Considerando a atual subutilização do espectro de rádio frequências para comunicação sem fio, o rádio cognitivo é visto como um conceito chave para permitir uma melhoria da utilização deste recurso de comunicação. A implementação de dispositivos de rádio cognitivo deve basear-se nas quatro principais funções cognitivas: sensoriamento espectral, decisão espectral, compartilhamento espectral e mobilidade espectral. Através dessas funções, um dispositivo de rádio cognitivo é capaz de procurar canais livres para transmitir de forma oportunista em uma rede de rádios cognitivos. No entanto, as redes de rádios cognitivos devem ser gerenciadas, com o objetivo de garantir seu pleno funcionamento, melhorando o desempenho destes dispositivos. Este gerenciamento deve melhorar o conhecimento do administrador sobre o funcionamento da rede. Assim, a configuração, o monitoramento e a visualização das funções cognitivas são fundamentais para o processo de aprendizagem contínua do administrador de rede. Neste trabalho, propõe-se Kitsune, um sistema de gerenciamento com base em um modelo hierárquico que permite gerenciar as informações sobre as funções cognitivas em redes de rádios cognitivos. Kitsune é projetado para gerenciar todas as quatro funções cognitivas, permitindo que o administrador da rede possa configurar os dispositivos de rádio cognitivo, monitorar os resultados de cada função cognitiva e analisar importantes visualizações destes resultados. Além disso, um protótipo de Kitsune foi desenvolvido e avaliado por meio de um cenário experimental baseado na norma IEEE 802.22. O resultado obtido mostra que Kitsune fornece ao administrador um melhor conhecimento sobre a rede, melhorando a taxa de transferência média para cada canal. / Considering the current underutilization of radio frequency spectrum for wireless communication, the Cognitive Radio is seen as a key concept to enable the improvement of the radio frequency spectrum utilization. The implementation of cognitive radio devices must be based on the four main cognitive functions: spectrum sensing, spectrum decision, spectrum sharing, and spectrum mobility. Through these functions, a cognitive radio device is able to search for vacant channels to opportunistically transmit in a cognitive radio network. However, cognitive radio networks should be managed, aiming to guaranty the proper operation of the cognitive radio devices, improving the performance of these devices. This management should improve the administrator knowledge about the cognitive radio network operation. Therefore, the configuration, monitoring and visualization of the cognitive functions are fundamental to the continuous knowledge building process of the network administrator. In this paper we propose Kitsune, a management system based on a hierarchical model allowing to manage summarized information about cognitive functions in radio networks. Kitsune is designed to manage all four cognitive functions, enabling the network administrator to configure the cognitive radio devices, monitor the results of each cognitive function, and make important visualizations of these results. Moreover, a Kitsune prototype was developed and evaluated through an experimental IEEE 802.22 scenario. The result obtained show that Kitsune allows the administrator to achieve a better knowledge about the network and improve the average throughput for each channel.

With the rapid proliferation of new wireless communication devices and services, the demand for the radio spectrum is increasing at a rapid rate, which leads to making the spectrum more and more crowded. The limited available spectrum and the inefficiency in the spectrum usage have led to the emergence of cognitive radio (CR) and dynamic spectrum access (DSA) technologies, which enable future wireless communication systems to exploit the empty spectrum in an opportunistic manner. To do so, future wireless devices should be aware of their surrounding radio environment in order to adapt their operating parameters according to the real-time conditions of the radio environment. From this viewpoint, spectrum sensing is becoming increasingly important to new and future wireless communication systems, which is designed to monitor the usage of the radio spectrum and reliably identify the unused bands to enable wireless devices to switch from one vacant band to another, thereby achieving flexible, reliable, and efficient spectrum utilisation. This thesis focuses on issues related to local and cooperative spectrum sensing for CR networks, which need to be resolved. These include the problems of noise uncertainty and detection in low signal to noise ratio (SNR) environments in individual spectrum sensing. In addition to issues of energy consumption, sensing delay and reporting error in cooperative spectrum sensing. In this thesis, we investigate how to improve spectrum sensing algorithms to increase their detection performance and achieving energy efficiency. To this end, first, we propose a new spectrum sensing algorithm based on energy detection that increases the reliability of individual spectrum sensing. In spite of the fact that the energy detection is still the most common detection mechanism for spectrum sensing due to its simplicity. Energy detection does not require any prior knowledge of primary signals, but has the drawbacks of threshold selection, and poor performance due to noise uncertainty especially at low SNR. Therefore, a new adaptive optimal energy detection algorithm (AOED) is presented in this thesis. In comparison with the existing energy detection schemes the detection performance achieved through AOED algorithm is higher. Secondly, as cooperative spectrum sensing (CSS) can give further improvement in the detection reliability, the AOED algorithm is extended to cooperative sensing; in which multiple cognitive users collaborate to detect the primary transmission. The new combined approach (AOED and CSS) is shown to be more reliable detection than the individual detection scheme, where the hidden terminal problem can be mitigated. Furthermore, an optimal fusion strategy for hard-fusion based cognitive radio networks is presented, which optimises sensing performance. Thirdly, the need for denser deployment of base stations to satisfy the estimated high traffic demand in future wireless networks leads to a significant increase in energy consumption. Moreover, in large-scale cognitive radio networks some of cooperative devices may be located far away from the fusion centre, which causes an increase in the error rate of reporting channel, and thus deteriorating the performance of cooperative spectrum sensing. To overcome these problems, a new multi-hop cluster based cooperative spectrum sensing (MHCCSS) scheme is proposed, where only cluster heads are allowed to send their cluster results to the fusion centre via successive cluster heads, based on higher SNR of communication channel between cluster heads. Furthermore, in decentralised CSS as in cognitive radio Ad Hoc networks (CRAHNs), where there is no fusion centre, each cognitive user performs the local spectrum sensing and shares the sensing information with its neighbours and then makes its decision on the spectrum availability based on its own sensing information and the neighbours’ information. However, cooperation between cognitive users consumes significant energy due to heavy communications. In addition to this, each CR user has asynchronous sensing and transmission schedules which add new challenges in implementing CSS in CRAHNs. In this thesis, a new multi-hop cluster based CSS scheme has been proposed for CRAHNs, which can enhance the cooperative sensing performance and reduce the energy consumption compared with other conventional decentralised cooperative spectrum sensing modes.

Considerando a atual subutilização do espectro de rádio frequências para comunicação sem fio, o rádio cognitivo é visto como um conceito chave para permitir uma melhoria da utilização deste recurso de comunicação. A implementação de dispositivos de rádio cognitivo deve basear-se nas quatro principais funções cognitivas: sensoriamento espectral, decisão espectral, compartilhamento espectral e mobilidade espectral. Através dessas funções, um dispositivo de rádio cognitivo é capaz de procurar canais livres para transmitir de forma oportunista em uma rede de rádios cognitivos. No entanto, as redes de rádios cognitivos devem ser gerenciadas, com o objetivo de garantir seu pleno funcionamento, melhorando o desempenho destes dispositivos. Este gerenciamento deve melhorar o conhecimento do administrador sobre o funcionamento da rede. Assim, a configuração, o monitoramento e a visualização das funções cognitivas são fundamentais para o processo de aprendizagem contínua do administrador de rede. Neste trabalho, propõe-se Kitsune, um sistema de gerenciamento com base em um modelo hierárquico que permite gerenciar as informações sobre as funções cognitivas em redes de rádios cognitivos. Kitsune é projetado para gerenciar todas as quatro funções cognitivas, permitindo que o administrador da rede possa configurar os dispositivos de rádio cognitivo, monitorar os resultados de cada função cognitiva e analisar importantes visualizações destes resultados. Além disso, um protótipo de Kitsune foi desenvolvido e avaliado por meio de um cenário experimental baseado na norma IEEE 802.22. O resultado obtido mostra que Kitsune fornece ao administrador um melhor conhecimento sobre a rede, melhorando a taxa de transferência média para cada canal. / Considering the current underutilization of radio frequency spectrum for wireless communication, the Cognitive Radio is seen as a key concept to enable the improvement of the radio frequency spectrum utilization. The implementation of cognitive radio devices must be based on the four main cognitive functions: spectrum sensing, spectrum decision, spectrum sharing, and spectrum mobility. Through these functions, a cognitive radio device is able to search for vacant channels to opportunistically transmit in a cognitive radio network. However, cognitive radio networks should be managed, aiming to guaranty the proper operation of the cognitive radio devices, improving the performance of these devices. This management should improve the administrator knowledge about the cognitive radio network operation. Therefore, the configuration, monitoring and visualization of the cognitive functions are fundamental to the continuous knowledge building process of the network administrator. In this paper we propose Kitsune, a management system based on a hierarchical model allowing to manage summarized information about cognitive functions in radio networks. Kitsune is designed to manage all four cognitive functions, enabling the network administrator to configure the cognitive radio devices, monitor the results of each cognitive function, and make important visualizations of these results. Moreover, a Kitsune prototype was developed and evaluated through an experimental IEEE 802.22 scenario. The result obtained show that Kitsune allows the administrator to achieve a better knowledge about the network and improve the average throughput for each channel.

Considerando a atual subutilização do espectro de rádio frequências para comunicação sem fio, o rádio cognitivo é visto como um conceito chave para permitir uma melhoria da utilização deste recurso de comunicação. A implementação de dispositivos de rádio cognitivo deve basear-se nas quatro principais funções cognitivas: sensoriamento espectral, decisão espectral, compartilhamento espectral e mobilidade espectral. Através dessas funções, um dispositivo de rádio cognitivo é capaz de procurar canais livres para transmitir de forma oportunista em uma rede de rádios cognitivos. No entanto, as redes de rádios cognitivos devem ser gerenciadas, com o objetivo de garantir seu pleno funcionamento, melhorando o desempenho destes dispositivos. Este gerenciamento deve melhorar o conhecimento do administrador sobre o funcionamento da rede. Assim, a configuração, o monitoramento e a visualização das funções cognitivas são fundamentais para o processo de aprendizagem contínua do administrador de rede. Neste trabalho, propõe-se Kitsune, um sistema de gerenciamento com base em um modelo hierárquico que permite gerenciar as informações sobre as funções cognitivas em redes de rádios cognitivos. Kitsune é projetado para gerenciar todas as quatro funções cognitivas, permitindo que o administrador da rede possa configurar os dispositivos de rádio cognitivo, monitorar os resultados de cada função cognitiva e analisar importantes visualizações destes resultados. Além disso, um protótipo de Kitsune foi desenvolvido e avaliado por meio de um cenário experimental baseado na norma IEEE 802.22. O resultado obtido mostra que Kitsune fornece ao administrador um melhor conhecimento sobre a rede, melhorando a taxa de transferência média para cada canal. / Considering the current underutilization of radio frequency spectrum for wireless communication, the Cognitive Radio is seen as a key concept to enable the improvement of the radio frequency spectrum utilization. The implementation of cognitive radio devices must be based on the four main cognitive functions: spectrum sensing, spectrum decision, spectrum sharing, and spectrum mobility. Through these functions, a cognitive radio device is able to search for vacant channels to opportunistically transmit in a cognitive radio network. However, cognitive radio networks should be managed, aiming to guaranty the proper operation of the cognitive radio devices, improving the performance of these devices. This management should improve the administrator knowledge about the cognitive radio network operation. Therefore, the configuration, monitoring and visualization of the cognitive functions are fundamental to the continuous knowledge building process of the network administrator. In this paper we propose Kitsune, a management system based on a hierarchical model allowing to manage summarized information about cognitive functions in radio networks. Kitsune is designed to manage all four cognitive functions, enabling the network administrator to configure the cognitive radio devices, monitor the results of each cognitive function, and make important visualizations of these results. Moreover, a Kitsune prototype was developed and evaluated through an experimental IEEE 802.22 scenario. The result obtained show that Kitsune allows the administrator to achieve a better knowledge about the network and improve the average throughput for each channel.

Resource allocation consists in allocating spectrum and power on every link of a network, possibly under power and rate requirements. In the context of cognitive radios, almost 15 years of research produced an impressive amount of theoretical contributions, exploring a wide range of possibilities. However, despite the ever-growing list of imaginable scenarios, we observe in Chapter 2 that most of these studies are based on similar working hypotheses. Our first contribution is to challenge some of these hypotheses, and propose a novel resource allocation scheme. Sticking to realistic assumptions, we show how our scheme reduces both computational complexity and control traffic, compared to other state-of-the-art techniques.<p><p>Due to a majority of the abovementioned studies making some constraining assumptions, realistic system designs and experimental demonstrations are much more quiet and unharvested fields. In an effort to help this transition from theory to practice, our second contribution is a four-nodes cognitive network demonstrator, presented in Chapter 3. In particular, we aim at providing a modular platform available for further open collaboration: different options for spectrum sensing, resource allocation, synchronisation and others can be experimented on this demonstrator. As an example, we develop a simple protocol to show that our proposed resource allocation scheme is fully implementable, and that primary users can be avoided using our approach.<p><p>Chapter 4 aims at removing another working hypothesis made when developping our resource allocation scheme. Indeed, resource alloca- tion is traditionally a Media Access Control (MAC) layer problem. This means that when solving a resource allocation problem in a network, the routing paths are usually assumed to be known. Conversely, the routing problem, which is a network layer issue, usually assumes that the available capacities on each link of the network (which depend on resource allocation) are known. Nevertheless, these two problems are mathematically entangled, and a cross-layer allocation strategy can best decoupled approaches in several ways, as we discuss in Chapter 4. Accordingly, our third and last contribution is to develop such a cross-layer allocation scheme for the scenario proposed in previous chapters.<p><p>All conclusions are summarised in Chapter 5, which also points to a few tracks for future research. / Doctorat en Sciences de l'ingénieur / info:eu-repo/semantics/nonPublished

Generalized fading has been an imminent part and parcel of wireless communications. It not only characterizes the wireless channel appropriately but also allows its utilization for further performance analysis of various types of wireless communication systems. Under the umbrella of generalized fading channels, a unified performance analysis of a free-space optical (FSO) link over the Malaga (M) atmospheric turbulence channel that accounts for pointing errors and both types of detection techniques (i.e. indirect modulation/direct detection (IM/DD) as well as heterodyne detection) is presented. Specifically, unified exact closed-form expressions for the probability density function (PDF), the cumulative distribution function (CDF), the moment generating function (MGF), and the moments of the end-to-end signal-to-noise ratio (SNR) of a single link FSO transmission system are presented, all in terms of the Meijer's G function except for the moments that is in terms of simple elementary functions. Then capitalizing on these unified results, unified exact closed-form expressions for various performance metrics of FSO link transmission systems are offered, such as, the outage probability (OP), the higher-order amount of fading (AF), the average error rate for binary and M-ary modulation schemes, and the ergodic capacity (except for IM/DD technique, where closed-form lower bound results are presented), all in terms of Meijer's G functions except for the higher-order AF that is in terms of simple elementary functions. Additionally, the asymptotic results are derived for all the expressions derived earlier in terms of the Meijer's G function in the high SNR regime in terms of simple elementary functions via an asymptotic expansion of the Meijer's G function. Furthermore, new asymptotic expressions for the ergodic capacity in the low as well as high SNR regimes are derived in terms of simple elementary functions via utilizing moments. All the presented results are verified via computer-based Monte-Carlo simulations. Besides addressing the pointing errors with zero boresight effects as has been addressed above, a unified capacity analysis of a FSO link that accounts for nonzero boresight pointing errors and both types of detection techniques (i.e. heterodyne detection as well as IM/DD) is also addressed. Specifically, an exact closed-form expression for the moments of the end-to-end SNR of a single link FSO transmission system is presented in terms of well-known elementary functions. Capitalizing on these new moments expressions, approximate and simple closed-form results for the ergodic capacity at high and low SNR regimes are derived for lognormal (LN), Rician-LN (RLN), and M atmospheric turbulences. All the presented results are verified via computer-based Monte-Carlo simulations. Based on the fact that FSO links are cost-effective, license-free, and can provide even higher bandwidths compared to the traditional radio-frequency (RF) links, the performance analysis of a dual-hop relay system composed of asymmetric RF and FSO links is presented. This is complemented by the performance analysis of a dual-branch transmission system composed of a direct RF link and a dual-hop relay composed of asymmetric RF and FSO links. The performance of the later scenario is evaluated under the assumption of the selection combining (SC) diversity and the maximal ratio combining (MRC) schemes. RF links are modeled by Rayleigh fading distribution whereas the FSO link is modeled by a unified GG fading distribution. More specifically, in this work, new exact closed-form expressions for the PDF, the CDF, the MGF, and the moments of the end-to-end SNR are derived. Capitalizing on these results, new exact closed-form expressions for the OP, the higher-order AF, the average error rate for binary and M-ary modulation schemes, and the ergodic capacity are offered. Cognitive radio networks (CRN) have also proved to improve the performance of wireless communication systems and hence based on this, the hybrid system analyzed above is extended with CRN technology wherein the outage and error performance analysis of a dual-hop transmission system composed of asymmetric RF channel cascaded with a FSO link is presented. For the RF link, an underlay cognitive network is considered where the secondary users share the spectrum with licensed primary users. Indoor femtocells act as a practical example for such networks. Specifically, it is assumed that the RF link applies power control to maintain the interference at the primary network below a predetermined threshold. While the RF channel is modeled by the Rayleigh fading distribution, the FSO link is modeled by a unified Gamma-Gamma turbulence distribution. The FSO link accounts for pointing errors and both types of detection techniques (i.e. heterodyne detection as well as IM/DD). With this model, a new exact closed-form expression is derived for the OP and the error rate of the end-to-end SNR of these systems in terms of the Meijer's G function and the Fox's H functions under amplify-and-forward relay schemes. All new analytical results are verified via computer-based Monte-Carlo simulations and are illustrated by some selected numerical results.

Wireless is everywhere. Smartphones, tablets, laptops, implantable medical devices, and many other wireless devices are massively taking part of our everyday activities. On average, an actively digital consumer has three devices. However, most of these wireless devices are small equipped with batteries that are often limited and need to be replaced or recharged. This fact limits the operating lifetime of wireless devices and presents a major challenge in wireless communication. To improve the perpetual energy operation of wireless communication systems, energy harvesting (EH) from the radio frequency (RF) signals is one promising solution to make the wireless communication systems self-sustaining. Since RF signals are known to transmit information, it is interesting to study when RF signals are simultaneously used to transmit information and scavenge energy, namely simultaneous wireless information and power transfer (SWIPT). In this thesis, we specifically aim to study the SWIPT in multiple-input multiple-output (MIMO) relay communication systems and in cognitive radio (CR) networks. First, we study the SWIPT in MIMO relay systems where the relay harvests the energy from the source and uses partially/fully the harvested energy to forward the signal to the destination. For both the amplify-and-forward (AF) and decode-and-forward (DF) relaying protocols, we consider the ideal scheme where both the energy and information transfer to the relay happen simultaneously, and the practical power splitting and time switching schemes. For each scheme, we aim to maximize the achievable end-to-end rate with a certain energy constraint at the relay. Furthermore, we consider the sum rate maximization problem for the multiuser MIMO DF relay broadcasting channels with multiple EH-enabled relays, and an enhanced low complex solution is proposed based on the block diagonalization method. Finally, we study the energy and data performance of the SWIPT in CR network where either the primary receiver (PR) or the secondary receiver (SR) is using the antenna switching (AS) technique. When the PR is an EH-enabled node, we illustrate the incentive of spectrum sharing in CR networks. When the SR is an EH-enabled node, we propose two thresholding-based selection schemes: the prioritizing data selection scheme and the prioritizing energy selection scheme.

Thesis(M.Sc. (Computer Science)) -- University of Limpopo, 2020 / Spectrum scarcity is one of the major problems affecting the advancement of wireless technology. The world is now entering into a new era called the “Fourth Industrial Revolution” and technologies like the Internet of Things (IoT) and blockchain are surfacing at a rapid pace. All these technologies and this new era need high speed network (Internet) connectivity. Internet connectivity is reliant on the availability of spectrum Channels. The Federal Communication Commission (FCC) has emphatically alluded on the urgency of finding quick and effective solutions to the problem of spectrum scarcity because the available spectrum bands are getting depleted at an alarming rate. Cognitive Radio Ad Hoc Networks (CRAHNs) have been introduced to solve the problem of spectrum depletion. CRAHNs are mobile networks which allow for two groups of users: Primary Users (PUs) and Secondary Users (SUs). PUs are the licensed users of the spectrum and SUs are the unlicensed users. The SUs access spectrum bands opportunistically by switching between unused spectrum bands. The current licensed users do not fully utilize their spectrum bands. Some licensed users only use their spectrum bands for short time periods and their bands are left idling for the greater part of time. CRNs take advantage of the periods when spectrum bands are not fully utilized by introducing secondary users to switch between the idle spectrum bands. The CRAHNs technology can be implemented in different types of routing environments including military networks. The military version of CRAHNs is called Military Cognitive Radio Ad Hoc Networks (MCRAHNs). Military networks are more complex than ordinary networks because they are subject to random attacks and possible destruction. This research project investigates the delays experienced in routing packets for MCRAHNs and proposes a new routing algorithm called Spectrum-Aware Transitive Multicasting On Demand Distance Vector (SAT-MAODV) which has been optimized for reducing delays in packet transmission and increasing throughput. In the data transmission process, there are several levels where delays are experienced. Our research project focuses on Routing Path (RP) delay, Spectrum Mobility (SM) delay and Node Relay (NR) delay. This research project proposes techniques for spectrum switching and routing called Time-Based Availability (TBA), Informed Centralized Multicasting (ICM), Node Roaming Area (NRA) and Energy Smart Transitivity (EST). All these techniques have been integrated into SAT-MAODV. SAT-MAODV was simulated and compared with the best performing algorithms in MCRHANs. The results show that SAT-MAODV performs better than its counterparts

Cognitive radio networks (CRNs) have emerged as a solution for the looming spectrum crunch caused by the rapid adoption of wireless devices over the previous decade. This technology enables efficient spectrum utility by dynamically reusing existing spectral bands. A CRN achieves this by requiring its users – called secondary users (SUs) – to measure and opportunistically utilise the band of a legacy broadcaster – called a primary user (PU) – in a process called spectrum sensing. Sensing requires the distribution and fusion of measurements from all SUs, which is facilitated by a variety of architectures and topologies. CRNs possessing a central computation node are called centralised networks, while CRNs composed of multiple computation nodes are called decentralised networks. While simpler to implement, centralised networks are reliant on the central node – the entire network fails if this node is compromised. In contrast, decentralised networks require more sophisticated protocols to implement, while offering greater robustness to node failure. Relay-based networks, a subset of decentralised networks, distribute the computation over a number of specialised relay nodes – little research exists on spectrum sensing using these networks. CRNs are vulnerable to unique physical layer attacks targeted at their spectrum sensing functionality. One such attack is the Byzantine attack; these attacks occur when malicious SUs (MUs) alter their sensing reports to achieve some goal (e.g. exploitation of the CRN’s resources, reduction of the CRN’s sensing performance, etc.). Mitigation strategies for Byzantine attacks vary based on the CRN’s network architecture, requiring defence algorithms to be explored for all architectures. Because of the sparse literature regarding relay-based networks, a novel algorithm – suitable for relay-based networks – is proposed in this work. The proposed algorithm performs joint MU detection and secure sensing by large-scale probabilistic inference of a statistical model. The proposed algorithm’s development is separated into the following two parts. • The first part involves the construction of a probabilistic graphical model representing the likelihood of all possible outcomes in the sensing process of a relay-based network. This is done by discovering the conditional dependencies present between the variables of the model. Various candidate graphical models are explored, and the mathematical description of the chosen graphical model is determined. • The second part involves the extraction of information from the graphical model to provide utility for sensing. Marginal inference is used to enable this information extraction. Belief propagation is used to infer the developed graphical model efficiently. Sensing is performed by exchanging the intermediate belief propagation computations between the relays of the CRN. Through a performance evaluation, the proposed algorithm was found to be resistant to probabilistic MU attacks of all frequencies and proportions. The sensing performance was highly sensitive to the placement of the relays and honest SUs, with the performance improving when the number of relays was increased. The transient behaviour of the proposed algorithm was evaluated in terms of its dynamics and computational complexity, with the algorithm’s results deemed satisfactory in this regard. Finally, an analysis of the effectiveness of the graphical model’s components was conducted, with a few model components accounting for most of the performance, implying that further simplifications to the proposed algorithm are possible. / Dissertation (MEng)--University of Pretoria, 2020. / Electrical, Electronic and Computer Engineering / MEng / Unrestricted

Traditionally, radio spectrum has been statically allocated to wireless service providers (WSPs). Regulators, like FCC, give wireless service providers exclusive long term licenses for using specific range of frequencies in particular geographic areas. Moreover, restrictions are imposed on the technologies to be used and the services to be provided. The lack of flexibility in static spectrum allocation constrains the ability to make use of new technologies and the ability to redeploy the spectrum to higher valued uses, thereby resulting in inefficient spectrum utilization [23, 38, 42, 62, 67]. These limitations have motivated a paradigm shift from static spectrum allocation towards a more ‘liberalized’ notion of spectrum management in which secondary users can borrow idle spectrum from primary spectrum licensees, without causing harmful interference to the latter- a notion commonly referred to as dynamic spectrum access (DSA) or open spectrum access [3], [82]. Cognitive radio [30, 47], empowered by Software Defined Radio (SDR) [81], is poised to promote the efficient use of spectrum by adopting this open spectrum approach. In this dissertation, we first address the problem of dynamic channel (spectrum) access by a set of cognitive radio enabled nodes, where each node acting in a selfish manner tries to access and use as many channels as possible, subject to the interference constraints. We model the dynamic channel access problem as a modified Rubinstein-St˚ahl bargaining game. iii In our model, each node negotiates with the other nodes to obtain an agreeable sharing rule of the available channels, such that, no two interfering nodes use the same channel. We solve the bargaining game by finding Subgame Perfect Nash Equilibrium (SPNE) strategies of the nodes. First, we consider finite horizon version of the bargaining game and investigate its SPNE strategies that allow each node to maximize its utility against the other nodes (opponents). We then extend these results to the infinite horizon bargaining game. Furthermore, we identify Pareto optimal equilibria of the game for improving spectrum utilization. The bargaining solution ensures that no node is starved of channels. The spectrum that a secondary node acquires comes to it at a cost. Thus it becomes important to study the ‘end system’ perspective of such a cost, by focusing on its implications. Specifically, we consider the problem of incentivizing nodes to provide the service of routing using the acquired spectrum. In this problem, each secondary node having a certain capacity incurs a cost for routing traffic through it. Secondary nodes will not have an incentive to relay traffic unless they are compensated for the costs they incur in forwarding traffic. We propose a path auction scheme in which each secondary node announces its cost and capacity to the routing mechanism, both of which are considered as private information known only to the node. We design a route selection mechanism and a pricing function that can induce nodes to reveal their cost and capacity honestly (making our auction truthful), while minimizing the payment that needs to be given to the nodes (making our auction optimal). By considering capacity constraint of the nodes, we explicitly support multiple path routing. For deploying our path auction based routing mechanism in DSA networks, we provide polynomial time iv algorithms to find the optimal route over which traffic should be routed and to compute the payment that each node should receive. All our proposed algorithms have been evaluated via extensive simulation experiments. These results help to validate our design philosophy and also illustrate the effectiveness of our solution approach.