648 research outputs found
Dynamic Pricing in Heterogeneous Wireless Cellular Networks
Smart communications devices are giving users instant access to applications that consume large amounts of data. These applications have different requirements on the network for delivery of data. In order to support these different applications, operators are required to support multiple service classes.
Given the regulatory and technology constraints and the relatively high cost associated with wireless spectrum licensing and utilization, demand will exceed supply leading to congestion and overload conditions. In addition to new broadband radio technologies offering higher data rates, operators are looking at deploying alternate heterogeneous technologies, such as WLAN, to provide additional bandwidth for serving customers. It is expected that this will still fall short of providing enough network resources to meet the ITU requirement for 1% new call blocking probability. An economic mechanism that offers incentives to individuals for rational behavior is required in order in order to reduce the demand for network resources and resolve the congestion problem.
The research in this dissertation demonstrates that the integration of a dynamic pricing with connection admission control mechanism for an operator deploying cooperative heterogeneous networks (e.g., LTE and WLAN) offering multiple QoS service classes reduces the new call blocking probability to the required 1% level.
The experimental design consisted, first, of an analytical model of the CAC algorithm with dynamic pricing in a heterogeneous environment. The analytical model was subsequently validated through discrete-event simulation using Matlab
Robust distributed resource allocation for cellular vehicle-to-vehicle communication
Mit Release 14 des LTE Standards unterstützt dieser die direkte Fahrzeug-zu-Fahrzeug-Kommunikation über den Sidelink. Diese Dissertation beschäftigt sich mit dem Scheduling Modus 4, einem verteilten MAC-Protokoll ohne Involvierung der Basisstation, das auf periodischer Wiederverwendung von Funkressourcen aufbaut. Der Stand der Technik und eine eigene Analyse des Protokolls decken verschiedene Probleme auf. So wiederholen sich Kollisionen von Paketen, wodurch manche Fahrzeuge für längere Zeit keine sicherheitskritischen Informationen verbreiten können. Kollisionen entstehen vermehrt auch dadurch, dass Hidden-Terminal-Probleme in Kauf genommen werden oder veränderliche Paketgrößen und -raten schlecht unterstützt werden. Deshalb wird ein Ansatz namens "Scheduling based on Acknowledgement Feedback Exchange" vorgeschlagen. Zunächst wird eine Funkreservierung in mehrere ineinander verschachtelte Unter-Reservierungen mit verschiedenen Funkressourcen unterteilt, was die Robustheit gegenüber wiederholenden Kollisionen erhöht. Dies ist die Grundlage für eine verteilte Staukontrolle, die die Periodizitätseigenschaft nicht verletzt. Außerdem können so veränderliche Paketgrößen oder -raten besser abgebildet werden. Durch die periodische Wiederverwendung können Acknowledgements für Funkressourcen statt für Pakete ausgesendet werden. Diese können in einer Bitmap in den Padding-Bits übertragen werden. Mittels der Einbeziehung dieser Informationen bei der Auswahl von Funkressourcen können Hidden-Terminal-Probleme effizient vermieden werden, da die Acknowledgements auch eine Verwendung dieser Funkressource ankündigen. Kollisionen können nun entdeckt und eine Wiederholung vermieden werden. Die Evaluierung des neuen MAC-Protokolls wurde zum großen Teil mittels diskreter-Event-Simulationen durchgeführt, wobei die Bewegung jedes einzelnen Fahrzeuges simuliert wurde. Der vorgeschlagene Ansatz führt zu einer deutlich erhöhten Paketzustellrate. Die Verwendung einer anwendungsbezogenen Awareness-Metrik zeigt, dass die Zuverlässigkeit der Kommunikation durch den Ansatz deutlich verbessert werden kann. Somit zeigt sich der präsentierte Ansatz als vielversprechende Lösung für die erheblichen Probleme, die der LTE Modus 4 mit sich bringt.The LTE Standard added support for a direct vehicle-to-vehicle communication via the Sidelink with Release 14. This dissertation focuses on the scheduling Mode 4, a distributed MAC protocol without involvement of the base station, which requires the periodic reuse of radio resources. The state of the art and a own analysis of this protocol unveil multiple problems. For example, packet collisions repeat in time, so that some vehicles are unable to distribute safety-critical information for extended periods of time. Collisions also arise due to the hidden-terminal problem, which is simply put up with in Mode 4. Additionally, varying packet sizes or rates can hardly be supported. Consequently, an approach called "Scheduling based on Acknowledgement Feedback Exchange" is proposed. Firstly, a reservation of radio resources is split into multiple, interleaved sub-reservations that use different radio resources. This increases the robustness against repeating collisions. It is also the basis for a distributed congestion control that does not violate the periodicity. Moreover, different packet rates or sizes can be supported. The periodic reuse of radio resources enables the transmission of acknowledgements for radio resources instead of packets. These can be transmitted in a bitmap inside the padding bits. Hidden-terminal problems can be mitigated by considering the acknowledgements when selecting radio resources as they announce the use of these radio resources. Collisions can also be detected and prevented from re-occurring. The evaluation of the MAC protocol is mostly performed using discrete-event simulations, which model the movement of every single vehicle. The presented approach leads to a clear improvement of the packet delivery rate. The use of an application-oriented metric shows that the communication robustness can be improved distinctly. The proposed approach hence presents itself as a promising solution for the considerable problems of LTE Mode 4
A survey on vehicular communication for cooperative truck platooning application
Platooning is an application where a group of vehicles move one after each other in close proximity, acting jointly as a single physical system. The scope of platooning is to improve safety, reduce fuel consumption, and increase road use efficiency. Even if conceived several decades ago as a concept, based on the new progress in automation and vehicular networking platooning has attracted particular attention in the latest years and is expected to become of common implementation in the next future, at least for trucks.The platoon system is the result of a combination of multiple disciplines, from transportation, to automation, to electronics, to telecommunications. In this survey, we consider the platooning, and more specifically the platooning of trucks, from the point of view of wireless communications. Wireless communications are indeed a key element, since they allow the information to propagate within the convoy with an almost negligible delay and really making all vehicles acting as one. Scope of this paper is to present a comprehensive survey on connected vehicles for the platooning application, starting with an overview of the projects that are driving the development of this technology, followed by a brief overview of the current and upcoming vehicular networking architecture and standards, by a review of the main open issues related to wireless communications applied to platooning, and a discussion of security threats and privacy concerns. The survey will conclude with a discussion of the main areas that we consider still open and that can drive future research directions.(c) 2022 The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)
Synergizing Roadway Infrastructure Investment with Digital Infrastructure for Infrastructure-Based Connected Vehicle Applications: Review of Current Status and Future Directions
The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.The safety, mobility, environmental and economic benefits of Connected and Autonomous Vehicles (CAVs) are potentially dramatic. However, realization of these benefits largely hinges on the timely upgrading of the existing transportation system. CAVs must be enabled to send and receive data to and from other vehicles and drivers (V2V communication) and to and from infrastructure (V2I communication). Further, infrastructure and the transportation agencies that manage it must be able to collect, process, distribute and archive these data quickly, reliably, and securely. This paper focuses on current digital roadway infrastructure initiatives and highlights the importance of including digital infrastructure investment alongside more traditional infrastructure investment to keep up with the auto industry's push towards this real time communication and data processing capability. Agencies responsible for transportation infrastructure construction and management must collaborate, establishing national and international platforms to guide the planning, deployment and management of digital infrastructure in their jurisdictions. This will help create standardized interoperable national and international systems so that CAV technology is not deployed in a haphazard and uncoordinated manner
A survey of machine learning techniques applied to self organizing cellular networks
In this paper, a survey of the literature of the past fifteen years involving Machine Learning (ML) algorithms applied to self organizing cellular networks is performed. In order for future networks to overcome the current limitations and address the issues of current cellular systems, it is clear that more intelligence needs to be deployed, so that a fully autonomous and flexible network can be enabled. This paper focuses on the learning perspective of Self Organizing Networks (SON) solutions and provides, not only an overview of the most common ML techniques encountered in cellular networks, but also manages to classify each paper in terms of its learning solution, while also giving some examples. The authors also classify each paper in terms of its self-organizing use-case and discuss how each proposed solution performed. In addition, a comparison between the most commonly found ML algorithms in terms of certain SON metrics is performed and general guidelines on when to choose each ML algorithm for each SON function are proposed. Lastly, this work also provides future research directions and new paradigms that the use of more robust and intelligent algorithms, together with data gathered by operators, can bring to the cellular networks domain and fully enable the concept of SON in the near future
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