Radio resource allocation for overlay D2D-based vehicular communications in future wireless networks

Mobilfunknetze der nächsten Generation ermöglichen einen weitverbreiteten Einsatz von Device-to-Device Kommunikation, der direkten Kommunikation zwischen zellularen Endgeräten. Für viele Anwendungsfälle zur direkten Kommunikation zwischen Endgeräten sind eine deterministische Latenz und die hohe Zuverlässigkeit von zentraler Bedeutung. Dienste zur direkten Kommunikation (D2D) für in der Nähe befindliche Endgeräte sind vielversprechend die hohen Anforderungen an Latenz und Zuverlässigkeit für zukünftige vertikale Anwendungen zu erfüllen. Eine der herausragenden vertikalen Anwendungen ist die Fahrzeugkommunikation, bei der die Fahrzeuge sicherheitskritische Meldungen direkt über D2D-Kommunikation austauschen, die dadurch zur Reduktion von Verkehrsunfällen und gleichzeitig von Todesfällen im Straßenverkehrt beiträgt. Neue Techniken zur effizienteren Zuweisung von Funkressourcen in der D2D-Kommunikation haben in letzter Zeit in Industrie und Wissenschaft große Aufmerksamkeit erlangt. Zusätzlich zur Allokation von Ressourcen, wird die Energieeffizienz zunehmend wichtiger, die normalerweise im Zusammenhang mit der Ressourcenallokation behandelt wird. Diese Dissertation untersucht verschiedener Ansätze der Funkressourcenzuweisung und Energieeffizienztechniken in der LTE und NR V2X Kommunikation. Im Folgenden beschreiben wir kurz die Kernideen der Dissertation. Meist zeichnen sich D2D-Anwendungen durch ein relativ geringes Datenvolumen aus, die über Funkressourcen übertragen werden. In LTE können diese Funkressourcen aufgrund der groben Granularität für die Ressourcenzuweisung nicht effizient genutzt werden. Insbesondere beim semi-persistenten Scheduling, bei dem eine Funkressource über einen längeren Zeitraum im Overlay D2D festgelegt wird, sind die Funkressourcen für solche Anwendungen nicht ausgelastet. Um dieses Problem zu lösen, wird eine hierarchische Form für das Management der Funkressourcen, ein sogenanntes Subgranting-Schema, vorgeschlagen. Dabei kann ein nahegelegener zellularer Nutzer, der sogenannte begünstigte Nutzer, ungenutzten Funkressourcen, die durch Subgranting-Signalisierung angezeigt werden, wiederzuverwenden. Das vorgeschlagene Schema wird bewertet und mit "shortening TTI", einen Schema mit reduzierten Sendezeitintervallen, in Bezug auf den Zellendurchsatz verglichen. Als nächster Schritt wird untersucht, wie der begünstigten Benutzer ausgewählt werden kann und als Maximierungsproblem des Zellendurchsatzes im Uplink unter Berücksichtigung von Zuverlässigkeits- und Latenzanforderungen dargestellt. Dafür wird ein heuristischer zentralisierter, d.h. dedizierter Sub-Granting-Radio-Ressource DSGRR-Algorithmus vorgeschlagen. Die Simulationsergebnisse und die Analyse ergeben in einem Szenario mit stationären Nutzern eine Erhöhung des Zelldurchsatzes bei dem Einsatz des vorgeschlagenen DSGRR-Algorithmus im Vergleich zu einer zufälligen Auswahl von Nutzern. Zusätzlich wird das Problem der Auswahl des begünstigten Nutzers in einem dynamischen Szenario untersucht, in dem sich alle Nutzer bewegen. Wir bewerten den durch das Sub-Granting durch die Mobilität entstandenen Signalisierungs-Overhead im DSGRR. Anschließend wird ein verteilter Heuristik-Algorithmus (OSGRR) vorgeschlagen und sowohl mit den Ergebnissen des DSGRR-Algorithmus als auch mit den Ergebnissen ohne Sub-Granting verglichen. Die Simulationsergebnisse zeigen einen verbesserten Zellendurchsatz für den OSGRR im Vergleich zu den anderen Algorithmen. Außerdem ist zu beobachten, dass der durch den OSGRR entstehende Overhead geringer ist als der durch den DSGRR, während der erreichte Zellendurchsatz nahe am maximal erreichbaren Uplink-Zellendurchsatz liegt. Zusätzlich wird die Ressourcenallokation im Zusammenhang mit der Energieeffizienz bei autonomer Ressourcenauswahl in New Radio (NR) Mode 2 untersucht. Die autonome Auswahl der Ressourcen wird als Verhältnis von Summenrate und Energieverbrauch formuliert. Das Ziel ist den Stromverbrauch der akkubetriebenen Endgeräte unter Berücksichtigung der geforderten Zuverlässigkeit und Latenz zu minimieren. Der heuristische Algorithmus "Density of Traffic-based Resource Allocation (DeTRA)" wird als Lösung vorgeschlagen. Bei dem vorgeschlagenen Algorithmus wird der Ressourcenpool in Abhängigkeit von der Verkehrsdichte pro Verkehrsart aufgeteilt. Die zufällige Auswahl erfolgt zwingend auf dem dedizierten Ressourcenpool beim Eintreffen aperiodischer Daten. Die Simulationsergebnisse zeigen, dass der vorgeschlagene Algorithmus die gleichen Ergebnisse für die Paketempfangsrate (PRR) erreicht, wie der sensing-basierte Algorithmus. Zusätzlich wird der Stromverbrauch des Endgeräts reduziert und damit die Energieeffizienz durch die Anwendung des DeTRA-Algorithmus verbessert. In dieser Arbeit werden Techniken zur Allokation von Funkressourcen in der LTE-basierten D2D-Kommunikation erforscht und eingesetzt, mit dem Ziel Funkressourcen effizienter zu nutzen. Darüber hinaus ist der in dieser Arbeit vorgestellte Ansatz eine Basis für zukünftige Untersuchungen, wie akkubasierte Endgeräte mit minimalem Stromverbrauch in der NR-V2X-Kommunikation Funkressourcen optimal auswählen können.Next-generation cellular networks are envisioned to enable widely Device-to-Device (D2D) communication. For many applications in the D2D domain, deterministic communication latency and high reliability are of exceptionally high importance. The proximity service provided by D2D communication is a promising feature that can fulfil the reliability and latency requirements of emerging vertical applications. One of the prominent vertical applications is vehicular communication, in which the vehicles disseminate safety messages directly through D2D communication, resulting in the fatality rate reduction due to a possible collision. Radio resource allocation techniques in D2D communication have recently gained much attention in industry and academia, through which valuable radio resources are allocated more efficiently. In addition to the resource allocation techniques, energy sustainability is highly important and is usually considered in conjunction with the resource allocation approach. This dissertation is dedicated to studying different avenues of the radio resource allocation and energy efficiency techniques in Long Term Evolution (LTE) and New Radio (NR) Vehicle-to-Everythings (V2X) communications. In the following, we briefly describe the core ideas in this study. Mostly, the D2D applications are characterized by relatively small traffic payload size, and in LTE, due to coarse granularity of the subframe, the radio resources can not be utilized efficiently. Particularly, in the case of semi-persistent scheduling when a radio resource is scheduled for a longer time in the overlay D2D, the radio resources are underutilized for such applications. To address this problem, a hierarchical radio resource management scheme, i.e., a sub-granting scheme, is proposed by which nearby cellular users, i.e., beneficiary users, are allowed to reuse the unused radio resource indicated by sub-granting signaling. The proposed scheme is evaluated and compared with shortening Transmission Time Interval (TTI) schemes in terms of cell throughput. Then, the beneficiary user selection problem is investigated and is cast as a maximization problem of uplink cell throughput subject to reliability and latency requirements. A heuristic centralized, i.e., dedicated sub-granting radio resource Dedicated Sub-Granting Radio Resource (DSGRR) algorithm is proposed to address the original beneficiary user selection problem. The simulation results and analysis show the superiority of the proposed DSGRR algorithm over the random beneficiary user selection algorithm in terms of the cell throughput in a scenario with stationary users. Further, the beneficiary user selection problem is investigated in a scenario where all users are moving in a dynamic environment. We evaluate the sub-granting signaling overhead due to mobility in the DSGRR, and then a distributed heuristics algorithm, i.e., Open Sub-Granting Radio Resource (OSGRR), is proposed and compared with the DSGRR algorithm and no sub-granting case. Simulation results show improved cell throughput for the OSGRR compared with other algorithms. Besides, it is observed that the overhead incurred by the OSGRR is less than the DSGRR while the achieved cell throughput is yet close to the maximum achievable uplink cell throughput. Also, joint resource allocation and energy efficiency in autonomous resource selection in NR, i.e. Mode 2, is examined. The autonomous resource selection is formulated as a ratio of sum-rate and energy consumption. The objective is to minimize the energy efficiency of the power-saving users subject to reliability and latency requirements. A heuristic algorithm, density of traffic-based resource allocation (DeTRA), is proposed to solve the problem. The proposed algorithm splits the resource pool based on the traffic density per traffic type. The random selection is then mandated to be performed on the dedicated resource pool upon arrival of the aperiodic traffic is triggered. The simulation results show that the proposed algorithm achieves the same packet reception ratio (PRR) value as the sensing-based algorithm. In addition, per-user power consumption is reduced, and consequently, the energy efficiency is improved by applying the DeTRA algorithm. The research in this study leverages radio resource allocation techniques in LTE based D2D communications to be utilized radio resources more efficiently. In addition, the conducted research paves a way to study further how the power-saving users would optimally select the radio resources with minimum energy consumption in NR V2X communications

Radio resource management for V2X in cellular systems

The thesis focuses on the provision of cellular vehicle-to-everything (V2X) communications, which have attracted great interest for 5G due to the potential of improving traffic safety and enabling new services related to intelligent transportation systems. These types of services have strict requirements on reliability, access availability, and end-to-end (E2E) latency. V2X requires advanced network management techniques that must be developed based on the characteristics of the networks and traffic requirements. The integration of the Sidelink (SL), which enables the direct communication between vehicles (i.e., vehicle-to-vehicle (V2V)) without passing through the base station into cellular networks is a promising solution for enhancing the performance of V2X in cellular systems. In this thesis, we addressed some of the challenges arising from the integration of V2V communication in cellular systems and validated the potential of this technology by providing appropriate resource management solutions. Our main contributions have been in the context of radio access network slicing, mode selection, and radio resource allocation mechanisms. With regard to the first research direction that focuses on the RAN slicing management, a novel strategy based on offline Q-learning and softmax decision-making has been proposed as an enhanced solution to determine the adequate split of resources between a slice for eMBB communications and a slice for V2X. Then, starting from the outcome of the off-line Q-learning algorithm, a low-complexity heuristic strategy has been proposed to achieve further improvements in the use of resources. The proposed solution has been compared against proportional and fixed reference schemes. The extensive performance assessment have revealed the ability of the proposed algorithms to improve network performance compared to the reference schemes, especially in terms of resource utilization, throughput, latency and outage probability. Regarding the second research direction that focuses on the mode selection, two different mode selection solutions referred to as MSSB and MS-RBRS strategies have been proposed for V2V communication over a cellular network. The MSSB strategy decides when it is appropriate to use one or the other mode, i.e. sidelink or cellular, for the involved vehicles, taking into account the quality of the links between V2V users, the available resources, and the network traffic load situation. Moreover, the MS-RBRS strategy not only selects the appropriate mode of operation but also decides efficiently the amount of resources needed by V2V links in each mode and allows reusing RBs between different SL users while guaranteeing the minimum signal to interference requirements. The conducted simulations have revealed that the MS-RBRS and MSSB strategies are beneficial in terms of throughput, radio resource utilization, outage probability and latency under different offered loads comparing to the reference scheme. Last, we have focused on the resource allocation problem including jointly mode selection and radio resource scheduling. For the mode selection, a novel mode selection has been presented to decide when it is appropriate to select sidelink mode and use a distributed approach for radio resource allocation or cellular mode and use a centralized radio resource allocation. It takes into account three aspects: the quality of the links between V2V users, the available resources, and the latency. As for the radio resource allocation, the proposed approach includes a distributed radio resource allocation for sidelink mode and a centralized radio resource allocation for cellular mode. The proposed strategy supports dynamic assignments by allowing transmission over mini-slots. A simulation-based analysis has shown that the proposed strategies improved the network performance in terms of latency of V2V services, packet success rate and resource utilization under different network loads.La tesis se centra en la provisión de comunicaciones para vehículos sistemas celulares (V2X: Vehicle to Everything), que han atraído un gran interés en el contexto de 5G debido a su potencial de mejorar la seguridad del tráfico y habilitar nuevos servicios relacionados con los sistemas inteligentes de transporte. Estos tipos de servicios tienen requisitos estrictos en términos fiabilidad, disponibilidad de acceso y latencia de extremo a extremo (E2E). Para ello, V2X requiere técnicas avanzadas de gestión de red que deben desarrollarse en función de las características de las redes y los requisitos de tráfico. La integración del Sidelink (SL), que permite la comunicación directa entre vehículos (es decir, vehículo a vehículo (V2V)) sin pasar por la estación base de las redes celulares, es una solución prometedora para mejorar el rendimiento de V2X en el sistema celular. En esta tesis, abordamos algunos de los desafíos derivados de la integración de la comunicación V2V en los sistemas celulares y validamos el potencial de esta tecnología al proporcionar soluciones de gestión de recursos adecuadas. Nuestras principales contribuciones han sido en el contexto del denominado "slicing" de redes de acceso radio, la selección de modo y los mecanismos de asignación de recursos radio. Respecto a la primera dirección de investigación que se centra en la gestión del RAN slicing, se ha propuesto una estrategia novedosa basada en Q-learning y toma de decisiones softmax como una solución para determinar la división adecuada de recursos entre un slice para comunicaciones eMBB y un slice para V2X. Luego, a partir del resultado del algoritmo de Q-learning, se ha propuesto una estrategia heurística de baja complejidad para lograr mejoras adicionales en el uso de los recursos. La solución propuesta se ha comparado con esquemas de referencia proporcionales y fijos. La evaluación ha revelado la capacidad de los algoritmos propuestos para mejorar el rendimiento de la red en comparación con los esquemas de referencia, especialmente en términos de utilización de recursos, rendimiento, y latencia . Con respecto a la segunda dirección de investigación que se centra en la selección de modo, se han propuesto dos soluciones de diferentes llamadas estrategias MSSB y MS-RBRS para la comunicación V2V a través de una red celular. La estrategia MSSB decide cuándo es apropiado usar el modo SL o el modo celular, para los vehículos involucrados, teniendo en cuenta la calidad de los enlaces entre los usuarios de V2V, los recursos disponibles y la situación de carga de tráfico de la red. Además, la estrategia MS-RBRS no solo selecciona el modo de operación apropiado, sino que también decide eficientemente la cantidad de recursos que los enlaces V2V necesitan en cada modo, y permite que los RB se reutilicen entre diferentes usuarios de SL al tiempo que garantiza requisitos mínimos de señal a interferencia. Se ha presentado un análisis basado en simulación para evaluar el desempeño de las estrategias propuestas. Finalmente, nos hemos centrado en el problema conjunto de la selección de modo y la asignación de recursos de radio. Para la selección de modo, se ha presentado una nueva estrategia para decidir cuándo es apropiado seleccionar el modo SL y usar un enfoque distribuido para la asignación de recursos de radio o el modo celular y usar la asignación de recursos de radio centralizada. Tiene en cuenta tres aspectos: la calidad de los enlaces entre los usuarios de V2V, los recursos disponibles y la latencia. En términos de asignación de recursos de radio, el enfoque propuesto incluye una asignación de recursos de radio distribuida para el modo SL y una asignación de recursos de radio centralizada para el modo celular. La estrategia propuesta admite asignaciones dinámicas al permitir la transmisión a través de mini-slots. Los resultados muestran las mejoras en términos de latencia, tasa de recepción y la utilización de recursos bajo diferentes cargas de red.Postprint (published version

Simu5G – An OMNeT++ library for end-to-end performance evaluation of 5G networks

In this paper we introduce Simu5G, a new OMNeT++-based model library to simulate 5G networks. Si-mu5G allows users to simulate the data plane of 5G New Radio deployments, in an end-to-end perspective and including all protocol layers, making it a valuable tool for researchers and practitioners interested in the performance evaluation of 5G networks and services. We discuss the modelling of the protocol layers, network entities and functions, and validate our abstraction of the physical layer using 3GPP-based sce-narios. Moreover, we show how Simu5G can be used to evaluate Multi-access Edge Computing (MEC) and Cellular Vehicle-to-everything (C-V2X) services offered through a 5G network

Open sub-granting radio resources in overlay D2D-based V2V communications

Capacity, reliability, and latency are seen as key requirements of new emerging applications, namely vehicle-to-everything (V2X) and machine-type communication in future cellular networks. D2D communication is envisaged to be the enabler to accomplish the requirements for the applications as mentioned earlier. Due to the scarcity of radio resources, a hierarchical radio resource allocation, namely the sub-granting scheme, has been considered for the overlay D2D communication. In this paper, we investigate the assignment of underutilized radio resources from D2D communication to device-to-infrastructure communication, which are moving in a dynamic environment. The sub-granting assignment problem is cast as a maximization problem of the uplink cell throughput. Firstly, we evaluate the sub-granting signaling overhead due to mobility in a centralized sub-granting resource algorithm, dedicated sub-granting radio resource (DSGRR), and then a distributed heuristics algorithm, open sub-granting radio resource (OSGRR), is proposed and compared with the DSGRR algorithm and no sub-granting case. Simulation results show improved cell throughput for the OSGRR compared with other algorithms. Besides, it is observed that the overhead incurred by the OSGRR is less than the DSGRR while the achieved cell throughput is yet close to the maximum achievable uplink cell throughput

A Survey on Resource Allocation in Vehicular Networks

Vehicular networks, an enabling technology for Intelligent Transportation System (ITS), smart cities, and autonomous driving, can deliver numerous on-board data services, e.g., road-safety, easy navigation, traffic efficiency, comfort driving, infotainment, etc. Providing satisfactory Quality of Service (QoS) in vehicular networks, however, is a challenging task due to a number of limiting factors such as erroneous and congested wireless channels (due to high mobility or uncoordinated channel-access), increasingly fragmented and congested spectrum, hardware imperfections, and anticipated growth of vehicular communication devices. Therefore, it will be critical to allocate and utilize the available wireless network resources in an ultra-efficient manner. In this paper, we present a comprehensive survey on resource allocation schemes for the two dominant vehicular network technologies, e.g. Dedicated Short Range Communications (DSRC) and cellular based vehicular networks. We discuss the challenges and opportunities for resource allocations in modern vehicular networks and outline a number of promising future research directions

D4.3 Final Report on Network-Level Solutions

Research activities in METIS reported in this document focus on proposing solutions to the network-level challenges of future wireless communication networks. Thereby, a large variety of scenarios is considered and a set of technical concepts is proposed to serve the needs envisioned for the 2020 and beyond. This document provides the final findings on several network-level aspects and groups of solutions that are considered essential for designing future 5G solutions. Specifically, it elaborates on: -Interference management and resource allocation schemes -Mobility management and robustness enhancements -Context aware approaches -D2D and V2X mechanisms -Technology components focused on clustering -Dynamic reconfiguration enablers These novel network-level technology concepts are evaluated against requirements defined by METIS for future 5G systems. Moreover, functional enablers which can support the solutions mentioned aboveare proposed. We find that the network level solutions and technology components developed during the course of METIS complement the lower layer technology components and thereby effectively contribute to meeting 5G requirements and targets.Aydin, O.; Valentin, S.; Ren, Z.; Botsov, M.; Lakshmana, TR.; Sui, Y.; Sun, W.... (2015). D4.3 Final Report on Network-Level Solutions. http://hdl.handle.net/10251/7675