Vehicle to vehicle (V2V) wireless communications

This work focuses on the vehicle-to-vehicle (V2V) communication, its current challenges, future perspective and possible improvement.V2V communication is characterized by the dynamic environment, high mobility, nonpredective scenario, propagation effects, and also communicating antenna's positions. This peculiarity of V2V wireless communication makes channel modelling and the vehicular propagation quite challenging. In this work, firstly we studied the present context of V2V communication also known as Vehicular Ad-hoc Netwok (VANET) including ongoing researches and studies particularly related to Dedicated Short Range Communication (DSRC), specifically designed for automotive uses with corresponding set of protocols and standards. Secondly, we focused on communication models and improvement of these models to make them more suitable, reliable and efficient for the V2V environment. As specifies the standard, OFDM is used in V2V communication, Adaptable OFDM transceiver was designed. Some parameters as performance analytics are used to compare the improvement with the actual situation. For the enhancement of physical layer of V2V communication, this work is focused in the study of MIMO channel instead of SISO. In the designed transceiver both SISO and MIMO were implemented and studied successfully

Fine-Grained Reliability for V2V Communications around Suburban and Urban Intersections

Safe transportation is a key use-case of the 5G/LTE Rel.15+ communications, where an end-to-end reliability of 0.99999 is expected for a vehicle-to-vehicle (V2V) transmission distance of 100-200 m. Since communications reliability is related to road-safety, it is crucial to verify the fulfillment of the performance, especially for accident-prone areas such as intersections. We derive closed-form expressions for the V2V transmission reliability near suburban corners and urban intersections over finite interference regions. The analysis is based on plausible street configurations, traffic scenarios, and empirically-supported channel propagation. We show the means by which the performance metric can serve as a preliminary design tool to meet a target reliability. We then apply meta distribution concepts to provide a careful dissection of V2V communications reliability. Contrary to existing work on infinite roads, when we consider finite road segments for practical deployment, fine-grained reliability per realization exhibits bimodal behavior. Either performance for a certain vehicular traffic scenario is very reliable or extremely unreliable, but nowhere in relatively proximity to the average performance. In other words, standard SINR-based average performance metrics are analytically accurate but can be insufficient from a practical viewpoint. Investigating other safety-critical point process networks at the meta distribution-level may reveal similar discrepancies.Comment: 27 pages, 6 figures, submitted to IEEE Transactions on Wireless Communication

Fine-Grained vs. Average Reliability for V2V Communications around Intersections

Intersections are critical areas of the transportation infrastructure associated with 47% of all road accidents. Vehicle-to-vehicle (V2V) communication has the potential of preventing up to 35% of such serious road collisions. In fact, under the 5G/LTE Rel.15+ standardization, V2V is a critical use-case not only for the purpose of enhancing road safety, but also for enabling traffic efficiency in modern smart cities. Under this anticipated 5G definition, high reliability of 0.99999 is expected for semi-autonomous vehicles (i.e., driver-in-the-loop). As a consequence, there is a need to assess the reliability, especially for accident-prone areas, such as intersections. We unpack traditional average V2V reliability in order to quantify its related fine-grained V2V reliability. Contrary to existing work on infinitely large roads, when we consider finite road segments of significance to practical real-world deployment, fine-grained reliability exhibits bimodal behavior. Performance for a certain vehicular traffic scenario is either very reliable or extremely unreliable, but nowhere in relative proximity to the average performance.Comment: 5 pages, 4 figures. arXiv admin note: substantial text overlap with arXiv:1706.1001

Agile Calibration Process of Full-Stack Simulation Frameworks for V2X Communications

Computer simulations and real-world car trials are essential to investigate the performance of Vehicle-to-Everything (V2X) networks. However, simulations are imperfect models of the physical reality and can be trusted only when they indicate agreement with the real-world. On the other hand, trials lack reproducibility and are subject to uncertainties and errors. In this paper, we will illustrate a case study where the interrelationship between trials, simulation, and the reality-of-interest is presented. Results are then compared in a holistic fashion. Our study will describe the procedure followed to macroscopically calibrate a full-stack network simulator to conduct high-fidelity full-stack computer simulations.Comment: To appear in IEEE VNC 2017, Torino, I

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

Robust Low-Cost Multiple Antenna Processing for V2V Communication

Cooperative V2V communication with frequent, periodic broadcast of messages between vehicles is a key enabler of applications that increase traffic safety and traffic efficiency on roads. Such broadcast V2V communication requires an antenna system with omnidirectional coverage, which is difficult to achieve using a single antenna element. For a mounted, omnidirectional antenna on a vehicle is distorted by the vehicle body, and exhibits a nonuniform directional pattern with low gain in certain directions. The thesis addresses this problem by developing schemes that employ multiple antennas (MAs) to achieve an effective radiation pattern with omnidirectional characteristics at both the transmit- and the receive-side. To ensure robust communication, the MA schemes are designed to minimize the burst error probability of several consecutive status messages in a scarce multipath environment with a dominant path between vehicles.First, at the receive-side, we develop a hybrid analog-digital antenna combiner. The analog part of the combiner is composed of low-cost analog combining networks (ACNs) of phase shifters that do not depend on channel stateinformation (CSI), while the digital part uses maximal ratio combining. We show that the optimal phase slopes of the analog part of the combiner (i.e., the phase slopes that minimize the burst error probability) are the same found under the optimization of a single ACN, which was done in earlier work. We then show how directional antennas can be employed in this context to achieve an effective omnidirectional radiation pattern of the antenna system that is robust in all directions of arrival of received signals.Secondly, at the transmit-side, we develop two low-cost analog MA schemes, an analog beamforming network (ABN) of phase shifters, and an antenna switching network (ASN), for the case when receivers employ the ACN or the hybrid combiner. Both schemes are shown to achieve an effective radiation pattern with improved omnidirectional characteristics at the transmit-side without relying on CSI.Thirdly, the schemes above were developed assuming that all vehicles broadcast their messages with the same fixed period. Therefore, we tackle the practical scenario when different vehicles use different and potentially varying broadcast periods. We show that the phase slopes of the MA schemes at the receiver and/or transmitter can be designed to support multiple broadcast periods.\ua0Lastly, the optimal phase slopes of the MA schemes were analytically derived under a worst-case propagation corresponding to a dominant path with an angle of departure, and an angle of arrival that are approximately non-varying over the time it takes to transmit and receive several packets. We relax this assumption and study the system performance under a time-varying dominant component instead. We derive a design rule that yields robust phase slopes that effectively mitigate the losses due to the time-variation of the dominant path

A Two-Stage Allocation Scheme for Delay-Sensitive Services in Dense Vehicular Networks

Driven by the rapid development of wireless communication system, more and more vehicular services can be efficiently supported via vehicle-to-everything (V2X) communications. In order to allocate radio resource with the reasonable implementation complexity in dense urban intersection, a two-stage allocation algorithm is proposed in this paper, whose main objective is to minimize delay and ensure reliability. In particular, as for the first stage, the allocation policy is based on traffic density information (TDI), which is different from utilizing channel state information (CSI) and queue state information (QSI) in the second stage. Moreover, in order to reflect the influence of TDI on delay, a macroscopic vehicular mobility model is employed in this paper. Simulation results show that the proposed algorithm can acquire an asymptotically optimal performance with the acceptable complexity

Multi-Agent Reinforcement Learning for Joint Channel Assignment and Power Allocation in Platoon-Based C-V2X Systems

We consider the problem of joint channel assignment and power allocation in underlaid cellular vehicular-to-everything (C-V2X) systems where multiple vehicle-to-infrastructure (V2I) uplinks share the time-frequency resources with multiple vehicle-to-vehicle (V2V) platoons that enable groups of connected and autonomous vehicles to travel closely together. Due to the nature of fast channel variant in vehicular environment, traditional centralized optimization approach relying on global channel information might not be viable in C-V2X systems with large number of users. Utilizing a reinforcement learning (RL) approach, we propose a distributed resource allocation (RA) algorithm to overcome this challenge. Specifically, we model the RA problem as a multi-agent system. Based solely on the local channel information, each platoon leader, who acts as an agent, collectively interacts with each other and accordingly selects the optimal combination of sub-band and power level to transmit its signals. Toward this end, we utilize the double deep Q-learning algorithm to jointly train the agents under the objectives of simultaneously maximizing the V2I sum-rate and satisfying the packet delivery probability of each V2V link in a desired latency limitation. Simulation results show that our proposed RL-based algorithm achieves a close performance compared to that of the well-known exhaustive search algorithm.Comment: 6 pages, 4 figure

Cluster-Based Radio Resource Management for D2D-Supported Safety-Critical V2X Communications

Deploying direct device-to-device (D2D) links is a promising technology for vehicle-to-X (V2X) applications. However, intracell interference, along with stringent requirements on latency and reliability, are challenging issues. In this paper, we study the radio resource management problem for D2D-based safety-critical V2X communications. We first transform the V2X requirements into the constraints that are computable using slowly varying channel state information only. Secondly, we formulate an optimization problem, taking into account the requirements of both vehicular users (V-UEs) and cellular users (C-UEs), where resource sharing can take place not only between a V-UE and a C-UE but also among different V-UEs. The NP-hardness of the problem is rigorously proved. Moreover, a heuristic algorithm, called Cluster-based Resource block sharing and pOWer allocatioN (CROWN), is proposed to solve this problem. Finally, simulation results indicate promising performance of the CROWN scheme