Cognitive radios (CRs) are devices that are capable of sensing the spectrum and using its free portions in an opportunistic manner. The free spectrum portions are referred to as white spaces or spectrum holes. It is widely believed that CRs are one of the key enabling technologies for realizing a new regulatory spectrum management paradigm, viz. dynamic spectrum access (DSA). CRs often employ software-defined radio (SDR) platforms that are capable of executing artificial intelligence (AI) algorithms to reconfigure their transmission/reception (TX/RX) parameters to communicate efficiently while avoiding interference with licensed (a.k.a. primary or incumbent) users and unlicensed (a.k.a. secondary or cognitive) users. When different stakeholders share a common resource, such as the case in spectrum sharing, security, privacy, and enforcement become critical considerations that affect the welfare of all stakeholders. Recent advances in radio spectrum access technologies, such as CRs, have made spectrum sharing a viable option for significantly improving spectrum utilization efficiency. However, those technologies have also contributed to exacerbating the difficult problems of security, privacy and enforcement. In this dissertation, we review some of the critical security and privacy threats that impact spectrum sharing. We also discuss ex ante (preventive) approaches which mitigate the security and privacy threats and help spectrum enforcement. / Ph. D.

Cognitive radio (CR) is seen as one of the enabling technologies for realizing a new regulatory spectrum management paradigm, viz. opportunistic spectrum sharing (OSS). In the OSS paradigm, unlicensed users (a.k.a. secondary users) opportunistically operate in fallow licensed spectrum on a non-interference basis to licensed users (a.k.a. incumbent or primary users). Incumbent users have absolute priority in licensed bands, and secondary users must vacate the channel where incumbent user signals are detected. A CR network is composed of secondary users equipped with CRs and it can coexist with incumbent users in licensed bands under the OSS paradigm. The coexistence between incumbent users and secondary users is referred to as incumbent coexistence, and the coexistence between CR networks of the same type is referred to as self-coexistence. In this dissertation, we address three coexistence-related problems at the medium access control (MAC) layer in CR networks: (1) the rendezvous (control channel) establishment problem, (2) the channel assignment problem in an ad hoc CR network, and (3) the spectrum sharing problem between infrastructure-based CR networks, i.e., the 802.22 wireless regional area networks (WRANs). Existing MAC layer protocols in conventional wireless networks fail to adequately address the key issues concerning incumbent and self coexistence that emerge in CR networks. To solve the rendezvous establishment problem, we present a systematic approach, based on quorum systems, for designing channel hopping protocols that ensure a pair of CRs to "rendezvous" within an upper-bounded time over a common channel that is free of incumbent user signals. In a single radio interface, ad hoc CR network, we propose a distributed channel assignment scheme that assigns channels at the granularity of "segments" for minimizing the channel switching overhead. By taking into account the coexistence requirements, we propose an inter-network spectrum sharing protocol that enables the sharing of vacant TV white space among coexisting WRANs. Our analytical and simulation results show that these proposed schemes can effectively address the aforementioned MAC layer coexistence problems in CR networks. / Ph. D.

Dynamic spectrum access (DSA) technique has been widely accepted as a crucial solution to mitigate the potential spectrum scarcity problem. Spectrum sharing between the government incumbents and commercial wireless broadband operators/users is one of the key forms of DSA. Two categories of spectrum management methods for shared use between incumbent users (IUs) and secondary users (SUs) have been proposed, i.e., the server-driven method and the sensing-based method. The server-driven method employs a central server to allocate spectrum resources while considering incumbent protection. The central server has access to the detailed IU operating information, and based on some accurate radio propagation model, it is able to allocate spectrum following a particular access enforcement method. Two types of access enforcement methods -- exclusion zone and protection zone -- have been adopted for server-driven DSA systems in the current literature. The sensing-based method is based on recent advances in cognitive radio (CR) technology. A CR can dynamically identify white spaces through various incumbent detection techniques and reconfigure its radio parameters in response to changes of spectrum availability. The focus of this dissertation is to address critical privacy and security issues in the existing DSA systems that may severely hinder the progress of DSA's deployment in the real world. Firstly, we identify serious threats to users' privacy in existing server-driven DSA designs and propose a privacy-preserving design named P²-SAS to address the issue. P²-SAS realizes the complex spectrum allocation process of protection-zone-based DSA in a privacy-preserving way through Homomorphic Encryption (HE), so that none of the IU or SU operation data would be exposed to any snooping party, including the central server itself. Secondly, we develop a privacy-preserving design named IP-SAS for the exclusion-zone- based server-driven DSA system. We extend the basic design that only considers semi- honest adversaries to include malicious adversaries in order to defend the more practical and complex attack scenarios that can happen in the real world. Thirdly, we redesign our privacy-preserving SAS systems entirely to remove the somewhat- trusted third party (TTP) named Key Distributor, which in essence provides a weak proxy re-encryption online service in P²-SAS and IP-SAS. Instead, in this new system, RE-SAS, we leverage a new crypto system that supports both a strong proxy re-encryption notion and MPC to realize privacy-preserving spectrum allocation. The advantages of RE-SAS are that it can prevent single point of vulnerability due to TTP and also increase SAS's service performance dramatically. Finally, we identify the potentially crucial threat of compromised CR devices to the ambient wireless infrastructures and propose a scalable and accurate zero-day malware detection system called GuardCR to enhance CR network security at the device level. GuardCR leverages a host-based anomaly detection technique driven by machine learning, which makes it autonomous in malicious behavior recognition. We boost the performance of GuardCR in terms of accuracy and efficiency by integrating proper domain knowledge of CR software. / Ph. D.

This dissertation presents an empirical approach to identifying decisions for adapting cognitive radio parameters with no a priori knowledge of the environment. Cognitively inspired radios, attempt to combine observed metrics of system performance with artificial intelligence decision-making algorithms. Current architectures trend towards hybrid combinations of heuristics, such as genetic algorithms (GA) and experiential methods, such as case-based reasoning (CBR). A weakness in the GA is its reliance on limited mathematical models for estimating bit error rate, packet error rate, throughput, and signal-to-noise ratio. The CBR approach is similarly limited by its dependency on past experiences. Both methods have potential to suffer in environments not previously encountered. In contrast, the statistical methods identify performance estimation models based on exercising defined experimental designs. This represents an experiential decision-making process formed in the present rather than the past. There are three core contributions from this empirical framework: 1) it enables a new approach to decision making based on empirical estimation models of system performance, 2) it provides a systematic method for initializing cognitive engine configuration parameters, and 3) it facilitates deeper understanding of system behavior by quantifying parameter significance, and interaction effects. Ultimately, this understanding enables simplification of system models by identifying insignificant parameters. This dissertation defines an abstract framework that enables application of statistical approaches to cognitive radio systems regardless of its platform or application space. Specifically, it assesses factorial design of experiments and response surface methodology (RSM) to an over-the-air wireless radio link. Results are compared to a benchmark GA cognitive engine. The framework is then used for identifying software-defined radio initialization settings. Taguchi designs, a related statistical method, are implemented to identify initialization settings of a GA. / Ph. D.

Dynamic spectrum access (DSA) wireless networks focus on using RF spectrum more efficiently and dynamically. Significant progress has been made during the past few years. For example, many measurements of current spectrum utilization are available. Theoretical analyses and computational simulations of DSA networks also abound. In sharp contrast, few network systems, particularly those with a decentralized structure, have been built even at a small scale to investigate the performance, behavior, and dynamics of DSA networks under different scenarios. This dissertation provides the theory, design, and implementation of a software radio-based decentralized DSA network prototype, and its enabling technologies: software radio, signal detection and classification, and distributed cooperative spectrum sensing. By moving physical layer functions into the software domain, software radio offers an unprecedented level of flexibility in radio development and operation, which can facilitate research and development of cognitive radio (CR) and DSA networks. However, state-of-the-art software radio systems still have serious performance limitations. Therefore, a performance study of software radio is needed before applying it in any development. This dissertation investigates three practical issues governing software radio performance that are critical in DSA network development: RF front end nonlinearity, dynamic computing resource allocation, and execution latency. It provides detailed explanations and quantitative results on SDR performance. Signal detection is the most popular method used in DSA networks to guarantee non-interference to primary users. Quickly and accurately detecting signals under all possible conditions is challenging. The cyclostationary feature detection method is attractive for detecting primary users because of its ability to distinguish between modulated signals, interference, and noise at a low signal-to-noise ratio (SNR). However, a key issue of cyclostationary signal analysis is the high computational cost. To tackle this challenge, parallel computing is applied to develop a cyclostationary feature based signal detection method. This dissertation presents the method's performance on multiple signal types in noisy and multi-path fading environments. Distributed cooperative spectrum sensing is widely endorsed to monitor the radio environment so as to guarantee non-interference to incumbent users even at a low SNR and under hostile conditions like shadowing, fading, interference, and multi-path. However, such networks impose strict performance requirements on data latency and reliability. Delayed or faulty data may cause secondary users to interfere with incumbent users because secondary users could not be informed quickly or reliably. To support such network performance, this dissertation presents a set of data process and management schemes in both sensors and data fusion nodes. Further, a distributed cooperative sensor network is built from multiple sensors; together, the network compiles a coherent semantic radio environment map for DSA networks to exploit available frequencies opportunistically. Finally, this dissertation presents the complete design of a decentralized and asynchronous DSA network across the PHY layer, MAC layer, network layer, and application layer. A ten-node prototype is built based on software radio technologies, signal detection and classification methods, distributed cooperative spectrum sensing systems, dynamic wireless protocols, and a multi-channel allocation algorithm. Systematic experiments are carried out to identify several performance determining factors for decentralized DSA networks. / Ph. D.

Machine-to-Machine (M2M) communications is an emerging communication paradigm that provides ubiquitous connectivity between devices along with an ability to communicate autonomously without human intervention. M2M communications acts as an enabling technology for the practical realization of Internet-of-Things (IoT). However, M2M communications differs from conventional Human-to-Human (H2H) communications due to its unique features such as massive number of connected devices, small data transmissions, little or no mobility, requirements of high energy efficiency and reliability, etc. These features create various challenges for existing communication networks which are primarily optimized for H2H communications. Therefore, novel solutions are required to meet the key requirements of M2M communications. In addition, enhancements are required at different layers of the protocol stack to support co-existence of M2M devices and H2H users. The main objective of this research is to investigate the challenges of M2M communications in two broad types of M2M networks; capillary M2M and cellular M2M networks. The primary focus is on developing novel solutions, algorithms, and protocol enhancements for successfully enabling M2M communications. Since cognitive radio technology is very promising for M2M communications, special emphasis is on capillary M2M networks with cognitive radio based Physical layer. Besides, the focus is also on exploring new frontiers in M2M communications. This thesis covers different aspects of M2M communications. Considering the motivation for cognitive M2M and service requirements of M2M devices, two cognitive MAC protocols have been proposed. The first protocol is centralized in nature and utilizes a specialized frame structure for co-existence with the primary network as well as handling different Quality-of-Service (QoS) requirements of M2M devices. The second protocol is a distributed cognitive MAC protocol, which is specially designed to provide high energy efficiency and reliability for M2M devices operating in challenging wireless environments. Both protocols explicitly account for the peculiarities of cognitive radio environments. The protocols have been evaluated using analytical modeling and simulation studies. Recently IETF has standardized a specially designed routing protocol for capillary M2M networks, known as RPL (Routing for Low Power and Lossy Networks). RPL is emerging as the de facto routing protocol for many M2M applications including the smart grid. On the other hand, the application of cognitive radio for smart grid communication is under active investigation in the research community. Hence, it is important to investigate the applicability and adaptation of RPL in cognitive radio environments. In this regard, an enhanced RPL based routing protocol has been proposed for cognitive radio enabled smart grid networks. The enhanced protocol provides novel modifications to RPL for protecting the primary users along with meeting the utility requirements of the secondary network. An important challenge in LTE-based cellular networks with M2M communications is the uplink radio resource management as available resources are shared between M2M devices and H2H users, having different and often conflicting QoS requirements. Apart from this, energy efficiency requirements become critically important. Further, the specific constraints of Single Carrier Frequency Division Multiple Access (SC-FDMA) complicate the resource allocation problem. In this respect, an energy efficient resource allocation algorithm for the uplink of LTE networks with M2M/H2H co-existence under statistical QoS guarantees has been developed, that is based on canonical duality theory. The proposed algorithm outperforms classical algorithms in terms of energy efficiency while satisfying the QoS requirements of M2M devices and H2H users. A new frontier in M2M communications is the nano-M2M communications, which is envisioned to create the Internet-of-Nano-Things (IoNT). Molecular communication (MC) is a promising communication technique for nano-M2M communications. In literature, no model for error performance of MC exists. Therefore, an error performance model has been developed that explicitly accounts for noise and interference effects. Since relaying and network coding based solutions are gaining popularity for nano-M2M networks, the error performance of a network coded molecular nano-M2M network has been evaluated as well. Finally, the thesis is concluded based on the overall picture of the research conducted. In addition, some directions for future work are included as well.

In this thesis the multi-polarized Cognitive Radios are studied. Cognitive Radios are proposed as an interesting way to more efficiently use the frequency resources. A Cognitive Radio secondary user finds the frequency bands which are not utilized by primary users and communicates on them without interfering with the primary users. In order to achieve this goal the secondary user must be able to detect reliably and quickly the presence of a primary user in a frequency band. In this thesis, the impact of polarization on the spectrum sensing performances of cognitive radio systems is studied.<p><p>First the depolarization occurring in the wireless channel is studied for two cognitive radio scenarios. This is done through an extensive measurement campaign in two outdoor-to-indoor and indoor-to-indoor scenarios where the parameters characterizing the radiowaves polarization are characterized at three different spatial scales: small-scale variation, large-scale variation and distance variation. <p><p>Second, a new approach is proposed in modeling of multi-polarized channels. The polarization of received fields is characterized from an electromagnetic point of view by modeling the polarization ellipse. Theoretical formulations are proposed in order to obtain the parameters characterizing the polarization ellipse based on the signals received on three cross-polarized antennas. A system-based statistical model of the time-dynamics of polarization is proposed based on an indoor-to-indoor measurement campaign. The analytical formulations needed in order to project the polarization ellipse onto a polarized multi-antenna system are given and it is shown how the model can be generated. <p><p>Third, the impact of polarization on the spectrum sensing performances of energy detection method is presented and its importance is highlighted. The performance of spectrum sensing with multi-polarized antennas is compared with unipolar single and multi-antenna systems. This analysis is based on an analytical formulation applied to the results obtained from the multi-polarized measurement campaign. The detection probability as a function of distance between the primary transmitter and the secondary terminal and the inter-antenna correlation effect on the spectrum sensing performance are studied. <p><p>An important limitation of energy detector is its dependence on the knowledge of the noise variance. An uncertainty on the estimation of the noise variance considerably affects the performance of energy detector. This limitation is resolved by proposing new multi-polarized spectrum sensing methods which do not require any knowledge neither on the primary signal nor on the noise variance. These methods, referred to as “Blind spectrum sensing methods”, are based on the use of three cross-polarized antennas at the secondary terminal. Based on an analytical formulation and the results obtained from the measurement campaign, the performances of the proposed methods are compared with each-other and with the energy detection method. The effect of antenna orientation on the spectrum sensing performance of the proposed methods and the energy detection method is studied using the proposed elliptical polarization model. <p> / Doctorat en Sciences de l'ingénieur / info:eu-repo/semantics/nonPublished

Le vieillissement de la population sans doute catalysera l’augmentation des maladies chroniques et intensifiera le besoin de solutions d’assistance à la personne. Pendant que les chercheurs s’activent à apporter des réponses aux problèmes de santé publique qui s’accentuent, en s’appuyant sur les technologies de l’information et de la communication, le nombre des objets connectés connait une expansion fulgurante. Ainsi, le désir de révolution des technologies pour la santé, afin de faire face à la menace pathologique, coïncide avec le développement de l’Internet des objets 1. En effet, grâce aux innovations technologiques et au progrès médical, nombre de pathologies, souvent chroniques pourraient être suivies en temps réel et en tout lieu. Dans ce contexte, la gestion ou le partage des ressources de communication, la compatibilité des technologies et les performances à atteindre constituent des défis importants. Cet accroissement significatif du volume des communications, les contraintes de mobilité imposées par le contexte du suivi de patient ainsi que les besoins de qualité dans les transmissions de données médicales, révèlent une aspiration à des infrastructures de communication plus flexibles.Dans cette thèse, nous présentons une architecture de communication basée sur les réseaux Radio Cognitive pour répondre à cette exigence. Le caractère adaptable, flexible et autonome de la solution proposée permet d’aspirer à de meilleures performances. Ainsi, pour l’évaluation de son efficacité,nous avons choisi d’analyser et de tester trois critères importants pour les transmissions de données médicales urgentes.La connectivité en tout lieu : Ce premier critère est essentiel dans la mesure des performances et l’estimation de la fiabilité d’une infrastructure réseau dédiée à la santé. Plus précisément, toute solution de communication envisagée, doit être en mesure d’accompagner le patient suivi dans son environnement. En effet, la haute disponibilité des services réseaux et la qualité offerte sont déterminantes pour le suivi de patient à distance. Nous proposons dans cette première contribution, un mécanisme de prédiction spectrale capable d’examiner l’état d’occupation des bandes de fréquence. Cet algorithme associé au module de prise de décision Radio Cognitive, permet de parer aux éventuelles discontinuités de connexion réseaux.La gestion des interférences : Il s’agit du second critère qui évalue le degré de coexistence des ondes garantit par l’architecture, dans un contexte de prolifération des réseaux et des objets connectés. Le matériel communicant doit être capable de percevoir, d’analyser son environnement et d’agir en fonction des différentes contraintes. L’intérêt étant de protéger le matériel surtout médical, souvent très sensible aux bruits. Le suivi du patient devient alors possible à domicile ou à l’hôpital par exemple, avec un niveau d’interférence acceptable. Ainsi, tout en proposant un modèle de déploiement du réseau Radio Cognitive dans un centre hospitalier, nous définissons des exemples de fonctions permettant une adaptation dynamique des paramètres de communication en fonction de la sensibilité des équipements médicaux de proximité.L’efficacité dans la transmission de contenu multimédia : Ce dernier critère symbolise la capacité de l’architecture à fournir du contenu de qualité pour une assistance en temps réel. En effet, un réseau de soin à domicile ou une situation d’urgence peut nécessiter la transmission d’images ou de contenu multimédia vers les centres hospitaliers. Une solution de suivi de patient à distance doit être capable de fournir ces facilités qui imposent l’accès au haut débit. Dans une contribution répondant à cette préoccupation, nous suggérons un algorithme de réservation de ressources permettant de mieux gérer la qualité de service pour le contenu multimédia médical. / The aging of the population will probably catalyze the rise of chronic diseases and could intensify the need for personal assistance solutions. While researchers are focusing on information and communication technologies to provide responses to these public health problems, the number of connected objects is experiencing a rapid expansion. Indeed, desired revolution of technologies for health, forprevention and disease treatment coincides with the development of the Internet of Things 2. Thus, technological innovations and medical progress, for making it possible to monitor pathologies, often chronic, anywhere need appropriate equipments. Also, remote and real-time patient monitoring applications would require more network resources. In this context, communication resources management/sharing, technologies and equipments compatibilities and aplication’s desired performances become significant challenges. In this thesis, we propose an architecture based on Cognitive Radio, for meeting the medical applications constraints. We also analyze and test three important criteria for emergency transmissions, using this architecture.Connectivity : Any solution for patients monitoring must have anywhere and anytime capabilities for care continuity needs. High availability of network services and quality offered are critical for patient telemonitoring. We propose in this context, a spectral prediction mechanism able to examine the occupation conditions of the frequency bands. The algorithm we propose, associated learning and Grey Model technique in order to deal with any network connection discontinuities.Interference management : Network equipments must be able to perceive or to analyze their environment and act according to the underlying constraints. The interest is to protect in our case, medical equipment which are very sensitive to noise. Patient monitoring becomes possible at home or in the hospital, for example, with an acceptable level of interference. We propose for this criterion evaluation, a Cognitive Radio Networks deployment model in a hospital area. We define examples of functions for dynamic adaptation of the communication parameters, depending on the nearby medical devices sensitivity.Transmission efficiency under multimedia content delivery : This criterion analizes the ability of the architecture to provide desired quality in multimedia content delivery for real-time assistance or diagnosis. Patient monitoring at home or an emergency event may require the transmission of image or audio content to the hospital center. The remote monitoring solution must be able to provide these facilities which require a broadband network. We suggest an algorithm for resource reservation that performs a better management of the quality of service for medical multimedia content. We combine this algorithm with a transmission parameters control methode for maintaining the QoS at an acceptable level.

Les progrès récents des technologies de communication et la prolifération de l'informatique sans fil et des dispositifs de communication, ont induit 'a une surcharge dans l'utilisation du spectre radio. Cependant, les expériences de la Commission Fédérale de Communication (FCC) ont révélé que l'utilisation du spectre varie entre 15% et 85%. Par conséquent, les réseaux radios cognitifs (Cognitive Radio Networks ou CRNs) sont proposés afin d'utiliser le spectre radio d'une manière opportuniste. Dans ce type de réseaux radios cognitifs, où les fréquences de transmission sont sélectionnées d'une manière opportuniste - également sont appelés réseaux Ad-Hoc à radios cognitives -, la fiabilité de la dissémination des données est difficile 'a réaliser. D'abord, en plus des défis déjà connus dans les environnements sans fils, la diversité dans le nombre de fréquences qu'un noeud à radio cognitif a droit d'utiliser ajoute un autre défi, en limitant l'accessibilité à ses noeuds voisins. Deuxièmement, les noeuds à radio cognitif (CR) doivent conquérir les ressources de fréquences résiduelles avec les noeuds à radio primaire (PR), tout en essayent de les exploiter d'une manière opportuniste. En outre, les noeuds CR ne devraient pas perturber la qualité de réception des noeuds PR durant leur communication, et ce en limitant les interférences entre les deux de noeuds. Par conséquent, une nouvelle méthode de sélection de fréquences est requise afin de réduire le nombre d'interférences nuisibles aux noeuds PR, et maximiser les chances de délivrance des messages aux voisins récepteurs des noeuds CR, et augmenter ainsi la fiabilité des données disséminées. Dans cette thèse nous proposons SURF, une nouvelle méthode distribuée de sélection de fréquences pour la dissémination fiable de données dans un réseau radio cognitif multi-sauts. SURF classifie les fréquences radio disponibles en fonction de l'occupation des fréquences des noeuds à radio primaire et le nombre de noeuds 'a radio cognitive utilisant ces fréquences. Les résultats de simulation obtenus par NS-2 confirment que SURF est une stratégie efficace dans la sélection des meilleures fréquences de diffusion de données, comparée aux autres approches liées. Nous avons aussi constaté que les stratégies de sélection de fréquences sont considérablement influencées par l'activité des noeuds 'a radio primaire. Dans la suite ce cette thèse, nous étudierons et analyserons l'impact des modèles d'activités des noeuds PR sur les différentes stratégies de sélection de fréquences à travers des simulations basées NS-2. Nous avons remarqué que l'activité intermittente de PR est le cas où les solutions intelligentes doivent opérées. C'est dans ce cas où SURF donne les meilleures résultats et la région ciblée se serve des opportunités de communication. Enfin, dans cette thèse, nous allons encore plus loin en vérifiant l'applicabilité et la faisabilité de SURF. Dans cette perspective, d'abord, nous proposons une architecture d'accès à internet basse sur la radio cognitive pour les réseaux partiellement endommagés. Nous discutons les détails architecturaux et le principe de fonctionnement de l'architecture proposée. Nous avons également passé en revue les enjeux et les défis de déploiement de cette nouvelle architecture. Deuxièmement, nous discutons l'applicabilité de SURF dans le contexte de l'agrégation de fréquences et à cet égard, nous discutons une stratégie d'interférence basée sur l'agrégation de fréquences pour les réseaux radios cognitifs.

One critical step to successfully integrate wireless data networks to the high-speed wired backbone is the design of network control policies that efficiently utilize resources to provide Quality of Service (QoS) to the users in the integrated networks. Such a design has remained a challenge since wireless networks are time-varying in nature, not only in terms of user/packet arrivals but also in terms of physical channel conditions and access opportunities. In this thesis, we study the stochastic control of time-varying networks to design efficient scheduling and resource allocation policies. In particular, in Chapter 3, we focus on a broad class of control policies that work based on a pick-and-compare principle for networks with time-varying channels. By trading the throughput for complexity and memory requirement, these policies require less complexity compared to the well-investigated throughput-optimal Generalized Maximum Weight Matching (GMWM) policy and also require only linear-memory storage with the number of data-flows. Through Lyapunov analysis tools, we characterize the stability region and delay performance of the studied policies and show how they vary in response to the channel variations. In Chapter 4, we go into further detail and consider the problem of network control from a new perspective through which we carefully incorporate the time-efficiency of underlying scheduling algorithms. Specifically, we develop a policy that dynamically adjusts the time given to the available scheduling algorithms according to queue-backlog and channel correlations. We study the resulting stability region of developed policy and show that the region is at least as large as the one for any static policy. Finally, motivated by the current under-utilization of wireless spectrum, in Chapter 5, we investigate the control of cognitive radio networks as a special example of networks that provide time-varying access opportunities. We assume that users dynamically join and leave the network and may have different utility functions, or could collaborate for a common purpose. We develop a policy that performs joint admission and resource control and works for any user load, either inside or outside the capacity region. Through Lyapunov Optimization techniques, we show that the developed policy can achieve a utility performance arbitrarily close to the optimality with a tradeoff in the average service delay of admitted users.