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

Smart Sensing and Performance Analysis for Cognitive Radio Networks

Static spectrum access policy has resulted in spectrum scarcity as well as low spectrum utility in today\u27s wireless communications. To utilize the limited spectrum more efficiently, cognitive radio networks have been considered a promising paradigm for future network. Due to the unique features of cognitive radio technology, cognitive radio networks not only raise new challenges, but also bring several fundamental problems back to the focus of researchers. So far, a number of problems in cognitive radio networks have remained unsolved over the past decade. The work presented in this dissertation attempts to fill some of the gaps in the research area of cognitive radio networks. It focuses primarily on spectrum sensing and performance analysis in two architectures: a single cognitive radio network and multiple co-existing cognitive radio networks. Firstly, a single cognitive radio network with one primary user is considered. A weighted cooperative spectrum sensing framework is designed, to increase the spectrum sensing accuracy. After studying the architecture of a single cognitive radio network, attention is shifted to co-existing multiple cognitive radio networks. The weakness of the conventional two-state sensing model is pointed out in this architecture. To solve the problem, a smart sensing model which consists of three states is designed. Accordingly, a method for a two-stage detection procedure is developed to accurately detect each state of the three. In the first stage, energy detection is employed to identify whether a channel is idle or occupied. If the channel is occupied, received signal is further analyzed at the second stage to determine whether the signal originates from a primary user or an secondary user. For the second stage, a statistical model is developed, which is used for distance estimation. The false alarm and miss detection probabilities for the spectrum sensing technology are theoretically analyzed. Then, how to use smart sensing, coupled with a designed media access control protocol, to achieve fairness among multiple CRNs is thoroughly investigated. The media access control protocol fully takes the PU activity into account. Afterwards, the significant performance metrics including throughput and fairness are carefully studied. In terms of fairness, the fairness dynamics from a micro-level to macro-level is evaluated among secondary users from multiple cognitive radio networks. The fundamental distinctions between the two-state model and the three-state sensing model are also addressed. Lastly, the delay performance of a cognitive radio network supporting heterogeneous traffic is examined. Various delay requirements over the packets from secondary users are fully considered. Specifically, the packets from secondary users are classified into either delay-sensitive packets or delay-insensitive packets. Moreover, a novel relative priority strategy is designed between these two types of traffic by proposing a transmission window strategy. The delay performance of both a single-primary user scenario and a multiple-primary user scenario is thoroughly investigated by employing queueing theory

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

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

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

Analytical Modelling of Scheduling Schemes under Self-similar Network Traffic. Traffic Modelling and Performance Analysis of Centralized and Distributed Scheduling Schemes.

High-speed transmission over contemporary communication networks has drawn many research efforts. Traffic scheduling schemes which play a critical role in managing network transmission have been pervasively studied and widely implemented in various practical communication networks. In a sophisticated communication system, a variety of applications co-exist and require differentiated Quality-of-Service (QoS). Innovative scheduling schemes and hybrid scheduling disciplines which integrate multiple traditional scheduling mechanisms have emerged for QoS differentiation. This study aims to develop novel analytical models for commonly interested scheduling schemes in communication systems under more realistic network traffic and use the models to investigate the issues of design and development of traffic scheduling schemes. In the open literature, it is commonly recognized that network traffic exhibits self-similar nature, which has serious impact on the performance of communication networks and protocols. To have a deep study of self-similar traffic, the real-world traffic datasets are measured and evaluated in this study. The results reveal that selfsimilar traffic is a ubiquitous phenomenon in high-speed communication networks and highlight the importance of the developed analytical models under self-similar traffic. The original analytical models are then developed for the centralized scheduling schemes including the Deficit Round Robin, the hybrid PQGPS which integrates the traditional Priority Queueing (PQ) and Generalized Processor Sharing (GPS) schemes, and the Automatic Repeat reQuest (ARQ) forward error control discipline in the presence of self-similar traffic. Most recently, research on the innovative Cognitive Radio (CR) techniques in wireless networks is popular. However, most of the existing analytical models still employ the traditional Poisson traffic to examine the performance of CR involved systems. In addition, few studies have been reported for estimating the residual service left by primary users. Instead, extensive existing studies use an ON/OFF source to model the residual service regardless of the primary traffic. In this thesis, a PQ theory is adopted to investigate and model the possible service left by selfsimilar primary traffic and derive the queue length distribution of individual secondary users under the distributed spectrum random access protocol