Radiofrequency spectrum is a finite resource that consists of the frequencies in the range 3 kHz to 300 GHz. It is used for wireless communication and supports several applications and services. Whether it is at the personal, community or society level, and whether it is for applications in consumer electronics, building management, smart utility networks, intelligent driving systems, the Internet of Things, industrial automation and so on, the demand for wireless communication is increasing continuously. Together with this increase in demand, there is an increase in the quality of service requirements in terms of throughput, and the reliability and availability of wireless services. Industrial wireless sensor networks, for example, operate in environments that are usually harsh and time varying. The frequency spectrum that is utilised by industrial wireless protocols such as WirelessHART and ISA 100.11a, is also used by many other wireless technologies, and with wireless applications growing rapidly, it is possible that multiple heterogeneous wireless systems will need to operate in overlapping spatiotemporal regions in the future. Increased radiofrequency interference affects connectivity and reduces communication link quality. This affects reliability and latency negatively, both of which are core quality service requirements. Getting multiple heterogeneous radio systems to co-exist harmoniously in shared spectrum is challenging. Traditionally, this has been achieved by granting network operators exclusive rights that allow them to access parts of the spectrum assigned to them and hence the problems of co-existence and limited spectrum could be ignored. Design time multi-access techniques have also been used. At present, however, it has become necessary to use spectrum more efficiently, to facilitate the further growth of wireless communication. This can be achieved in a number of ways. Firstly, the policy that governs the regulation of radiofrequency spectrum must be updated to accommodate flexible, dynamic spectrum access. Secondly, new techniques for multiple-access and spectrum sharing should be devised. A revolutionary new communication paradigm is required, and one such paradigm has recently emerged in the form of Cognitive Radio technology. Traditional methods to sharing spectrum assume that radios in a wireless network work together in an unchanging environment. Cognitive radios, on the other hand, can sense, learn and adapt. In cognitive radio networks, the interactions between users are taken into account, in order for adjustments to be made to suit the prevailing radio environment. In this thesis, the problem of spectrum scarcity and coexistence is addressed using cognitive radio techniques, to ensure more efficient use of radio-frequency spectrum. An introduction to cognitive radio networks is given, covering cognitive radio fundamentals, spectrum sensing, dynamic spectrum management, game theoretic approaches to spectrum sharing and security in cognitive radio networks. A focus is placed on wireless industrial networks as a challenging test case for cognitive radio. A study on spectrum management policy is conducted, together with an investigation into the current state of radio-frequency spectrum utilisation, to uncover real and artificial cases of spectrum scarcity. A novel cognitive radio protocol is developed together with an open source test bed for it. Finally, a game theoretic dynamic spectrum access algorithm is developed that can provide scalable, fast convergence spectrum sharing in cognitive radio networks. This work is a humble contribution to the advancement of wireless communication. / Thesis (PhD)--University of Pretoria, 2016. / Centre for Telecommunication Engineering for the Information Society / Electrical, Electronic and Computer Engineering / PhD / Unrestricted

Recent disasters, including the 9/11 terrorist attacks, Hurricane Katrina, the London subway bombings, and the California wildfires, have all highlighted the limitations of current mobile communication systems for public safety first responders. First, in a point-to-point configuration, legacy radio systems used by first responders from differing agencies are often made by competing manufacturers and may use incompatible waveforms or channels. In addition, first responder radio systems, which may be licensed and programmed to operate in frequency bands allocated within their home jurisdiction, may be neither licensed nor available in forward-deployed disaster response locations, resulting in an operational scarcity of usable frequencies. To address these problems, first responders need smart radio solutions which can bridge these disparate legacy radio systems together, can incorporate new smart radio solutions, or can replace these existing aging radios. These smart radios need to quickly find each other and adhere to spectrum usage and access policies. Second, in an infrastructure configuration, legacy radio systems may not operate at all if the existing communications backbone has been destroyed by the disaster event. A communication system which can provide a new, temporary infrastructure or can extend an existing infrastructure into a shaded region is needed. Smart radio nodes that make up the public safety infrastructure again must be able to find each other, adhere to spectrum usage policies, and provide access to other smart radios and legacy public safety radios within their coverage area. This work addresses these communications problems in the following ways. First, it applies cognitive radio technology to develop a smart radio system capable of rapidly adapting itself so it can communicate with existing legacy radio systems or other smart radios using a variety of standard and customized waveforms. These smart radios can also assemble themselves into an ad-hoc network capable of providing a temporary communications backbone within the disaster area, or a network extension to a shaded communications area. Second, this work analyzes and characterizes a series of rendezvous protocols which enable the smart radios to rapidly find each other within a particular coverage area. Third, this work develops a spectrum sharing protocol that enables the smart radios to adhere to spectral policies by sharing spectrum with other primary users of the band. Fourth, the performance of the smart radio architecture, as well as the performance of the rendezvous and spectrum sharing protocols, is evaluated on a smart radio network testbed, which has been assembled in a laboratory setting. Results are compared, when applicable, to existing radio systems and protocols. Finally, this work concludes by briefly discussing how the smart radio technologies developed in this dissertation could be combined to form a public safety communications architecture, applicable to the FCC's stated intent for the 700 MHz Band. In the future, this work will be extended to applications outside of the public safety community, specifically, to communications problems faced by warfighters in the military. / Ph. D.

The spectacular growth in wireless services imposes scarcity in term of the available radio spectrum. A solution to overcome this scarcity is to adopt what so called cognitive radio based on dynamic spectrum access. With dynamic spectrum access, secondary (unlicensed) users can access  spectrum owned by primary (licensed) users when it is temporally and/or geographically unused. This unused spectrum is termed as spectrum opportunity. Finding these spectrum opportunities related aspects are studied in this thesis where two approaches of finding spectrum opportunities, namely spectrum sensing and geo-locations databases are considered. In spectrum sensing arena, two topics are covered, blind spectrum sensing and sensing time and periodic sensing interval optimization. For blind spectrum sensing, a spectrum scanner based on maximum minimum eigenvalues detector and frequency domain rectangular filtering is developed. The measurements show that the proposed scanner outperforms the energy detector scanner in terms of the probability of detection. Continuing in blind spectrum sensing, a novel blind spectrum sensing technique based on discriminant analysis called spectrum discriminator has been developed in this thesis. Spectrum discriminator has been further developed to peel off multiple primary users with different transmission power from a wideband sensed spectrum. The spectrum discriminator performance is measured and compared with the maximum minimum eigenvalues detector in terms of the probability of false alarm, the probability of detection and the sensing time. For sensing time and periodic sensing interval optimization, a new approach that aims at maximizing the probability of right detection, the transmission efficiency and the captured opportunities is proposed and simulated. The proposed approach optimizes the sensing time and the periodic sensing interval iteratively. Additionally, the periodic sensing intervals for multiple channels are optimized to achieve as low sensing overhead and unexplored opportunities as possible for a multi channels system. The thesis considers radar bands and TV broadcasting bands to adopt geo-locations databases for spectrum opportunities. For radar bands, the possibility of spectrum sharing with secondary users in L, S and C bands is investigated. The simulation results show that band sharing is possible with more spectrum opportunities offered by C band than S and L band which comes as the least one. For the TV broadcasting bands, the thesis treats the power assignment for secondary users operate in Gävle area, Sweden. Furthermore, the interference that the TV transmitter would cause to the secondary users is measured in different locations in the same area. / <p>QC 20130114</p> / QUASAR

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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

This thesis provides three main contributions with respect to the Dynamic Channel and Power Assignment (DCPA) problem. DCPA refers to the allocation of transmit power and frequency channels to links in a cognitive dynamic spectrum network so as to maximize the total number of feasible links while minimizing the aggregate transmit power. In order to provide a method to compare related, yet disparate, work, the first contribution of this thesis is a unifying optimization formulation to describe the DCPA problem. This optimization problem is based on maximizing the number of feasible links and minimizing transmit power of a set of communications links in a given communications network. Using this optimization formulation, this thesis develops its second contribution: a evaluation method for comparing DCPA algorithms. The evaluation method is applied to five DPCA algorithms representative of the DCPA literature . These five algorithms are selected to illustrate the tradeoffs between control modes (centralized versus distributed) and channel/power assignment techniques. Initial algorithm comparisons are done by analyzing channel and power assignment techniques and algorithmic complexity of five different DCPA algorithms. Through simulations, algorithm performance is evaluated by the metrics of feasibility ratio and average power per link. Results show that the centralized algorithm Minimum Power Increase Assignment (MPIA) has the overall best feasibility ratio and the lowest average power per link of the five algorithms we investigated. Through assignment by the least change in transmit power, MPIA minimizes interference and increases the number of feasible links. However, implementation of this algorithm requires calculating the inverse of near singular matrices, which could lead to inaccurate results. The third contribution of this thesis is a proposed distributed channel assignment algorithm, Least Interfering Channel and Iterative Power Assignment (LICIPA). This distributed algorithm has the best feasibility ratio and lowest average power per link of the distributed algorithms. In some cases, LICIPA achieves 90% of the feasibility ratio of MPIA, while having lower complexity and overall lower average run time. / Master of Science

Dynamic spectrum access (DSA) is a powerful approach to mitigate the spectrum scarcity problem caused by rapid increase in wireless communication demands. Based on architecture design, DSA systems can be categorized as centralized and distributed. To successfully enable DSA, both centralized and distributed systems have to deal with spectrum management issues including spectrum sensing, spectrum decision, spectrum sharing and spectrum mobility. Our work starts by investigating the challenges of efficient spectrum monitoring in centralized spectrum sensing. Since central controllers usually require the presence information of incumbent users/primary users (IUs) for decision making, which is obtained during spectrum sensing, privacy issues of IUs become big concerns in some DSA systems where IUs have strong operation security needs. To aid in this, we design novel location privacy protection schemes for IUs. Considering the general drawbacks of centralized systems including high computational overhead for central controllers, single point failure and IU privacy issues, in many scenarios, a distributed DSA system is required. In this dissertation, we also cope with the spectrum sharing issues in distributed spectrum management, specifically the secondary user (SU) power control problem, by developing distributed and secure transmit power control algorithms for SUs. In centralized spectrum management, the common approach for spectrum monitoring is to build infrastructures (e.g. spectrum observatories), which cost much money and manpower yet have relatively low coverage. To aid in this, we propose a crowdsourcing based spectrum monitoring system to capture the accurate spectrum utilization at a large geographical area, which leverages the power of masses of portable mobile devices. The central controller can accurately predict future spectrum utilization and intelligently schedule the spectrum monitoring tasks among mobile SUs accordingly, so that the energy of mobile devices can be saved and more spectrum activities can be monitored. We also demonstrate our system's ability to capture not only the existing spectrum access patterns but also the unknown patterns where no historical spectrum information exists. The experiment shows that our spectrum monitoring system can obtain a high spectrum monitoring coverage with low energy consumption. Environmental Sensing Capability (ESC) systems are utilized in DSA in 3.5 GHz to sense the IU activities for protecting them from SUs' interference. However, IU location information is often highly sensitive in this band and hence it is preferable to hide its true location under the detection of ESCs. As a remedy, we design novel schemes to preserve both static and moving IU's location information by adjusting IU's radiation pattern and transmit power. We first formulate IU privacy protection problems for static IU. Due to the intractable nature of this problem, we propose a heuristic approach based on sampling. We also formulate the privacy protection problem for moving IUs, in which two cases are analyzed: (1) protect IU's moving traces; (2) protect its real-time current location information. Our analysis provides insightful advice for IU to preserve its location privacy against ESCs. Simulation results show that our approach provides great protection for IU's location privacy. Centralized DSA spectrum management systems has to bear several fundamental issues, such as the heavy computational overhead for central controllers, single point failure and privacy concerns of IU caused by large amounts of information exchange between users and controllers and often untrusted operators of the central controllers. In this dissertation, we propose an alternative distributed and privacy-preserving spectrum sharing design for DSA, which relies on distributed SU power control and security mechanisms to overcome the limitations of centralized DSA spectrum management. / Doctor of Philosophy / Due to the rapid growth in wireless communication demands, the frequency spectrum is becoming increasingly crowded. Traditional spectrum allocation policy gives the unshared access of fixed bands to the licensed users, and there is little unlicensed spectrum left now to allocate to newly emerged communication demands. However, studies on spectrum occupancy show that many licensed users who own the license of certain bands are only active for a small percentage of time, which results in plenty of underutilized spectrum. Hence, a new spectrum sharing paradigm, called dynamic spectrum access (DSA), is proposed to mitigate this problem. DSA enables the spectrum sharing between different classes of users, generally, the unlicensed users in the DSA system can access the licensed spectrum opportunistically without interfering with the licensed users. Based on architecture design, DSA systems can be categorized as centralized and distributed. In centralized systems, a central controller will make decisions on spectrum usage for all unlicensed users. Whereas in distributed systems, unlicensed users can make decisions for themselves independently. To successfully enable DSA, both centralized and distributed DSA systems need to deal with spectrum management issues, such as resource allocation problems and user privacy issues, etc. The resource allocation problems include, for example, the problems to discover and allocate idle bands and the problems to control users' transmit power for successful coexistence. Privacy issues may also arise during the spectrum management process since certain information exchange is inevitable for global decision making. However, due to the Federal Communications Commission's (FCC) regulation, licensed users' privacy such as their location information must be protected in any case. As a result, dynamic and efficient spectrum management techniques are necessary for DSA users. In this dissertation, we investigate the above-mentioned spectrum management issues in both types of DSA systems, specifically, the spectrum sensing challenges with licensed user location privacy issues in centralized DSA, and the spectrum sharing problems in distributed DSA systems. In doing so, we propose novel schemes for solving each related spectrum management problem and demonstrate their efficacy through the results from extensive evaluations and simulations. We believe that this dissertation provides insightful advice for DSA users to solve different spectrum management issues for enabling DSA implementation, and hence helps in a wider adoption of dynamic spectrum sharing.

Recent advancements in frequency-agile radio technology and dynamic spectrum access network have created a huge space for improving the utilization efficiency of wireless spectrum. Existing algorithms and protocols, however, have not taken full advantage of the new technologies due to obsolete network design ideologies inherited from conventional network design, such as static spectrum access and static channelization. In this dissertation, we propose new resource management models and algorithms that capitalize on the frequency-agility of next generation radios and the dynamic spectrum access concepts to increase the utilization efficiency of wireless spectrum. We first propose a new analytical model for Dynamic Spectrum Access (DSA) networks. Compared to previous models, the new model is able to include essential DSA mechanisms such as spectrum sensing and primary interference avoidance into solid mathematical representation and thus drastically increase the accuracy of our model. The subsequent numerical study conforms well with existing empirical studies and provides fundamental insights on the design of future DSA networks. We then take advantage of partially overlapped channel in frequency-agile radio networks and propose simple joint channel scheduling and flow routing optimization algorithm that maximizes network throughput. The model quantifies the impact of fundamental network settings, such as node density and traffic load, on the performance of partially overlapped channel based networks. We then propose a cross-layer radio resource allocation algorithm JSSRC (Joint Spectrum Sharing and end-to-end data Rate Control) that iteratively adapts a frequency-agile radio network to optimum with regard to aggregate network spectrum utilization. Subsequently, we extend JSSRC to include routing and present TRSS (joint Transport, Routing and Spectrum Sharing) to solve the much more complex joint transport, routing and spectrum sharing optimization problem. Both JSSRC and TRSS enjoy theoretical convergence and achieve optimum with appropriate scheduling algorithms. The works together strive to improve efficiency of spectrum utilization in frequency-agile radio networks. Numerical and simulation studies show the effectiveness of our designs to reduce the so-called spectrum shortage problem. / Ph. D.

With dynamic spectrum access emerging as an important paradigm for efficient spectrum use, mechanisms are required to ensure disciplined spectrum access by secondary users. This must be done without requiring secondary users to disclose private data, such as their exact usage pattern or identities of parties involved. We formulate, design and evaluate a mechanism to collect spectrum activity information using a set of CPEs. A system design is presented which uses a number of techniques to address mobility and security issues involved in relying on CPEs to collect spectrum activity information. The system imposes an observation probability such that a rational cheater is dissuaded from spectrum misuse. The minimum number of CPEs required to impose this observation probability is determined by formulating it as an integer linear program. The security and privacy of this system is analyzed, along with simulation results to evaluate the quality of the solution. Based on the current design, directions for future work are identified and preliminary approaches are presented. / 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