Vehicular Dynamic Spectrum Access: Using Cognitive Radio for Automobile Networks

Vehicular Dynamic Spectrum Access (VDSA) combines the advantages of dynamic spectrum access to achieve higher spectrum efficiency and the special mobility pattern of vehicle fleets. This dissertation presents several noval contributions with respect to vehicular communications, especially vehicle-to-vehicle communications. Starting from a system engineering aspect, this dissertation will present several promising future directions for vehicle communications, taking into consideration both the theoretical and practical aspects of wireless communication deployment. This dissertation starts with presenting a feasibility analysis using queueing theory to model and estimate the performance of VDSA within a TV whitespace environment. The analytical tool uses spectrum measurement data and vehicle density to find upper bounds of several performance metrics for a VDSA scenario in TVWS. Then, a framework for optimizing VDSA via artificial intelligence and learning, as well as simulation testbeds that reflect realistic spectrum sharing scenarios between vehicle networks and heterogeneous wireless networks including wireless local area networks and wireless regional area networks. Detailed experimental results justify the testbed for emulating a mobile dynamic spectrum access environment composed of heterogeneous networks with four dimensional mutual interference. Vehicular cooperative communication is the other proposed technique that combines the cooperative communication technology and vehicle platooning, an emerging concept that is expected to both increase highway utilization and enhance both driver experience and safety. This dissertation will focus on the coexistence of multiple vehicle groups in shared spectrum, where intra-group cooperation and inter-group competition are investigated in the aspect of channel access. Finally, a testbed implementation VDSA is presented and a few applications are developed within a VDSA environment, demonstrating the feasibility and benefits of some features in a future transportation system

Parallelising reception and transmission in queues of secondary users

In a cognitive radio network, the secondary users place the packets to be transmitted on a queue to control the order of arrival and to adapt to the network state. Previous conceptionsassigned to each secondary user a single queue that contains both received and forwarded packets. Our present article divides the main queue into two sub queues: one to receive the arrived packets and the other to transmit the available packets. This approach reduces the transmission delay due on the one hand; to the shifting of data placed on the single queue, and on the other hand; to the sequential processing of reception and transmission, in theprevious designs. All without increasing the memory capacity of the queue, in the new approach

Channel Selection Algorithms for Cognitive Radio Systems

The Spectrum of Radio Frequency plays a key/central role in supporting the operation of the whole range of mobile wireless devices. Such centrality derives from the fact it is necessary when operating different technologies, such as TV, cellular networks, and satellite transmissions, among others. Hence, the urgent need to design a better management of these technologies as a means of minimizing the amount spectrum that is used. This study was developed in two different stages. During a preliminary stage we came up with a modelling method of the service time duration in cognitive radio networks, which fosters a better management of the spectrum through its opportunistic use. In a second stage, we propose four algorithms to manage these cognitive radio networks, using the modelling method that was defined in the first stage, as a basis. After implementing all the simulations, it was possible to verify the feasibility of this modelling methodology and also to confirm the expected results. It should also be pointed out that the four suggested algorithms were tested by carrying out simulations, being effective solutions for difference operational scenarios

Priority queueing models for cognitive radio networks with traffic differentiation

In this paper, we present a new queueing model providing the accurate average system time for packets transmitted over a cognitive radio (CR) link for multiple traffic classes with the preemptive and non-preemptive priority service disciplines. The analysis considers general packet service time, general distributions for the channel availability periods and service interruption periods, and a service-resume transmission. We further introduce and analyze two novel priority service disciplines for opportunistic spectrum access (OSA) networks which take advantage of interruptions to preempt low priority traffic at a low cost. Analytical results, in addition to simulation results to validate their accuracy, are also provided and used to illustrate the impact of different OSA network parameters on the average system time. We particularly show that, for the same average CR transmission link availability, the packet system time significantly increases in a semi-static network with long operating and interruption periods compared to an OSA network with fast alternating operating and interruption periods. We also present results indicating that, due to the presence of interruptions, priority queueing service disciplines provide a greater differentiated service in OSA networks than in traditional networks. The analytical tools presented in this paper are general and can be used to analyze the traffic metrics of most OSA networks carrying multiple classes of traffic with priority queueing service differentiation

Non-Cooperative Spectrum Access -- The Dedicated vs. Free Spectrum Choice

We consider a dynamic spectrum access system in which Secondary Users (SUs) choose to either acquire dedicated spectrum or to use spectrum-holes (white spaces) which belong to Primary Users (PUs). The trade-off incorporated in this decision is between immediate yet costly transmission and free but delayed transmission (a consequence of both the possible appearance of PUs and sharing the spectrum holes with multiple SUs). We first consider a system with a single PU band, in which the SU decisions are fixed. Employing queueing-theoretic methods, we obtain explicit expressions for the expected delays associated with using the PU band. Based on that, we then consider self-interested SUs and study the interaction between them as a non-cooperative game. We prove the existence and uniqueness of a symmetric Nash equilibrium, and characterize the equilibrium behavior explicitly. Using our equilibrium results, we show how to maximize revenue from renting dedicated bands to SUs and briefly discuss the extension of our model to multiple PUs. Finally, since spectrum sensing can be resource-consuming, we characterize the gains provided by this capability.National Science Foundation (U.S.) (Grant CNS-0915988)National Science Foundation (U.S.) (Grant CNS-0916263)National Science Foundation (U.S.) (Grant CNS-1054856)National Science Foundation (U.S.). Engineering Research Centers Program (Center for Integrated Access Networks Grant EEC-0812072)United States. Office of Naval Research (Grant N00014-12-1-0064)United States. Army Research Office. Multidisciplinary University Research Initiative (Grant W911NF-08-1-0238

Reliability and Quality of Service in Opportunistic Spectrum Access

RÉSUMÉ Les réseaux radio-cognitif constituent une des meilleures options technologiques pour les réseaux sans-fil futurs. Afin d’étudier comment la fiabilité devrait être redéfinie dans ces réseaux, nous étudions d'abord les sources les plus fréquentes de panne dans les réseaux sans-fil et fournissons une procédure systématique de classement des pannes. Il est ensuite expliqué comment les radios cognitives peuvent profiter de leur propre capacité à mettre en œuvre des mécanismes efficaces de prévention et de récupération contre les pannes et ainsi assurer des communications sans-fil fiables et de qualité de service constante. En considérant des normes arrivantes sur la base de l'OSA, ce qui distingue un réseau radio-cognitif de ses prédécesseurs est des changements fréquents de canal ainsi que de nouvelles exigences telles la détection de disponibilité et la décision d'utilisation du spectre. Nous nous concentrons sur cet aspect et modélisons la remise du spectre comme une panne. Par conséquent, améliorer la fiabilité est équivalent à augmenter le temps moyen entre pannes, à rendre plus efficace le processus de récupération et à réduire le temps moyen de réparation. Nous étudions donc d'abord l'impact du temps de récupération sur la performance du réseau radio-cognitif. En classifiant les pannes en dures et souples, il est examiné comment la disponibilité, le temps moyen entre pannes et le temps moyen jusqu'à la réparation sont touchés par le procès de récupération. Nous observons que le temps dépensé pour la récupération empêche le réseau d'atteindre le maximum de disponibilité. Par conséquent, pour obtenir un temps plus élevé entre pannes et un temps de réparation plus court, une option disponible est d'augmenter le nombre de canaux pouvant être utilisés par le réseau radio-cognitif, de sorte que, avec une haute probabilité, un utilisateur qui a raté le canal puisse trouver bientôt un nouveau canal. De l'autre côté, un mécanisme de récupération efficace est nécessaire pour mieux profiter de ce grand nombre de canaux; l'amélioration de la récupération est donc indispensable. Pour étudier l'impact de la récupération sur les couches plus hautes (e.g., la couche liaison et réseau), l’approche de l’analyse de file d'attente est choisie. Compte tenu des périodes de récupération comme une interruption de service, un modèle général de file d'attente de M/G/1 avec des interruptions est proposé. Différents paramètres de fiabilité et de qualité de service peuvent être trouvés à partir de ce modèle de file d'attente pour étudier comment la spécification des canaux, tels la distribution des périodes de disponibilité et d'indisponibilité, et la spécification de l'algorithme de récupération, tels la durée de récupération, affectent les paramètres de performance comme la perte de paquets, de retard et de gigue, et aussi le temps entre pannes. Pour soutenir la différenciation des classes de trafic, nous proposons une approche de file d'attente avec priorité. Nous proposons une extension des résultats du modèle de file d'attente générale et présentons quatre différentes disciplines de file d'attente de priorité, allant d'un régime préemptif absolu à un régime complètement non préemptif. Les nouvelles disciplines augmentent la flexibilité et la résolution de décision et permettent au noeud CR de contrôler l'interaction des différentes classes de trafic avec plus de précision.---------- ABSTRACT Cognitive-radio based wireless networks are a technology of choice for incoming wireless networks. To investigate how reliability should be redefined for these networks, we study the most common sources of failure in wireless networks and provide a systematic failure classification procedure. It is then explained how cognitive radios can use their inherent capabilities to implement efficient prevention and recovery mechanisms to combat failures and thereby provide more reliable communications and consistent quality of service in wireless networks. Considering incoming OSA-based standards, what distinguishes a cognitive radio network from its predecessors is the frequent spectrum handovers along with new requirements such as spectrum sensing and spectrum usage decision. We thus focus on this aspect and model the spectrum handover as a failure, so improving the reliability is equivalent to increasing the mean time to failure, improving the recovery process and shortening the mean time to repair. We first study the impact of the recovery time on the performance of the cognitive radio network. By classifying the failures into hard and soft, it is investigated how the availability, mean time to failure and mean time to repair are affected by the recovery time. It is observed that the time spent for recovery prevents the network from reaching the maximum availability. Therefore, to achieve a high mean time to hard failure and low mean time to repair, an available option is to increase the number of channels, so that with a high probability, a user who missed the channel can soon find a new channel. On the other side, an efficient recovery scheme is required to better take advantage of a large number of channels. Recovery improvement is thus indispensable. To study the impact of recovery on higher communication layers, a queueing approach is chosen. Considering the recovery periods as a service interruption, a general M/G/1 queueing model with interruption is proposed. Different reliability and quality of service parameters can be found from this queueing model to investigate how channel parameters, such as availability and unavailability periods, and the recovery algorithm specifications, such as the recovery duration, affect packet loss, delay and jitter, and also the MTTF and MTTR for hard and soft failures. To support traffic differentiation, we suggest a priority queueing approach. We extend the results of the general queueing model and discuss four different priority queueing disciplines ranging from a pure preemptive scheme to a pure non-preemptive scheme. New disciplines increase the flexibility and decision resolution and enable the CR node to more accurately control the interaction of different classes of traffic. The models are solved, so it can be analyzed how the reliability and quality of service parameters, such as delay and jitter, for a specific class of traffic are affected not only by the channel parameters, but also by the characteristics of other traffic classes. The M/G/1 queueing model with interruptions is a foundation for performance analysis and an answer to the need of having closed-form analytical relations. We then extend the queueing model to more realistic scenarios, first with heterogeneous channels (heterogeneous service rate for different channels) and second with multiple users and a random medium access model

EUROPEAN CONFERENCE ON QUEUEING THEORY 2016

International audienceThis booklet contains the proceedings of the second European Conference in Queueing Theory (ECQT) that was held from the 18th to the 20th of July 2016 at the engineering school ENSEEIHT, Toulouse, France. ECQT is a biannual event where scientists and technicians in queueing theory and related areas get together to promote research, encourage interaction and exchange ideas. The spirit of the conference is to be a queueing event organized from within Europe, but open to participants from all over the world. The technical program of the 2016 edition consisted of 112 presentations organized in 29 sessions covering all trends in queueing theory, including the development of the theory, methodology advances, computational aspects and applications. Another exciting feature of ECQT2016 was the institution of the Takács Award for outstanding PhD thesis on "Queueing Theory and its Applications"

Influence of various application types on the performance of LTE mobile networks

Modern mobile internet networks are becoming heavier and denser. Also it is not regularly planned, and becoming more heterogeneous. The explosive growth in the usage of smartphones poses numerous challenges for LTE cellular networks design and implementation. The performance of LTE networks with bursty and self-similar traffic has become a major challenge. Accurate modeling of the data generated by each connected wireless device is important for properly investigating the performance of LTE networks. This paper presents a mathematical model for LTE networks using queuing theory considering the influence of various application types. Using sporadic source traffic feeding to the queue of the evolved node B and with the exponential service time assumption, we construct a queuing model to estimate the performance of LTE networks. We use the performance model presented in this paper to study the influence of various application categories on the performance of LTE cellular networks. Also we validate our model with simulation using NS3 simulator with different scenarios

Spatiotemporal characterization of users' experience in massive cognitive radio networks

The need to capture the actual network traf c condition and fundamental queueing dynamics in a massive cognitive radio network (CRN) is important for proper analysis of the intrinsic effects of spatial distribution while capturing the essential temporal distribution properties of the network. In massive CRN, many users, including primary and secondary users, transmit on scarce spectrum resources. While primary users (PUs) are delay-sensitive users that require prioritized access over secondary users (SUs), carrying out analysis that captures this property becomes imperative if users' service experience is to be satisfactory. This paper presents priority conscious spatiotemporal analysis capable of characterizing users' experience in massive CRN. Users in the primary priority queue were considered to have pre-emptive priory over users in the virtual and secondary priority queues. A Geo/G/1 discrete-time Markov chain queueing system was adopted to characterize both primary and secondary priority queues, while the virtual priority queue was analyzed as part of the secondary priority queue. Using the tools of stochastic geometry and queueing theory, the user's coverage probability was determined while the delay experienced by each class of users in the network was obtained using existing results. Through the obtained delay for each class of users in the network, the corresponding quality of service was also obtained. The results obtained show that the proposed framework is capable of accurately characterizing users' service experience in massive CRN.The SENTECH Chair in Broadband Wireless Multimedia Communications (BWMC), Department of Electrical, Electronics, and Computer Engineering, University of Pretoria, South Africa.http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=6287639am2020Electrical, Electronic and Computer Engineerin