Traditional hardware radios provide very rigid solutions to radio problems. Intelligent software defined radios, also known as cognitive radios, provide flexibility and agility compared to hardware radio systems. Cognitive radios are well suited for radio applications in a changing radio frequency environment, such as dynamic spectrum access. In this thesis, a cognitive radio is demonstrated where the system self reconfigures to demodulate a detected waveform. The GNU Radio framework is used to provide basic software defined radio building blocks and is supplemented with FPGA accelerators. The use of GNU Radio compliant hardware interfaces allows for seamless hardware/software radio deployments. Dynamic resource mapping allows radio designers to operate at a layer of abstraction above the physical radio implementation. By establishing lower level abstraction layers, future researchers can focus on larger picture concepts such as learning algorithms and behavioral models for the cognitive engine. / Master of Science

Dynamic Spectrum Access allows wireless users to access a wide range of spectrum which increases a node's ability to communicate with its neighbors, and spectral efficiency through opportunistic access to licensed bands. Our study focuses on the scalability of network performance, which we define in terms of network transport capacity and end-to-end throughput per node, as the network density increases. We develop an analytical procedure for performance evaluation of ad hoc DSA networks using Markov models, and analyze the performance of a DSA network with one transceiver per node and a dedicated control channel. We also develop and integrate a detailed model for energy detection in Poisson networks with sensing. We observe that the network capacity scales sub-linearly with the number of DSA users and the end-to-end throughput diminishes, when the number of data channels is fixed. Nevertheless, we show that DSA can improve network performance by allowing nodes to access more spectrum bands while providing a mechanism for spectrum sharing and maintaining network wide connectivity. We also observe that the percentage of relative overhead at the medium access layer does not scale with the number of users. Lastly, we examine the performance impact of primary user density, detection accuracy, and the number of available data channels. The results help to answer the fundamental question of the scaling behavior of network capacity, end-to-end throughput, and network overhead in ad hoc DSA networks. / Master of Science

For the past 70 years, the Federal Communications Commission (FCC) has been the licensing authority for wireless spectrum. Traditionally, spectrum was commercially licensed to primary users with defined uses. With the growth of personal communication systems in the 1990''s, unallocated spectrum has become a scarce commodity. However, since most primary users are active only at certain times and places, much of the allocated spectrum remains underutilized. Substantial holes exist in the spatio-temporal spectrum that could be opportunistically used by unlicensed secondary users. As a result, the FCC is considering allowing secondary users to opportunistically use frequencies that are not being used by primary users. If multiple secondary users are present in the same geographical area, the concept of Dynamic Spectrum Sharing (DSS) allows these users to share the opportunistic spectrum. If several secondary users want to use a limited set of frequency resources, they will very likely interfere with each other. Sensing is a distributed technique where each transmitter/receiver pair senses (both passively and actively) the available channels and uses the channel that provides the best performance. While sensing alone allows sharing of the spectrum, it is not the optimal method in terms of maximizing the capacity in such a shared system. If we allow the secondary users to collaborate and share information, optimal capacity might be reached. However, collaboration adds another level of complexity to the transceivers of the secondary users, since they must now be able to communicate (Note that in general, the secondary users may have completely different communication protocols, e.g., Wi-Fi and Bluetooth). Additionally, optimizing the capacity of the available spectrum could have other negative side effects such as impacting the fairness of sharing the resources. Our primary goal is to explore the benefit of this cost-benefit tradeoff by determining the capacity increase obtainable from collaboration. As a secondary goal, we also wish to determine how this increase in capacity affects fairness. To summarize, the goal of this work is to answer the question: Fundamentally, what is the benefit of collaboration in Dynamic Spectrum Sharing? / Master of Science

The radio frequency spectrum is not being efficiently utilized partly due to the current policy of allocating the frequency bands to specific services and users. In opportunistic spectrum access (OSA), the ``white spaces'' that are not occupied by primary users (a.k.a. incumbent users) can be opportunistically utilized by secondary users. To achieve this, we need to solve two problems: (i) primary-secondary incumbent protection, i.e., prevention of harmful interference from secondary users to primary users; (ii) secondary-secondary network coexistence, i.e., mitigation of mutual interference among secondary users. The first problem has been addressed by spectrum sensing techniques in cognitive radio (CR) networks and geolocation database services in database-driven spectrum sharing. The second problem is the main focus of this dissertation. To obtain a clear picture of coexistence issues, we propose a taxonomy of heterogeneous coexistence mechanisms for shared spectrum access. Based on the taxonomy, we choose to focus on four typical coexistence scenarios in this dissertation. Firstly, we study sensing-based OSA, when secondary users are capable of employing the channel aggregation technique. However, channel aggregation is not always beneficial due to dynamic spectrum availability and limited radio capability. We propose a channel usage model to analyze the impact of both primary and secondary user behaviors on the efficiency of channel aggregation. Our simulation results show that user demands in both the frequency and time domains should be carefully chosen to minimize expected cumulative delay. Secondly, we study the coexistence of homogeneous CR networks, termed as self-coexistence, when co-channel networks do not rely on inter-network coordination. We propose an uplink soft frequency reuse technique to enable globally power-efficient and locally fair spectrum sharing. We frame the self-coexistence problem as a non-cooperative game, and design a local heuristic algorithm that achieves the Nash equilibrium in a distributed manner. Our simulation results show that the proposed technique is mostly near-optimal and improves self-coexistence in spectrum utilization, power consumption, and intra-cell fairness. Thirdly, we study the coexistence of heterogeneous CR networks, when co-channel networks use different air interface standards. We propose a credit-token-based spectrum etiquette framework that enables spectrum sharing via inter-network coordination. Specifically, we propose a game-auction coexistence framework, and prove that the framework is stable. Our simulation results show that the proposed framework always converges to a near-optimal distributed solution and improves coexistence fairness and spectrum utilization. Fourthly, we study database-driven OSA, when secondary users are mobile. The use of geolocation databases is inadequate in supporting location-aided spectrum sharing if the users are mobile. We propose a probabilistic coexistence framework that supports mobile users by locally adapting their location uncertainty levels in order to find an appropriate trade-off between interference mitigation effectiveness and location update cost. Our simulation results show that the proposed framework can determine and adapt the database query intervals of mobile users to achieve near-optimal interference mitigation with minimal location updates. / Ph. D.

In recent years, Software Defined and Cognitive Radios (SDRs and CRs) have become popular topics of research. Game theory has proven to be a useful set of tools for analyzing wireless networks, including Cognitive Networks (CNs). This thesis provides a game theoretic cross-layer mechanism that can be used to control SDRs and CRs. We have constructed an upper-layer Topology Control (TC) game, which decides which links each node uses. A TDMA algorithm which we have adapted is then run on these links. The links and the TDMA schedule are then passed to a lower-layer game, the Link Adaptation Game (LAG), where nodes adjust their transmit power and their link parameters, which in this case are modulation scheme and channel coding rate. It is shown that both the TC game and the LAG converge to a Nash Equilibrium (NE). It is also shown that the solution for the TC game approximates the topology that results from maximizing the utility function when appropriate link costs are used. Also seen is the increase in throughput provided by the LAG when compared to the results of Greedy Rate Packing (GRP). / Master of Science

Software-Defined Radio (SDR) is a large field of research, and is rapidly expanding in terms of capabilities and applications. As the number of SDR platforms, deployments, and use-cases grow, interoperability, compatibility, and software re-use becomes more difficult. Additionally, advanced SDR applications require more advanced hardware and software platforms to support them, necessitating intelligent management of resources and functionality. Realizing these goals can be done using the paradigms of Component-Based Design (CBD) and Service-Oriented Architectures (SOAs). Component-based design has been applied to the field of SDR in the past to varying levels of success. We discuss the benefits of CBD, and how to successfully use CBD for SDR. We assert that by strictly enforcing the principles of CBD, we can achieve a high level of independence from both the hardware and software platforms, and enable component compatibility and interoperability between SDR platforms and deployments. Using CBD, we also achieve the use-case of a fully distributed SDR, where multiple hardware nodes act as one cohesive radio unit. Applying the concept of service-orientation to SDR is a novel idea, and we discuss how this enables a new radio paradigm in the form of goal-oriented autonomic radios. We define SOAs in the context of SDR, explain how our vision is different than middle-wares like CORBA, describe how SOAs can be used, and discuss the possibilities of autonomic radio systems. This thesis also presents our work on the Cognitive Radio Open Source Systems (CROSS) project. CROSS is a free and open-source prototype architecture that uses CBD to achieve platform independence and distributed SDR deployments. CROSS also provides an experimental system for using SOAs in SDRs. Using our reference implementation of CROSS, we successfully demonstrated a distributed cognitive radio performing dynamic spectrum access to communicate with another SDR while avoiding an interferer operating in the spectrum. / Master of Science

The computational power and algorithms needed to create a cognitive radio are quickly becoming available. There are many advantages to having a radio operated by cognitive engine, and so cognitive radios are likely to become very popular in the future. One of the main difficulties associated with the cognitive radio is ensuring the signal transmitted will follow all FCC rules. The work presented in this thesis provides a methodology to guarantee that all signals will be legal and valid. The first part to achieving this is a practical and easy to use software testing program based on the tabu search algorithm that tests the software off-line. The primary purpose of the software testing program is to find most of the errors, specially structural errors, while the radio is not in use so that it does not affect the performance of the system. The software testing program does not provide a complete assurance that no errors exist, so to supplement this deficit, a built-in self-test (BIST) is employed. The BIST is designed with two parts, one that is embedded into the cognitive engine and one that is placed into the radio's API. These two systems ensure that all signals transmitted by the cognitive radio will follow FCC rules while consuming a minimal amount of computational power. The software testing approach based on the tabu search is shown to be a viable method to test software with improved results over previous methods. Also, the software BIST demonstrated its ability to find errors in the signal production and is dem to only require an insignificant amount of computational power. Overall, the methods presented in this paper provide a complete and practical approach to assure the FCC of the legality of all signals in order to obtain a license for the product. / Master of Science

Since its inception, cognitive radio (CR) has quickly been accepted as the enabling radio technology for next-generation wireless communications. A CR promises unprecedented flexibility in radio functionalities via programmability at the lowest layer, which was once done in hardware. Due to its spectrum sensing, learning, and adaptation capabilities, CR is able to address the heart of the problem associated with spectrum scarcity (via dynamic spectrum access (DSA)) and interoperability (via channel switching). It is envisioned that CR will be employed as a general radio platform upon which numerous wireless applications can be implemented. For both theoretical and practical purposes, it is important for network researchers to model a cognitive radio ad hoc network (CRN) and optimize its performance. Such efforts are important not only for theoretical understanding, but also in that such results can be used as benchmarks for the design of distributed algorithms and protocols. However, due to some unique characteristics associated with CRNs, existing analytical techniques may not be applied directly. As a result, new theoretical results, along with new mathematical techniques, need to be developed. In this thesis, we focus on modeling and optimization of CRNs. In particular, we will study multicast communications in CRN and MIMO-empowered CRN, which we describe as follows. An important service that must be supported by CRNs is multicast. Although there are a lot of research on multicast in ad hoc networks, those results cannot be applied to a CRN, because of the complexity associated with a CR node (e.g., multiple available frequency bands, difference in available bands from neighboring nodes). In addition, a single-layer approach (e.g., multicast routing) is overly simplistic when resource optimization (i.e., minimizing network resource) is the main objective. For this purpose, a cross-layer approach is usually necessary, which should include joint consideration of multiple lower layers, in addition to network layer. However, such a joint formulation is usually highly complex and difficult. In this thesis, we aim to develop some novel algorithms that provide near-optimal solutions. Our goal is to minimize the required network-wide resource to support a set of multicast sessions, with a certain bit rate for each multicast session. The unique characteristics associated with CR and distinguish this problem from existing multicast research for ad hoc networks. In this work, we formulate this problem via a cross-layer approach with joint consideration of scheduling and routing. Although the problem formulation is in the form of mixed integer linear program (MILP), we are successful in developing a polynomial time algorithm that offers highly competitive solution. The main ideas of the algorithm include identification of key integer variables, fixing these variables via a series of relaxed linear program (LP), and tying up such integer fixing with a bottom-up tree construction. By comparing with a lower bound, we find that the proposed algorithm can provide a solution that is very close to the optimum. In parallel to the development of CR for DSA, multiple-input multiple-output (MIMO) has widely been accepted and now implemented in commercial wireless products to increase capacity. The goal of MIMO and how it operates are largely independent and orthogonal to CR. Instead of exploiting idle channels for wireless communications, MIMO attempts to increase capacity within the same channel via space-time processing. Assuming that CR and MIMO will ultimately marry each other and offer the ultimate flexibility in DSA and spectrum efficiency, we would like to inquire the potential capacity gain in this marriage. In particular, we are interested in how such marriage will affect the capacity of a user communication session in a multi-hop CRN. We explore MIMO-empowered CR network, which we call CRN^MIMO, to achieve ultimate flexibility in DSA and spectrum efficiency. Given that CR and MIMO handle interference at different levels (across channels vs. within a channel), we are interested in how joint optimization of both will maximize user capacity in a multi-hop network. To answer this question, we develop a tractable mathematical model for CRN^MIMO, which captures the essence of channel assignment (for CR) and degree-of-freedom (DoF) allocation (for MIMO). Based on this mathematical model, we use numerical results to show how channel assignment in CRN and DoF allocation in MIMO can be jointly optimized to maximize capacity. More important, for a CRN^MIMO with A_MIMO antennas at each node, we show that joint optimization of CR and MIMO offers more than A_MIMO-fold capacity increase than a CRN with only a single antenna at each node. / Master of Science

No / Spectrum sensing is used in cognitive radio systems to detect the availability of spectrum holes for secondary usage. The simplest and most famous spectrum sensing techniques are based either on energy detection or eigenspace analysis from Random Matrix Theory (RMT) such as using the Marchenko-Pastur law. These schemes suffer from uncertainty in estimating the noise variance which reduces their performance. In this paper we propose a new method to evaluate the noise variance that can eliminate the limitations of the aforementioned schemes. This method estimates the noise variance from a measurement set of noisy signals or noise-only signals. Extensive simulations show that the proposed method performs well in estimating the noise variance. Its performance greatly improves with increasing numbers of measurements and also with increasing numbers of samples taken per measurement.

No / Dynamic Spectrum Access (DSA) for secondary usage of underutilized radio spectrum is currently of great interest for radio regulatory authorities and for cellular network operators. However, the co-existence of multiple devices operating in the same bands, such as wireless microphones which also operate in TV bands, poses a challenge to DSA. Efficient and proactive spectrum sensing could prevent harmful interference between collocated devices, but existing blind spectrum sensing schemes such as energy detection and schemes based on Random Matrix Theory (RMT) have performance limitations. We propose a new blind spectrum sensing scheme for cognitive radio. The proposed scheme uses a new formula for the estimation of noise variance. The scheme has been evaluated through extensive simulations on wireless microphone signals and shows higher performance as compared to energy detection and RMT-based sensing schemes such as MME and EME. It also shows higher performance in terms of probability of detection (Pd).