Wireless communications systems underwent an evolution as the voice oriented applications evolved to data and multimedia based services. Furthermore, current wireless technologies, regulations and the un- derstanding of the technology are insufficient for the requirements of future wireless systems. Along with the rapid rise at the number of users, increasing demand for more communications capacity to deploy multimedia applications entail effective utilization of communications resources. Therefore, there is a need for effective spectrum allocation, adaptive and complex modulation, error recovery, channel estimation, diversity and code design techniques to allow high data rates while maintaining desired quality of service, and reconfigurable and flexible air interface technologies for better interference and fading management. However, traditional communications system design is based on allocating fixed amounts of resources to the user and does not consider adaptive spectrum utilization. Technologies which will lead to adaptive, intelligent, and aware wireless communications systems are expected to come up with consistent methodologies to provide solutions for the capacity, interference, and reliability problems of the wireless networks. Spectrum sensing feature of cognitive radio systems are a step forward to better recognize the problems and to achieve efficient spectrum allocation. On the other hand, even though spectrum sensing can constitute a solid base to achieve the reconfigurability and awareness goals of next generation networks, a new perspective is required to benefit from the whole dimensions of the available electro hyperspace. Therefore, spectrum sensing should evolve to a more general and comprehensive awareness providing a mechanism, not only as a part of CR systems which provide channel occupancy information but also as a communication environment awareness component of dynamic spectrum access paradigm which can adapt sensing parameters autonomously to ensure robust identification and parameter estimation for the signals over the monitored spectrum. Such an approach will lead to recognition of communications opportunities in different dimensions of spectrum hyperspace, and provide necessary information about the air interfaces, access techniques and waveforms that are deployed over the monitored spectrum to accomplish adaptive resource management and spectrum access. We define multidimensional signal analysis as a methodology, which not only provides the information that the spectrum hyperspace dimension in interest is occupied or not, but also reveals the underlaying information regarding to the parameters, such as employed channel access methods, duplexing techniques and other parameters related to the air interfaces of the signals accessing to the monitored channels and more. To achieve multidimensional signal analysis, a comprehensive sensing, classification, and a detection approach is required at the initial stage. In this thesis, we propose the multidimensional signal analysis procedures under signal identification algorithms in time, frequency. Moreover, an angle of arrival estimation system for wireless signals, and a spectrum usage modeling and prediction method are proposed as multidimensional signal analysis functionalities.

This thesis considers resource management issues in wireless sensor networks (WSNs), wireless local area networks (WLANs), and cognitive radio (CR) networks. Since energy is a critical resource in WSNs, we consider energy minimization techniques based on explicit node cooperation and distributed source coding (DSC). The explicit node cooperation based on space time block codes (STBC) improves energy efficiency of WSNs, by reducing the energy consumption per bit of each sensor node. The DSC on the other hand exploits the spatial correlation in WSNs, and thus reduces the data generated in a WSN. For the purpose of our analysis, we model the spatial correlation according to a linear Gauss-Markov model. Through our numerical results, we observe that the node cooperation combined with DSC can improve energy efficiency for many cases of interest. A unique aspect of our work is we obtain important structural results using the concepts from monotone comparative statics. These structural results provide insights into the general design of WSNs. Through our numerical results, we also demonstrate that, the cooperation based transmission can achieve better mutual information (MI)-energy tradeoff than the non-cooperation based transmission scheme. From the perspective of WLANs, we propose a price based approach to regulate the channel occupancy of low rate users, which is known to be the primary cause for low overall throughput in WLANs. Owing to the decentralized nature of WLANs we use non-cooperative game theory as a tool for analysis. Specifically, we use supermodular game theory. Through our analysis, we show that an increase in price leads to an increase in rate of WLAN users. We also prove that the best response dynamics indeed converge to the Nash equilibrium of the underlying non-cooperative game. Through our numerical results, we demonstrate that by proper tuning of the price, the proposed price based approach can lead to an improvement in overall throughput of a WLAN. Finally from the perspective of CR networks, we consider the impact of number of channels captured by a secondary user on its transmission control protocol (TCP) throughput. From our simulation results it was found that, there exists a definite optimal number of channels a secondary user needs to capture, to maximize its TCP throughput.

This doctoral thesis deals with design aspects of a reconfigurable frequency synthesizer for flexible radio transceivers in future cognitive multi-radios. The frequency bandwidth to be covered by this multi-radio synthesizer corresponds to the frequency bands of the most diffused wireless communication standards in the frequency band 800 MHz to 6 GHz. Since multi-standard operation is required, the synthesizer must fulfil the most stringent and sometimes conflicting requirements. Given these requirements, a novel approach for multi-mode frequency synthesis has been conceived. A hybrid phase locked loop based frequency synthesizer has been proposed and a novel switching protocol has been presented and validated on an experimental evaluation board. This approach combines fractional-N and integer-N modes of operation with switched loop filter topology. Compared to standard PLL techniques, the hybrid configuration provides a great flexibility in terms of reconfiguration and moreover, it offers relatively low circuit complexity and low power consumption. This architecture provides reconfiguration of the loop bandwidth, frequency resolution, phase noise and settling time performance and hence, it can adapt itself to diverse requirements given by the concerned wireless communication standards. Corresponding analyses, simulations and measurements have been carried out in order to verify the performance and functionality of the proposed solution. A part from the design of the multiband frequency synthesizer, a set of regional measurements of the radio spectrum utilization has been carried out in the framework of this dissertation research. These measurements are based on the energy detection principle and provide a close look at the degree of radio spectrum utilization in different regions, namely in the city of Brno in the Czech Republic and in the city of Paris and one of its suburbs in France. The goal of the experimental measurement campaign has been to estimate the degree of radio spectrum usage in a particular environment and to point out the fact that a new approach for radio spectrum management is inevitable

The sharing of the terrestrial TV frequency spectrum with Secondary Users (SUs) is presently the focus point of numerous research efforts worldwide. In many regulatory domains, contiguous blocks of VHF and UHF spectrum are available for exclusive use by the terrestrial TV broadcasting incumbents. However, this notion is currently challenged by the spectrum management paradigm of Dynamic Spectrum Access (DSA), advocating that this spectrum may be shared on a dynamic basis with SUs. The migration of analogue terrestrial TV to Digital Terrestrial Television (DTT) has also catalysed the notion that the terrestrial TV frequency spectrum will no longer be exclusively used for terrestrial broadcasting. Some administrations have already embraced this technology, reforming spectrum policy to allow unlicensed secondary access to the Spectral Opportunities (SOs) present in the terrestrial TV frequency bands. The Independent Communications Authority of South Africa (ICASA) has expressed early interest in the possibilities of TV white space technology and its possible utility in exploiting the SOs that exist in the terrestrial TV frequency bands. Core to the issues mentioned above is the quantification of the Spectral Opportunity (SO) available. To this end, the work presented in this thesis gives a quantified estimate of the SO available in South Africa. This work is the first of its kind for the South African environment and uncovers new knowledge regarding SO in South Africa. SO is analysed and quantified on provincial and national level for three discrete points in time: before the start of dual-illumination, during dual illumination and after analogue switch-off. A system model that is able to produce the required geo-referenced field strength coverage and SO maps is conceptualised and implemented. A complete standards compliant model is implemented from scratch, verified and validated, with design decisions specific to the South African context. The analysis methodology is developed with rigour. The construction of the TV transmitter database, definition of incumbent protection criteria and development of the required analysis metrics to quantify SO are presented. SO in the VHF and UHF terrestrial TV frequency bands is quantified by expressing SO in terms of the number of available channels, weighted respectively by land area and population density. The analysis results indicate that significant SO is available for exploitation by TV white space devices in the terrestrial TV spectrum in South Africa. The effects of radio astronomy advantage areas on the SO available are also investigated. The probability of finding contiguous channels in the Very High Frequency (VHF) and Ultra High Frequency (UHF) bands is also quantified. A comparative study, comparing the SO for South Africa with related work in Europe and the United States of America (USA), is also performed. Finally, maps that visualise the SO available are constructed for the three discrete time periods evaluated. / Thesis (PhD (Computer Engineering))--North-West University, Potchefstroom Campus, 2013

The sharing of the terrestrial TV frequency spectrum with Secondary Users (SUs) is presently the focus point of numerous research efforts worldwide. In many regulatory domains, contiguous blocks of VHF and UHF spectrum are available for exclusive use by the terrestrial TV broadcasting incumbents. However, this notion is currently challenged by the spectrum management paradigm of Dynamic Spectrum Access (DSA), advocating that this spectrum may be shared on a dynamic basis with SUs. The migration of analogue terrestrial TV to Digital Terrestrial Television (DTT) has also catalysed the notion that the terrestrial TV frequency spectrum will no longer be exclusively used for terrestrial broadcasting. Some administrations have already embraced this technology, reforming spectrum policy to allow unlicensed secondary access to the Spectral Opportunities (SOs) present in the terrestrial TV frequency bands. The Independent Communications Authority of South Africa (ICASA) has expressed early interest in the possibilities of TV white space technology and its possible utility in exploiting the SOs that exist in the terrestrial TV frequency bands. Core to the issues mentioned above is the quantification of the Spectral Opportunity (SO) available. To this end, the work presented in this thesis gives a quantified estimate of the SO available in South Africa. This work is the first of its kind for the South African environment and uncovers new knowledge regarding SO in South Africa. SO is analysed and quantified on provincial and national level for three discrete points in time: before the start of dual-illumination, during dual illumination and after analogue switch-off. A system model that is able to produce the required geo-referenced field strength coverage and SO maps is conceptualised and implemented. A complete standards compliant model is implemented from scratch, verified and validated, with design decisions specific to the South African context. The analysis methodology is developed with rigour. The construction of the TV transmitter database, definition of incumbent protection criteria and development of the required analysis metrics to quantify SO are presented. SO in the VHF and UHF terrestrial TV frequency bands is quantified by expressing SO in terms of the number of available channels, weighted respectively by land area and population density. The analysis results indicate that significant SO is available for exploitation by TV white space devices in the terrestrial TV spectrum in South Africa. The effects of radio astronomy advantage areas on the SO available are also investigated. The probability of finding contiguous channels in the Very High Frequency (VHF) and Ultra High Frequency (UHF) bands is also quantified. A comparative study, comparing the SO for South Africa with related work in Europe and the United States of America (USA), is also performed. Finally, maps that visualise the SO available are constructed for the three discrete time periods evaluated. / Thesis (PhD (Computer Engineering))--North-West University, Potchefstroom Campus, 2013

abstract: A principal goal of this dissertation is to study stochastic optimization and real-time scheduling in cyber-physical systems (CPSs) ranging from real-time wireless systems to energy systems to distributed control systems. Under this common theme, this dissertation can be broadly organized into three parts based on the system environments. The first part investigates stochastic optimization in real-time wireless systems, with the focus on the deadline-aware scheduling for real-time traffic. The optimal solution to such scheduling problems requires to explicitly taking into account the coupling in the deadline-aware transmissions and stochastic characteristics of the traffic, which involves a dynamic program that is traditionally known to be intractable or computationally expensive to implement. First, real-time scheduling with adaptive network coding over memoryless channels is studied, and a polynomial-time complexity algorithm is developed to characterize the optimal real-time scheduling. Then, real-time scheduling over Markovian channels is investigated, where channel conditions are time-varying and online channel learning is necessary, and the optimal scheduling policies in different traffic regimes are studied. The second part focuses on the stochastic optimization and real-time scheduling involved in energy systems. First, risk-aware scheduling and dispatch for plug-in electric vehicles (EVs) are studied, aiming to jointly optimize the EV charging cost and the risk of the load mismatch between the forecasted and the actual EV loads, due to the random driving activities of EVs. Then, the integration of wind generation at high penetration levels into bulk power grids is considered. Joint optimization of economic dispatch and interruptible load management is investigated using short-term wind farm generation forecast. The third part studies stochastic optimization in distributed control systems under different network environments. First, distributed spectrum access in cognitive radio networks is investigated by using pricing approach, where primary users (PUs) sell the temporarily unused spectrum and secondary users compete via random access for such spectrum opportunities. The optimal pricing strategy for PUs and the corresponding distributed implementation of spectrum access control are developed to maximize the PU's revenue. Then, a systematic study of the nonconvex utility-based power control problem is presented under the physical interference model in ad-hoc networks. Distributed power control schemes are devised to maximize the system utility, by leveraging the extended duality theory and simulated annealing. / Dissertation/Thesis / Ph.D. Electrical Engineering 2012

This thesis considers resource management issues in wireless sensor networks (WSNs), wireless local area networks (WLANs), and cognitive radio (CR) networks. Since energy is a critical resource in WSNs, we consider energy minimization techniques based on explicit node cooperation and distributed source coding (DSC). The explicit node cooperation based on space time block codes (STBC) improves energy efficiency of WSNs, by reducing the energy consumption per bit of each sensor node. The DSC on the other hand exploits the spatial correlation in WSNs, and thus reduces the data generated in a WSN. For the purpose of our analysis, we model the spatial correlation according to a linear Gauss-Markov model. Through our numerical results, we observe that the node cooperation combined with DSC can improve energy efficiency for many cases of interest. A unique aspect of our work is we obtain important structural results using the concepts from monotone comparative statics. These structural results provide insights into the general design of WSNs. Through our numerical results, we also demonstrate that, the cooperation based transmission can achieve better mutual information (MI)-energy tradeoff than the non-cooperation based transmission scheme. From the perspective of WLANs, we propose a price based approach to regulate the channel occupancy of low rate users, which is known to be the primary cause for low overall throughput in WLANs. Owing to the decentralized nature of WLANs we use non-cooperative game theory as a tool for analysis. Specifically, we use supermodular game theory. Through our analysis, we show that an increase in price leads to an increase in rate of WLAN users. We also prove that the best response dynamics indeed converge to the Nash equilibrium of the underlying non-cooperative game. Through our numerical results, we demonstrate that by proper tuning of the price, the proposed price based approach can lead to an improvement in overall throughput of a WLAN. Finally from the perspective of CR networks, we consider the impact of number of channels captured by a secondary user on its transmission control protocol (TCP) throughput. From our simulation results it was found that, there exists a definite optimal number of channels a secondary user needs to capture, to maximize its TCP throughput. / Applied Science, Faculty of / Electrical and Computer Engineering, Department of / Graduate

No description available.

In 2015, Federal Communications Commission (FCC) enabled shared commercial use of the 3.550-3.700 GHz band. A framework was developed to enable this spectrum-sharing capa- bility which included an automated frequency coordinator called Spectrum Access System (SAS). This work extends the open source SAS based on the aforementioned FCC SAS framework developed by researchers at Virginia Tech Wireless group, with real-time envi- ronment sensing capability along with intelligent incumbent detection using Software-defined Radios (SDRs) and a real-time graphical user interface. This extended version is called the OpenSAS. Furthermore, the SAS client and OpenSAS are extended to be compliant with the Wireless Innovation Forum (WINNF) specifications by testing the SAS-CBRS Base Station Device (CBSD) interface with the Google SAS Test Environment. The Environment Sensing Capability (ESC) functionality is evaluated and tested in our xG Testbed to verify its ability to detect the presence of users in the CBRS band. An ML-based feedforward neural net- work model is employed and trained using simulated radar waveforms as incumbent signals and captured 5G New Radio (NR) signals as a non-incumbent signal to predict whether the detected user is a radar incumbent or an unknown user. If the presence of incumbent radar is detected with an 85% or above certainty, incumbent protection is activated, terminating CBSD grants causing damaging interference to the detected incumbent. A 5G NR signal is used as a non-incumbent user and added to the training dataset to better the ability of the model to reject non-incumbent signals. The model achieves a maximum validation accuracy of 95.83% for signals in the 40-50 dB Signal-to-Noise Ratio (SNR) range. It achieves an 85.35% accuracy for Over the air (OTA) real-time tests. The non-incumbent 5G NR signal rejection accuracy is 91.30% for a calculated SNR range of 10-20 dB. In conclusion, this work advances state of the art in spectrum sharing systems by presenting an enhanced open source SAS and evaluating the newly added functionalities. / Master of Science / In 2015, Federal Communications Commission (FCC) enabled shared commercial use of the 3.550-3.700 GHz band. A framework was developed to enable this spectrum-sharing capability which included an automated frequency coordinator called Spectrum Access System (SAS). The task of the SAS is to make sure no two users use the same spectrum in the same location causing damaging interference to each other. The SAS is also responsible for prioritizing the higher tier users and protecting them from interference from lower tier users. This work extends the open source SAS based on the aforementioned FCC SAS framework developed by researchers at Virginia Tech Wireless group, with real-time environment sensing capability along with intelligent incumbent detection using Software-defined Radios (SDRs) and a real-time graphical user interface. This extended version is called the OpenSAS. Furthermore, the SAS client and OpenSAS are extended to be compliant with the Wireless Innovation Forum (WINNF) specifications by testing the SAS-CBRS Base Station Device (CBSD) interface with the Google SAS Test Environment. The Environment Sensing Capability (ESC) functionality is evaluated and tested in our xG Testbed to verify its ability to detect the presence of users in the CBRS band. The ESC is used to detect incumbent users (the highest tier) that do not inform the SAS about their use of the spectrum. An ML-based feedforward neural net- work model is employed and trained using simulated radar waveforms as incumbent signals and captured 5G New Radio (NR) signals as a non-incumbent signal to predict whether the detected user is a radar incumbent or an unknown user. If the presence of incumbent radar is detected with an 85% or above certainty, incumbent protection is activated, terminating CBSD grants causing damaging interference to the detected incumbent. A 5G NR signal is used as a non-incumbent user and added to the training dataset to better the ability of the model to reject non-incumbent signals. The model achieves a maximum validation accuracy of 95.83% for signals in the 40-50 dB Signal to-Noise Ratio (SNR) range. It achieves an 85.35% accuracy for Over the air (OTA) real-time tests. The non-incumbent 5G NR signal rejection accuracy is 91.30% for a calculated SNR range of 10-20 dB. In conclusion, this work advances state of the art in spectrum sharing systems by presenting an enhanced open source SAS and evaluating the newly added functionalities.

The heterogeneity and complexity of modern communication networks demands coupling network nodes with intelligence to perceive and adapt to different network conditions autonomously. Cognitive Networking is an emerging networking research area that aims to achieve this goal by applying distributed reasoning and learning across the protocol stack and throughout the network. Various cognitive node and cognitive network architectures with different levels of maturity have been proposed in the literature. All of them adopt the idea of coupling network devices with sensors to sense network conditions, artificial intelligence algorithms to solve problems, and a reconfigurable platform to apply solutions. However, little further research has investigated suitable reasoning and learning algorithms. In this dissertation, we take cognitive network research a step further by investigating the reasoning component of cognitive networks. In a deviation from previous suggestions, we suggest the use of a single flexible distributed reasoning algorithm for cognitive networks. We first propose an architecture for a cognitive node in a cognitive network that is general enough to apply to future networking challenges. We then introduce and justify our choice of the island genetic algorithm (iGA) as the distributed reasoning algorithm. Having introduced our cognitive node architecture, we then focus on the applicability of the island genetic algorithm as a single reasoning algorithm for cognitive networks. Our approach is to apply the island genetic algorithm to different single and cross layer communication and networking problems and to evaluate its performance through simulation. A proof of concept cognitive network is implemented to understand the implementation challenges and assess the island genetic algorithm performance in a real network environment. We apply the island genetic algorithm to three problems: channel allocation, joint power and channel allocation, and flow routing. The channel allocation problem is a major challenge for dynamic spectrum access which, in turn, has been the focal application for cognitive radios and cognitive networks. The other problems are examples of hard cross layer problems. We first apply the standard island genetic algorithm to a channel allocation problem formulated for the dynamic spectrum cognitive network environment. We also describe the details for implementing a cognitive network prototype using the universal software radio peripheral integrated with our extended implementation of the GNU radio software package and our island genetic algorithm implementation for the dynamic spectrum channel allocation problem. We then develop a localized variation of the island genetic algorithm, denoted LiGA, that allows the standard island genetic algorithm to scale and apply it to the joint power and channel allocation problem. In this context, we also investigate the importance of power control for cognitive networks and study the effect of non-cooperative behavior on the performance of the LiGA. The localized variation of the island genetic algorithm, LiGA, is powerful in solving node-centric problems and problems that requires only limited knowledge about network status. However, not every communication and networking problems can be solved efficiently in localized fashion. Thus, we propose a generalized version of the LiGA, namely the K-hop island genetic algorithm, as our final distributed reasoning algorithm proposal for cognitive networks. The K-hop island genetic algorithm is a promising algorithm to solve a large class of communication and networking problems with controllable cooperation and migration scope that allows for a tradeoff between performance and cost. We apply it to a flow routing problem that includes both power control and channel allocation. For all problems simulation results are provided to quantify the performance of the island genetic algorithm variation. In most cases, simulation and experimental results reveal promising performance for the island genetic algorithm. We conclude our work with a discussion of the shortcomings of island genetic algorithms without guidance from a learning mechanism and propose the incorporation of two learning processes into the cognitive node architecture to solve slow convergence and manual configuration problems. We suggest the cultural algorithm framework and reinforcement learning techniques as candidate leaning techniques for implementing the learning processes. However, further investigation and implementation is left as future work. / Ph. D.