This thesis conducts a performance analysis of cognitive transmission in a multiple- cell environment. Most of the cognitive radio (CR)-related research has focused on scenarios where a secondary system operates in the presence of a single primary com- munication system. In this work, we extend the study of a single-cell scenario to a more practical scenario where the secondary system is subjected to two independent primary users (PU). In particular, we investigate the performance of a secondary system operating in an interweaving fashion to explore the spectrum of opportuni- ties. Under the assumption of the Poison traffic model for PU activities, we apply the Markov chain model to first determine the system parameters for combined PUs activities, and then characterize the dynamics of the spectrum opportunities for a secondary user (SU) for both single- and multiple-channel access. To fully inves- tigate the proposed system, we also consider some possible drawbacks and provide corresponding solutions in the extension section. We derive the exact mathematical expressions for the performance metrics, in- cluding average waiting time and average service time of the SU transmission. To enrich the performance analysis, other performance metrics, such as average through- put and collision frequency/ratio are also presented. Through selected numerical examples, we examine the effect of different operation parameters on the SU system performance. We believe that those analytical results can help predict which types of SU applications can be supported under certain practical PU activities. / Graduate

Cognitive Radio (CR) is considered to be a novel approach to improve the underutilization of precious radio resources by exploiting the unused licensed spectrum in dynamically changing environments. Designing efficient resource allocation algorithms for dynamic spectrum sharing and for power allocation in OFDM-CR networks is still a challenging problem. In this thesis, we specifically deal with these two problems. Dynamic spectrum sharing for the unlicensed secondary users (SU)s with device coordination could minimize the wastage of the spectrum. But this is a feasible approach only if the network considers the fairness criterion. We study the dynamic spectrum sharing problem for device coordinated cognitive radio networks with respect to fairness. We propose a simple modified proportional fair algorithm for a dynamic spectrum sharing scenario with two constraints, time and utility. Utility is measured by the amount of data processed and time is measured as the duration of a slot. This algorithm could result in variable or fixed length time slots. We will discuss the several controls possible on the algorithm and the possible extension of this algorithm for multicarrier OFDM based CR systems. Traditional water-filling algorithm is inefficient for OFDM-CR networks due to the interaction with primary users (PU)s. We consider reliability/availability of subcarriers or primary user activity for power allocation. We model this aspect mathematically with a risk-return model by defining a general rate loss function. We then propose optimal and suboptimal algorithms to allocate power under a fixed power budget for such a system with linear rate loss. These algorithms as we will see allocate more power to more reliable subcarriers in a water-filling fashion with different water levels. We compare the performance of these algorithms for our model with respect to water-filling solutions. Simulations show that suboptimal schemes perform closer to optimal scheme although they could be implemented with same complexity as water-filling algorithm. We discuss the linearity of loss function and guidelines to choose its coefficients by obtaining upper bounds on them. Finally we extend this model for interference-limited OFDM-CR systems.

Cognitive Radio (CR) is considered to be a novel approach to improve the underutilization of precious radio resources by exploiting the unused licensed spectrum in dynamically changing environments. Designing efficient resource allocation algorithms for dynamic spectrum sharing and for power allocation in OFDM-CR networks is still a challenging problem. In this thesis, we specifically deal with these two problems. Dynamic spectrum sharing for the unlicensed secondary users (SU)s with device coordination could minimize the wastage of the spectrum. But this is a feasible approach only if the network considers the fairness criterion. We study the dynamic spectrum sharing problem for device coordinated cognitive radio networks with respect to fairness. We propose a simple modified proportional fair algorithm for a dynamic spectrum sharing scenario with two constraints, time and utility. Utility is measured by the amount of data processed and time is measured as the duration of a slot. This algorithm could result in variable or fixed length time slots. We will discuss the several controls possible on the algorithm and the possible extension of this algorithm for multicarrier OFDM based CR systems. Traditional water-filling algorithm is inefficient for OFDM-CR networks due to the interaction with primary users (PU)s. We consider reliability/availability of subcarriers or primary user activity for power allocation. We model this aspect mathematically with a risk-return model by defining a general rate loss function. We then propose optimal and suboptimal algorithms to allocate power under a fixed power budget for such a system with linear rate loss. These algorithms as we will see allocate more power to more reliable subcarriers in a water-filling fashion with different water levels. We compare the performance of these algorithms for our model with respect to water-filling solutions. Simulations show that suboptimal schemes perform closer to optimal scheme although they could be implemented with same complexity as water-filling algorithm. We discuss the linearity of loss function and guidelines to choose its coefficients by obtaining upper bounds on them. Finally we extend this model for interference-limited OFDM-CR systems. / Applied Science, Faculty of / Electrical and Computer Engineering, Department of / Graduate

There has been a growing demand for wireless communication services in the past few years. Recent reports reveal that the demand will not only increase in the number of subscribers but also in more diverse applications such as Machine-to-Machine (M2M) communications and the Internet of Things. With such demand for capacity increase, there is a necessity to shift from today’s Static Frequency Allocation (SFA) to Dynamic Spectrum Access (DSA). The change will make efficient use of spectrum by utilizing the unused parts in different times, frequencies and spaces. With this regard, cognitive radio (CR) is a powerful potential candidate for the spectrum scarcity problem. This work addresses the two main current discussions in Cognitive Radio Networks (CRN), spectral efficiency and interference mitigation problem. There are two main spectrum sharing techniques in CRN, overlay and underlay, which have been thoroughly investigated in the literature. Unlike the relative works which separate the use of overlay and underlay, this works considers the joint overlay and underlay as a hybrid system to enhance the spectral efficiency and Bit Error Rate (BER) performance in CRNs. MC-CDMA is proposed for underlay transmission for two main advantages. Firstly, for low power spectral density due to spreading. Secondly, for its capability to mitigate high interference. Two hybrid MC-CDMA schemes are proposed in this work. The first scheme spreads the underlay signal through the whole bandwidth to mitigate PU interference and benefit from the frequency diversity. To maximize data rate, overlay utilizes the available bands while keeping orthogonality with underlay using Orthogonal Variable Spreading Factor (OVSF) codes. To further increase capacity, an overload MC-CDMA system is proposed. In this scheme, overlay utilizes the full signal dimension, while underlay overloads the system. Two layered spreading is applied to differentiate overlay and underlay users. In order to detect the underlay signal, the overlay signal is detected first and is cancelled from the received signal. The underlay data is then detected from this modified signal. The framework is then extended to a multi-user underlay scenario. A code allocation algorithm is proposed in order to achieve low cross-correlation between the overlay and underlay users. The results show that the proposed overload system maintains good performance even in high PU interference level. Furthermore, the proposed hybrid capacities are optimized and compared with the two available hybrid systems in the literature. The proposed overload system showed to increase capacity significantly, both in AWGN and fading environment, in compared with the existing methods.

Cognitive radio is an important technology which aims to improve the spectrum resource utilization and allows a cognitive radio transceiver to detect and sense spectrum holes without causing interference to the primary users (PUs). As a result of the development of cognitive radio technology, the concept of cognitive radio ad hoc networks (CRAHNs) has recently been proposed in the literature, which aims to apply the cognitive radio to traditional ad hoc networks. However, this new network paradigm creates more research challenges than those in classical cognitive radio networks (CRNs). These research challenges in CRAHNs are due to the variable radio environments caused by spectrum-dependent communication links, hop-by-hop transmission, and changing topology. This study will focus on important research topics in spectrum management in scalable CRAHNs driven by local control, such as spectrum sharing, allocation, and mobility. To conduct this study, a local control approach is proposed to enable system-level analysis and protocol-level design with distributed protocols for spectrum sharing. In the local control approach, we can evaluate the system dynamics caused by either protocol-specific parameters or application-specific parameters in CRAHNs, which is hard to explore using existing methods. Moreover, combining the previous evaluations and scaling law analysis based on local control concept, we can design new distributed protocols based on the features of the medium access control (MAC) layer and the physical layer. In this study, the proposed research themes and related research issues surrounding spectrum sharing are discussed. Moreover, justification of the research has been made by experimental and analytical results. / Thesis (Ph.D, Electrical & Computer Engineering) -- Queen's University, 2013-02-04 14:37:45.883

Under the contemporary spectrum usage regulations, radio frequency bands are allocated statically to licensed users in a large geographical area and over a long period of time. Recent investigations have revealed that such static spectrum allocation has led to very poor usage of the overall spectrum. Cognitive radio has emerged as a new communication paradigm to improve the utilization of the radio spectrum. It is defined as an intelligent wireless communication system that allows coexistence of unlicensed users with the licensed ones as long as the perceived interference at the licensed user is capped below some acceptable level. In addition, the users in this system adopt efficient communication protocols to enhance spectral efficiency. We employ cooperative mechanisms wherein multiple users cooperate in order to accomplish the following tasks: 1) Cooperative spectrum sensing: In this task, the licensed users do not actively engage. Instead, the unlicensed users passively monitor the activity of the licensed users and transmit only during their absence. 2) Cooperative spectrum management: The licensed and unlicensed users can benefit from cooperation with each other, e.g., they can assist each other in transmission via relaying. In this fashion, they can save power or bandwidth and therefore, the whole network can accommodate more users. \end{itemize} In the first part of this thesis, we focus on cooperative spectrum sensing. We first study the performance of the optimal distributed detectors as the number of samples increases and identify the conditions under which the highest or lowest asymptotic performance is achieved. For each condition, we study several suboptimal detectors and obtain novel asymptotic expressions for their performance. We then consider distributed detection of an Orthogonal Frequency-Division Multiplexing (OFDM) signal source. We propose different optimal and suboptimal frequency-domain detectors and derive closed form expressions for their performance. These frequency-domain detectors, despite their lower computational complexity, outperform the state-of-the-art time-domain detectors. Finally, we consider distributed spectrum sensing in mixture-Nakagami fading channels. We propose several novel detectors that significantly outperform the traditional detectors. In all these cases, we prove that the suboptimal detectors are asymptotically optimal, i.e., their performance converges to the Uniformly Most Powerful (UMP) tests as the number of samples increases. In the second part of the thesis, we focus on cooperative spectrum management. We study the problem of cooperative relay selection and power allocation and determine the conditions, in terms of channel gains and network geometry, under which such cooperation leads to an increase in rate, or a reduction in power and bandwidth usage. Lastly, we propose cooperative protocols that exploit these results and greatly enhance spectrum efficiency. / Thesis (Ph.D, Mathematics & Statistics) -- Queen's University, 2013-06-04 18:23:24.845

As the demand for wireless communication services grows quickly, spectrum scarcity has been on the rise sharply. In this context, cognitive radio (CR) is being viewed as a new intelligent technology to solve the deficiency of fixed spectrum assignment policy in wireless communications. Spectrum sensing is one of the most fundamental technologies to realise dynamic spectrum access in cognitive radio networks. It requires high accuracy as well as low complexity. In this thesis, a novel adaptive threshold setting algorithm is proposed to optimise the trade-off between detection and false alarm probability in spectrum sensing while satisfying sensing targets set by the IEEE 802.22 standard. The adaptive threshold setting algorithm is further applied to minimise the error decision probability with varying primary users' spectrum utilisations. A closed-form expression for the error decision probability, satisfied SNR value, number of samples and primary users' spectrum utilisation ratio are derived in both fixed and the proposed adaptive threshold setting algorithms. By implementing both Welch and wavelet based energy detectors, the adaptive threshold setting algorithm demonstrates a more reliable and robust sensing result for both primary users (PUs) and secondary users (SUs) in comparison with the conventional fixed one. Furthermore, the wavelet de-noising method is applied to improve the sensing performance when there is insu cient number of samples. Finally, a novel database assisted spectrum sensing algorithm is proposed for a secondary access of the TV White Space (TVWS) spectrum. The proposed database assisted sensing algorithm is based on the developed database assisted approach for detecting incumbents like Digital Terrestrial Television (DTT) and Programme Making and Special Events (PMSE), but assisted by spectrum sensing to further improve the protection to primary users. Monte-Carlo simulations show a higher SUs' spectrum efficiency can be obtained for the proposed database assisted sensing algorithm than the existing stand-alone database assisted or sensing models.

Space-based communications systems to be employed by future artificial satellites, or spacecraft during exploration missions, can potentially benefit from software-defined radio adaptation capabilities. Multiple communication requirements could potentially compete for radio resources, whose availability of which may vary during the spacecraft's operational life span. Electronic components are prone to failure, and new instructions will eventually be received through software updates. Consequently, these changes may require a whole new set of near-optimal combination of parameters to be derived on-the-fly without instantaneous human interaction or even without a human in-the-loop. Thus, achieving a sufficiently set of radio parameters can be challenging, especially when the communication channels change dynamically due to orbital dynamics as well as atmospheric and space weather-related impairments. This dissertation presents an analysis and discussion regarding novel algorithms proposed in order to enable a cognition control layer for adaptive communication systems operating in space using an architecture that merges machine learning techniques employing wireless communication principles. The proposed cognitive engine proof-of-concept reasons over time through an efficient accumulated learning process. An implementation of the conceptual design is expected to be delivered to the SDR system located on the International Space Station as part of an experimental program. To support the proposed cognitive engine algorithm development, more realistic satellite-based communications channels are proposed along with rain attenuation synthesizers for LEO orbits, channel state detection algorithms, and multipath coefficients function of the reflector's electrical characteristics. The achieved performance of the proposed solutions are compared with the state-of-the-art, and novel performance benchmarks are provided for future research to reference.

Cognitive radios (CRs) have been proposed as a promising solution for improving spectrum utilization via opportunistic spectrum sharing. In a CR network environment, primary (licensed) users have priority over secondary (unlicensed) users when accessing the wireless channel. Thus, if a malicious secondary user exploits this spectrum access etiquette by mimicking the spectral characteristics of a primary user, it can gain priority access to a wireless channel over other secondary users. This scenario is referred to in the literature as primary user emulation (PUE). This dissertation first covers three approaches for detecting primary user emulation attacks in cognitive radio networks, which can be classified in two categories. The first category is based on cyclostationary features, which employs a cyclostationary calculation to represent the modulation features of the user signals. The calculation results are then fed into an artificial neural network for classification. The second category is based on video processing method of action recognition in frequency domain, which includes two approaches. Both of them analyze the FFT sequences of wireless transmissions operating across a cognitive radio network environment, as well as classify their actions in the frequency domain. The first approach employs a covariance descriptor of motion-related features in the frequency domain, which is then fed into an artificial neural network for classification. The second approach is built upon the first approach, but employs a relational database system to record the motion-related feature vectors of primary users on this frequency band. When a certain transmission does not have a match record in the database, a covariance descriptor will be calculated and fed into an artificial neural network for classification. This dissertation is completed by a novel PUE detection approach which employs a distributed sensor network, where each sensor node works as an independent PUE detector. The emphasis of this work is how these nodes collaborate to obtain the final detection results for the whole network. All these proposed approaches have been validated via computer simulations as well as by experimental hardware implementations using the Universal Software Radio Peripheral (USRP) software-defined radio (SDR) platform.

In this thesis, as an extension to [1], we propose a prioritized multi-layer network coding scheme for collaborative packet recovery in hybrid (interweave and underlay) cellular cognitive radio networks. This scheme allows the uncoordinated collaboration between the collocated primary and cognitive radio base-stations in order to minimize their own as well as each other’s packet recovery overheads, thus by improving their throughput. The proposed scheme ensures that each network’s performance is not degraded by its help to the other network. Moreover, it guarantees that the primary network’s interference threshold is not violated in the same and adjacent cells. Yet, the scheme allows the reduction of the recovery overhead in the collocated primary and cognitive radio networks. The reduction in the cognitive radio network is further amplified due to the perfect detection of spectrum holes which allows the cognitive radio base station to transmit at higher power without fear of violating the interference threshold of the primary network. For the secondary network, simulation results show reductions of 20% and 34% in the packet recovery overhead, compared to the non-collaborative scheme, for low and high probabilities of primary packet arrivals, respectively. For the primary network, this reduction was found to be 12%. Furthermore, with the use of fractional cooperation, the average recovery overhead is further reduced by around 5% for the primary network and around 10% for the secondary network when a high fractional cooperation probability is used.