de l’estàndard deWLAN, anomenada IEEE 802.11n, ha augmentat la seva capacitat notablement en relació als sistemes anteriors gràcies a la incorporació de la tecnologia de múltiples antenes en transmissió i recepció (MIMO). No obstant això, la nova proposta, al igual que les anteriors, segueix sense especificar com s’han d’implementar elsmecanismes de configuraciómés crucials, un dels quals és l’algoritme de codificació imodulació adaptativa (AMC). Aquests algoritmes ja han demostrat la seva importància a l’hora demaximitzar el rendiment del sistema tenint en compte les condicions canviants del canal. En aquesta tesis s’ha proposat un algoritme AMC de llaç tancat, anomenat adaptació ràpida de l’enllaç (FLA), que selecciona eficientment l’esquema demodulació i codificació adaptativa per xarxes WLAN basades en arquitectures multiportadora multiantena. L’algoritme FLA determina el mode de transmissió capaç de maximitzar el throughput per les condicions de canal actuals, mentre satisfà un requisit de qualitat de servei en forma de taxa d’error per paquet (PER). FLA utilitza una metodologia de predicció de PER basada en l’estimació de la relació senyal renou (SNR) efectiva exponencial (EESM). El rendiment de l’algoritme FLA ha estat avaluat en sistemes IEEE 802.11n, ja que aquests, gràcies a la incorporació d’unmecanisme de realimentació demodes de transmissió, poden adoptar solucions AMC de llaç tancat. En una primera part, l’estudi s’ha centrat a la capa física i després s’ha estès a la subcapa MAC. A la capa física s’ha demostrat l’efectivitat de l’algoritme FLA aconseguint un rendiment molt proper al que ens proporcionaria un esquema AMC òptim en termes de throughput, alhora que es satisfan els requisits de PER objectiu. L’algoritme FLA també ha estat avaluat utilitzant informació imperfecte del canal. S’ha vist que l’algoritme FLA proposat és robust en front dels efectes d’estimació imperfecte del canal, i només en canals altament selectius en freqüència, la informació imperfecte del canal provoca una davallada en el rendiment en termes de throughput. A la subcapa MAC, l’algoritme FLA ha estat complementat amb una estratègia de temps d’espera que disminueix la dependència amb la informació de canal disponible a mesura que aquesta va quedant desfassada respecte de l’estat actual. Aquesta informació de canal desfassada és conseqüència de la subcapa MAC que degut a la multiplexació d’usuaris introdueix grans retards entre que es determina el mode de transmissió més adequat i la seva utilització per a l’accés al canal. Els resultats obtinguts han demostrat la superioritat de FLA respecte d’altres algoritmes de llaç obert en condicions de saturació i de no saturació, i independentment de la longitud de paquet, nombre d’usuaris, protocol (CSMA/CA i CSMA/E2CA) i esquema d’accés (Basic Access i RTS/CTS). Amés, s’han desenvolupat diversosmodels analítics per tal d’estimar el rendiment del sistema a la subcapa MAC. Aquests models consideren tots els detalls de funcionament de la subcapaMAC del 802.11n, comper exemple un nombre finit de retransmissions de cada paquet, l’slot anòmal o els errors introduïts pel canal. Inicialment s’ha proposat unmodel semi-analític que determina el throughtput en condicions de saturació, considerant el rendiment dels algoritmes AMC. Després s’ha presentat un model analític que estima el rendiment del sistema per condicions de no saturació, mitjançat elmodelat de cues finites a cada estació. Aquestmodel consideramodes de transmissió fixes i és capaç de determinar de manera molt precisa mètriques de rendimentmolt importants comsón la probabilitat de bloqueig de cada estació, el retard mitjà del paquets, la probabilitat de descart o la mesura del goodput. Finalment, el model analític de no saturació s’ha utilitzat per definir un model semi-analític per tal d’estimar el rendiment del sistema quan es considera l’ús d’algoritmes AMC

Modelling of mobile fading channels with fading mitigation techniques

This thesis aims to contribute to the developments of wireless communication systems. The work generally consists of three parts: the first part is a discussion on general digital communication systems, the second part focuses on wireless channel modelling and fading mitigation techniques, and in the third part we discuss the possible application of advanced digital signal processing, especially time-frequency representation and blind source separation, to wireless communication systems. The first part considers general digital communication systems which will be incorporated in later parts. Today's wireless communication system is a subbranch of a general digital communication system that employs various techniques of A/D (Analog to Digital) conversion, source coding, error correction, coding, modulation, and synchronization, signal detection in noise, channel estimation, and equalization. We study and develop the digital communication algorithms to enhance the performance of wireless communication systems. In the Second Part we focus on wireless channel modelling and fading mitigation techniques. A modified Jakes' method is developed for Rayleigh fading channels. We investigate the level-crossing rate (LCR), the average duration of fades (ADF), the probability density function (PDF), the cumulative distribution function (CDF) and the autocorrelation functions (ACF) of this model. The simulated results are verified against the analytical Clarke's channel model. We also construct frequency-selective geometrical-based hyperbolically distributed scatterers (GBHDS) for a macro-cell mobile environment with the proper statistical characteristics. The modified Clarke's model and the GBHDS model may be readily expanded to a MIMO channel model thus we study the MIMO fading channel, specifically we model the MIMO channel in the angular domain. A detailed analysis of Gauss-Markov approximation of the fading channel is also given. Two fading mitigation techniques are investigated: Orthogonal Frequency Division Multiplexing (OFDM) and spatial diversity. In the Third Part, we devote ourselves to the exciting fields of Time-Frequency Analysis and Blind Source Separation and investigate the application of these powerful Digital Signal Processing (DSP) tools to improve the performance of wireless communication systems

Multi-Polarized Channel Characterization

Machine-to-machine (M2M) communication is becoming an important aspect of warehouse management, remote control, robotics, traffic control, supply chain management, fleet management and telemedicine. M2M is expected to become a significant portion of the Industrial Internet and, more broadly, the Internet of Things (IoT). The environments in which M2M systems are expected to operate may be challenging in terms of radio wave propagation due to their cluttered, multipath nature, which can cause deep signal fades and signal depolarization. Polarization diversity in two dimensions is a well-known technique to mitigate such fades. But in the presence of reflectors and retarders where multipath components arrive from any direction, we find the detrimental effects to be three-dimensional and thus consider herein mitigation approaches that are also 3D. The objectives of this dissertation are three. First, to provide a theoretical framework for depolarization in three dimensions. Second, to prepare a tripolar antenna design that meets cost, power consumption, and simplicity requirements of M2M applications and that can mitigate the expected channel effects. Finally, to develop new channel models in three dimensional space for wireless systems. Accordingly, this dissertation presents a complete description of 3D electromagnetic fields, in terms of their polarization characteristics and confirms the advantage of employing tripolar antennas in multipath conditions. Furthermore, the experimental results illustrate that highly variable depolarization occurs across all three spatial dimensions and is dependent on small changes in frequency and space. Motivated by these empirical results, we worked with a collaborating institution to develop a three-dimensional tripolar antenna that can be integrated with a commercially available wireless sensor. This dissertation presents the testing results that show that this design significantly improves channels over traditional 2D approaches. The implications of tripolar antenna integration on M2M systems include reduction in energy use, longer wireless communication link distances, and/or greater link reliability. Similar results are shown for a planar antenna design that enables four different polarization configurations. Finally, the work presents a novel three-dimensional geometry-based stochastic channel model that builds the channel as a sum of shell-like sub-regions, where each sub-region consists of groups of multipath components. The model is validated with empirical data to show the approach may be used for system analyses in indoor environments

Neural-Kalman Schemes for Non-Stationary Channel Tracking and Learning

This Thesis focuses on channel tracking in Orthogonal Frequency-Division Multiplexing (OFDM), a widely-used method of data transmission in wireless communications, when abrupt changes occur in the channel. In highly mobile applications, new dynamics appear that might make channel tracking non-stationary, e.g. channels might vary with location, and location rapidly varies with time. Simple examples might be the di erent channel dynamics a train receiver faces when it is close to a station vs. crossing a bridge vs. entering a tunnel, or a car receiver in a route that grows more tra c-dense. Some of these dynamics can be modelled as channel taps dying or being reborn, and so tap birth-death detection is of the essence. In order to improve the quality of communications, we delved into mathematical methods to detect such abrupt changes in the channel, such as the mathematical areas of Sequential Analysis/ Abrupt Change Detection and Random Set Theory (RST), as well as the engineering advances in Neural Network schemes. This knowledge helped us nd a solution to the problem of abrupt change detection by informing and inspiring the creation of low-complexity implementations for real-world channel tracking. In particular, two such novel trackers were created: the Simpli- ed Maximum A Posteriori (SMAP) and the Neural-Network-switched Kalman Filtering (NNKF) schemes. The SMAP is a computationally inexpensive, threshold-based abrupt-change detector. It applies the three following heuristics for tap birth-death detection: a) detect death if the tap gain jumps into approximately zero (memoryless detection); b) detect death if the tap gain has slowly converged into approximately zero (memory detection); c) detect birth if the tap gain is far from zero. The precise parameters for these three simple rules can be approximated with simple theoretical derivations and then ne-tuned through extensive simulations. The status detector for each tap using only these three computationally inexpensive threshold comparisons achieves an error reduction matching that of a close-to-perfect path death/birth detection, as shown in simulations. This estimator was shown to greatly reduce channel tracking error in the target Signal-to-Noise Ratio (SNR) range at a very small computational cost, thus outperforming previously known systems. The underlying RST framework for the SMAP was then extended to combined death/birth and SNR detection when SNR is dynamical and may drift. We analyzed how di erent quasi-ideal SNR detectors a ect the SMAP-enhanced Kalman tracker's performance. Simulations showed SMAP is robust to SNR drift in simulations, although it was also shown to bene t from an accurate SNR detection. The core idea behind the second novel tracker, NNKFs, is similar to the SMAP, but now the tap birth/death detection will be performed via an arti cial neuronal network (NN). Simulations show that the proposed NNKF estimator provides extremely good performance, practically identical to a detector with 100% accuracy. These proposed Neural-Kalman schemes can work as novel trackers for multipath channels, since they are robust to wide variations in the probabilities of tap birth and death. Such robustness suggests a single, low-complexity NNKF could be reusable over di erent tap indices and communication environments. Furthermore, a di erent kind of abrupt change was proposed and analyzed: energy shifts from one channel tap to adjacent taps (partial tap lateral hops). This Thesis also discusses how to model, detect and track such changes, providing a geometric justi cation for this and additional non-stationary dynamics in vehicular situations, such as road scenarios where re ections on trucks and vans are involved, or the visual appearance/disappearance of drone swarms. An extensive literature review of empirically-backed abrupt-change dynamics in channel modelling/measuring campaigns is included. For this generalized framework of abrupt channel changes that includes partial tap lateral hopping, a neural detector for lateral hops with large energy transfers is introduced. Simulation results suggest the proposed NN architecture might be a feasible lateral hop detector, suitable for integration in NNKF schemes. Finally, the newly found understanding of abrupt changes and the interactions between Kalman lters and neural networks is leveraged to analyze the neural consequences of abrupt changes and brie y sketch a novel, abrupt-change-derived stochastic model for neural intelligence, extract some neuro nancial consequences of unstereotyped abrupt dynamics, and propose a new portfolio-building mechanism in nance: Highly Leveraged Abrupt Bets Against Failing Experts (HLABAFEOs). Some communication-engineering-relevant topics, such as a Bayesian stochastic stereotyper for hopping Linear Gauss-Markov (LGM) models, are discussed in the process. The forecasting problem in the presence of expert disagreements is illustrated with a hopping LGM model and a novel structure for a Bayesian stereotyper is introduced that might eventually solve such problems through bio-inspired, neuroscienti cally-backed mechanisms, like dreaming and surprise (biological Neural-Kalman). A generalized framework for abrupt changes and expert disagreements was introduced with the novel concept of Neural-Kalman Phenomena. This Thesis suggests mathematical (Neural-Kalman Problem Category Conjecture), neuro-evolutionary and social reasons why Neural-Kalman Phenomena might exist and found signi cant evidence for their existence in the areas of neuroscience and nance. Apart from providing speci c examples, practical guidelines and historical (out)performance for some HLABAFEO investing portfolios, this multidisciplinary research suggests that a Neural- Kalman architecture for ever granular stereotyping providing a practical solution for continual learning in the presence of unstereotyped abrupt dynamics would be extremely useful in communications and other continual learning tasks.Programa de Doctorado en Multimedia y Comunicaciones por la Universidad Carlos III de Madrid y la Universidad Rey Juan CarlosPresidente: Luis Castedo Ribas.- Secretaria: Ana García Armada.- Vocal: José Antonio Portilla Figuera

Stationarity analysis of V2I radio channel in a suburban environment

Due to rapid changes in the environment, vehicular communication channels no longer satisfy the assumption of wide-sense stationary uncorrelated scattering. The non-stationary fading process can be characterized by assuming local stationarity regionswith finite extent in time and frequency. The local scattering function (LSF) and channel correlation function (CCF) provide a framework to characterize the mean power and correlation of the non-stationary channel scatterers, respectively. In this paper, we estimate the LSF and CCF from measurements collected in a vehicle-to-infrastructure radio channel sounding campaign in a suburban environment in Lille, France. Based on the CCF, the stationarity region is evaluated in time as 567 ms and used to capture the non-stationary fading parameters. We obtain the time-varying delay and Doppler power profiles fromthe LSF, and we analyze the corresponding root-mean-square delay and Doppler spreads. We show that the distribution of these parameters follows a lognormal model. Finally, application relevance in terms of channel capacity and diversity techniques is discussed. Results show that the assumption of ergodic capacity and the performance of various diversity techniques depend on the stationarity and coherence parameters of the channel. The evaluation and statistical modeling of such parameters can provide away of tracking channel variation, hence, increasing the performance of adaptive schemes