This research addresses the performance degradation in receivers due to poor selectivity. Poor selectivity is expected to be a primary limitation on the performance of Dynamic-Spectrum-Access (DSA) and millimeter wave (mmWave) technologies. Both DSA and mmWave are highly desired technologies because they can address the spectrum-deficit problem that is currently challenging the wireless industry. Accordingly, addressing poor receiver selectivity is necessary to expedite the adoption of these technologies into the main street of wireless. This research develops two receiver design concepts to enhance the performance of poorly-selective receivers. The first concept is called cognitive RF front-end control (CogRF). CogRF operates by cognitively controlling the local-oscillator and sampling frequencies in receivers. This research shows that CogRF can fulfil the objective of pre-selectors by minimizing the effects of weak and moderately-powered neighboring-channel signals on the desired signal. This research shows that CogRF can be an alternative to high-performance pre-selectors, and hence, CogRF is a viable architecture to implement reliable DSA and mmWave receivers. The theoretical design and hardware implementation of a cognitive engine and a spectrum sensor of CogRF are reported in this dissertation. Measurement results show that CogRF significantly reduces the rate of communication outage due to interference from neighboring-channel signals in poorly-selective receivers. The results also indicate that CogRF can enable a poorly-selective receiver to behave like a highly-selective receiver. The second receiver design concept addresses very strong neighboring-channel signals. The performance of poorly selective receivers can easily suffer due to a strong, unfiltered neighboring-channel signal. A strong neighboring-channel signal is likely for a DSA radio that is operating in military radar bands. Traditionally, strong neighboring signals are addressed using an Automatic-Gain-Control (AGC) that attempt to accommodate the strong received signal into the dynamic range of the receiver. However, this technique potentially desensitizes the receiver because it sacrifices the Signal-to-Noise-Ratio (SNR) of the desired signal. This research proposes the use of auxiliary-receive path to address strong neighboring-channel signals with minimal penalty on the SNR of the desired signal. Through simulation based analysis, and hardware-based measurement, this research shows that the proposed technique can provide significant improvement in the neighboring-channel-interference handling capability of the receiver. / Ph. D.

Cognitive radio (CR) technology allows devices to share the wireless spectrum with other users that have a license for operation in these spectrum bands. This area of research promises to solve the problem of spectrum scarcity in the unlicensed bands, and improve the inefficient spectrum utilization in the bands reserved for the licensed users. However, the opportunistic use of the available spectrum by the CR users must not affect the licensed users. This raises several concerns regarding spectrum sensing, sharing and reliable end-to-end communication in CR networks. This thesis is concerned with the design and implementation of communication protocols for the multi-hop infrastructure-less CR ad-hoc networks (CRAHNs). In addition, it also addresses the critical issue of interference-free spectrum usage in specific ad-hoc architectures, such as, resource-constrained wireless sensor networks and wireless mesh networks that have high traffic volumes. The problems of spectrum management that are unique to CR networks are first identified in this thesis. These issues are then addressed at each layer of the network protocol stack while considering the distributed operation in CRAHNs. At the physical layer an algorithmic suite is proposed that allows the CR devices to detect and adapt to the presence of wireless LANs and commercial microwave ovens. A common control channel is designed that allows sharing of the spectrum information between the CR users, even when the available spectrum varies dynamically. A spectrum sharing scheme for mesh networks is proposed at the link layer that allows cooperative detection of the licensed users and fair utilization of the available spectrum among the mesh devices. The spectrum availability and route formation are then considered jointly at the network layer, so that the licensed users are protected as well as the CRAHN performance is maximized. Finally, we extend the classical TCP at the transport layer to ensure end-to-end reliability in a multi-hop CR environment.

Improving the efficiency of spectrum access and utilization under the umbrella of cognitive radio (CR) is one of the most crucial research areas for nearly two decades. The results have been algorithms called cognitive radio engines which use machine learning (ML) to learn and adapt the communication's link based on the operating scenarios. While a number of algorithms for cognitive engine design have been identified, it is widely understood that significant room remains to grow the capabilities of the cognitive engines, and substantially better spectrum utilization and higher throughput can be achieved if cognitive engines are improved. This requires working through some difficult challenges and takes an innovative look at the problem. A tenet of the existing cognitive engine designs is that they are usually designed around one primary ML algorithm or framework. In this dissertation, we discover that it is entirely possible for an algorithm to perform better in one operating scenario (combination of channel conditions, available energy, and operational objectives such as max throughput, and max energy efficiency) while performing less effectively in other operating scenarios. This arises due to the unique behavior of an individual ML algorithm regardless of its operating conditions. Therefore, there is no individual algorithm or parameter sets that have superiority in performance over all other algorithms or parameter sets in all operating scenarios. Using the same algorithm at all times may present a performance that is acceptable, yet may not be the best possible performance under all operating scenarios we are faced with over time. Ideally, the system should be able to adapt its behavior by switching between various ML algorithms or adjusting the operating ML algorithm for the prevailing operating conditions and goal. In this dissertation, we introduce a novel architecture for cognitive radio engines, with the goal of better cognitive engines for improved link adaptation in order to enhance spectrum utilization. This architecture is capable of meta-reasoning and metacognition and the algorithms developed based on this architecture are called metacognitive engines (meta-CE). Meta-reasoning and metacognitive abilities provide for self-assessment, self-awareness, and inherent use and adaptation of multiple methods for link adaptation and utilization. In this work, we provide four different implementation instances of the proposed meta-CE architecture. First, a meta-CE which is equipped with a classification algorithm to find the most appropriate individual cognitive engine algorithm for each operating scenario. The meta-CE switches between the individual cognitive engine algorithms to decrease the training period of the learning algorithms and not only find the most optimal communication configuration in the fastest possible time but also provide the acceptable performance during its training period. Second, we provide different knowledge indicators for estimating the experience level of cognitive engine algorithms. We introduce a meta-CE equipped with these knowledge indicators extracted from metacognitive knowledge component. This meta-CE adjusts the exploration factors of learning algorithms to gain higher performance and decrease training time. The third implementation of meta-CE is based on the robust training algorithm (RoTA) which switches and adjusts the individual cognitive engine algorithms to guarantee a minimum performance level during the training phase. This meta-CE is also equipped with forgetting factor to deal with non-stationary channel scenarios. The last implementation of meta-CE enables the individual cognitive engine algorithms to handle delayed feedback scenarios. We analyze the impact of delayed feedback on cognitive radio engines' performances in two cases of constant and varying delay. Then we propose two meta-CEs to address the delayed feedback problem in cognitive engine algorithms. Our experimental results show that the meta-CE approach, when utilized for a CRS engine performed about 20 percent better (total throughput) than the second best performing algorithm, because of its ability to learn about its own learning and adaptation. In effect, the meta-CE is able to deliver about 70% more data than the CE with the fixed exploration rate in the 1000 decision steps. Moreover, the knowledge indicator (KI) autocorrelation plots show that the proposed KIs can predict the performance of the CEs as early as 100 time steps in advance. In non-stationary environments, the proposed RoTA based meta-CE guarantees the minimum required performance of a CRS while it’s searching for the optimal communication configurations. The RoTA based meta-CE delivers at least about 45% more data than the other algorithms in non-stationary scenarios when the channel conditions are often fluctuating. Furthermore, in delayed feedback scenarios, our results show that the proposed meta-CE algorithms are able to mitigate the adverse impact of delay in low latency scenarios and relieve the effects in high latency situations. The proposed algorithms show a minimum of 15% improvement in their performance compared to the other available delayed feedback strategies in literature. We also empirically tested the algorithms introduced in this dissertation and verified the results therein by designing an over the air (OTA) radio setup. For our experiments, we used GNU Radio and LiquidDSP as free software development toolkits that provide signal processing blocks to implement software-defined radios and signal-processing systems such as modulation, pulse-shaping, frame detection, equalization, and others. We also used two USRP N200 with WBX daughterboards, one as a transmitter and the other as a receiver. In these experiments, we monitored the packet success rate (PSR), throughput, and total data transferred as our key performance indicators (KPI). Then, we tested different proposed meta-CE algorithms in this dissertation to verify the productivity of the proposed algorithms in an OTA real-time radio setup. We showed that the experiments’ outputs support our simulations results as well.

Cognitive radio (CR) networks and heterogeneous cellular networks are promising approaches to satisfy the demand for higher data rates and better connectivity. A CR network increases the utilization of the radio spectrum by opportunistically using it. Heterogeneous networks provide high data rates and improved connectivity by spatially reusing the spectrum and by bringing the network closer to the user. Interference presents a critical challenge for reliable communication in these networks. Accurately modeling it is essential in ensuring a successful design and deployment of these networks. We first propose modeling the aggregate interference power at a primary receiver (PU-Rx) caused from transmissions by randomly located cognitive users (CUs) in a CR network as a shifted lognormal random process. Its parameters are determined using a moment matching method. Extensive benchmarking shows that the proposed model is more accurate than the lognormal and Gaussian process models considered in the literature, even for a relatively dense deployment of CUs. It also compares favorably with the asymptotically exact stable and symmetric truncated stable distribution models, except at high CU densities. Our model accounts for the effect of imperfect spectrum sensing, interweave and underlay modes of CR operation, and path-loss, time-correlated shad-owing and fading of the various links in the network. It leads to new expressions for the probability distribution function, level crossing rate (LCR), and average exceedance duration (AED). The impact of cooperative spectrum sensing is also characterized. We also apply and validate the proposed model by using it to redesign the primary exclusive zone to account for the time-varying nature of interference. Next we model the uplink inter-cell aggregate interference power in homogeneous and heterogeneous cellular systems as a simpler lognormal random variable. We develop a new moment generating function (MGF) matching method to determine the lognormal’s parameters. Our model accounts for the transmit power control, peak transmit power constraint, small scale fading and large scale shadowing, and randomness in the number of interfering mobile stations and their locations. In heterogeneous net-works, the random nature of the number and locations of low power base stations is also accounted for. The accuracy of the proposed model is verified for both small and large values of interference. While not perfect, it is more accurate than the conventional Gaussian and moment-matching-based lognormal and Gamma distribution models. It is also performs better than the symmetric-truncated stable and stable distribution models, except at higher user density.

ITC/USA 2009 Conference Proceedings / The Forty-Fifth Annual International Telemetering Conference and Technical Exhibition / October 26-29, 2009 / Riviera Hotel & Convention Center, Las Vegas, Nevada / Emerging and next-generation test instrumentation increasingly relies on network communication to manage complex and dynamic test scenarios, particularly for uninhabited autonomous systems. Adapting wireless communication infrastructure to accommodate challenging testing needs can benefit from reconfigurable radio technology. Frequency agility is one characteristic of reconfigurable radios that to date has seen only limited progress toward programmability. This paper overviews an ongoing project to validate a promising chipset that performs conversion of RF signals directly into digital data for the wireless receiver and, for the transmitter, converts digital data into RF signals. The Software Configurable Multichannel Transceiver (SCMT) enables four transmitters and four receivers in a single unit, programmable for any frequency band between 1 MHz and 6 GHz.

The widespread application of wireless services and the requirements of ubiquitous access have recently triggered rapidly booming energy consumption in wireless communications networks. Such escalation of energy consumption in wireless networks causes high operational expenditure from electricity bills for operators, unsatisfactory user experience due to limited battery capacity of wireless devices, and a large amount of greenhouse gas emission. Green radio (GR), which emphasizes both energy efficiency (EE) and spectral efficiency (SE), has been proposed as an effective solution and is becoming the mainstream for future wireless network design. Unfortunately, EE and SE do not always coincide and may even sometimes conflict. In this dissertation, we focus on energy-efficient transmission and resource allocation techniques for orthogonal frequency division multiple access (OFDMA) networks and the joint energy-efficient design of OFDMA and other promising wireless communications techniques, such as cognitive radio (CR) and two-way relay. Firstly, we investigate the principles of energy-efficient design for pure OFDMA networks. As the first step, we study the fundamental interrelationship between EE and SE in downlink OFDMA networks and analyze the impacts of channel gain and circuit power on the EE-SE relationship. We establish a general EE-SE optimization framework, where the overall EE, SE and per-user quality-of-service (QoS) are all considered. Under this framework, we find that EE is quasiconcave in SE and decreases with SE when SE is large enough. These findings are very helpful guidelines for designing energy- and spectral-efficient OFDMA. To facilitate the application of energy-efficient resource allocation, we then investigate the energy-efficient resource allocation in both downlink and uplink OFDMA networks. For the downlink transmission, the generalized EE is maximized while for the uplink case the minimum individual EE is maximized, both under prescribed per-user minimum data rate requirements. For both transmission scenarios, we first provide the optimal solution and then develop an computationally efficient suboptimal approach by exploring the inherent structure and property of the energy-efficient design. Then we study energy-efficient design in downlink OFDMA networks with effective capacity-based delay provisioning for delay-sensitive traffic. By integrating information theory with the concept of effective capacity, we formulate and solve an EE optimization problem with statistical delay provisioning. We also analyze the tradeoff between EE and delay, the relationship between spectral-efficient and energy-efficient designs, and the impact of system parameters, including circuit power and delay exponents, on the overall performance. Secondly, we consider joint energy-efficient design of OFDMA and CR and two-way relay, respectively, to further enhance the EE and SE of wireless networks. We study energy-efficient opportunistic spectrum access strategies for an OFDMA-based CR network with multiple secondary users (SUs). Both worst EE and average EE of the SUs are considered and optimized subject to constraints including maximum transmit power and maximum interference to primary user (PU) system. For both cases, we first find the optimal solution and then propose a low-complexity suboptimal alternative. The results show that the energy-efficient CR strategies significantly boost EE compared with the conventional spectral-efficient CR ones while the low-complexity suboptimal approaches can well balance the performance and complexity. Then we study energy-efficient resource allocation for OFDMA-based two-way relay, which aims at maximizing the aggregated EE utility while provisioning proportional fairness in EE among different terminal pairs. Different from most exist energy-efficient design, we consider a new circuit power model, where the dynamic circuit power is proportional to the number of active subcarrier. For low-complexity solution, we propose an EE-oriented sequential subchannel assignment policy and discover the sufficient condition for early termination of the sequential subchannel assignment without losing the EE optimality. It is found that the energy-efficient transmission does not necessarily make all the subcarriers active, which is another useful principle for practical energy-efficient system design.

The cognitive radio network (CRN) concept has been proposed as a solution to the growing demand and underutilization of the radio spectrum. To improve the radio spectrum utilization, CRN technology allows the coexistence of licensed and unlicensed systems over the same spectrum. In an underlay spectrum sharing system, secondary users (SUs) transmit simultaneously with the primary users (PUs) in the same frequency band given that the interference caused by the SU to the PU remains below a tolerable interference limit. Besides the transmission power limitation, a secondary network is subject to distinct channel impairments such as fading and interference from the primary transmissions. Also, CRNs face new security threats and challenges due to their unique cognitive characteristics.This thesis analyzes the performance of underlay CRNs and underlay cognitive relay networks under spectrum sharing constraints and security constraints. Distinct SU transmit power policies are obtained considering various interference constraints such as PU outage constraint or PU peak interference power constraint. The thesis is divided into an introduction and two research parts based on peer-reviewed publications. The introduction provides an overview of radio spectrum management, basic concepts of CRNs, and physical layer security. In the first research part, we study the performance of underlay CRNs with emphasis on a multiuser environment.In Part I-A, we consider a secondary network with delay-tolerant applications and analyze the ergodic capacity. Part I-B analyzes the secondary outage capacity which characterises the maximum data rate that can be achieved over a channel for a given outage probability. In Part I-C, we consider a secondary network with delay constrained applications, and derive expressions of the outage probability and delay-limited throughput. Part I-D presents a queueing model that provides an analytical tool to evaluate the secondary packet-level performance with multiple classes of traffic considering general interarrival and service time distributions. Analytical expressions of the SU average packet transmission time, waiting time in the queue, andtime spent in the system are provided.In the second research part, we analyze the physical layer security for underlay CRNs and underlay cognitive relay networks. Analytical expressions of the probability of non-zero secrecy capacity and secrecy outage probability are derived.Part II-A considers a single hop underlay CRN in the presence of multiple eavesdroppers (EAVs) and multiple SU-Rxs. In Part II-B, an underlay cognitive relay network in the presence of multiple secondary relays and multiple EAVs is studied.Numerical examples illustrate that it is possible to exploit the physical layer characteristics to achieve both security and quality of service in CRNs while satisfying spectrum sharing constraints.

Relay techniques have the potential to enhance capacity and coverage of a wireless network. Due to rapidly increasing number of smart phone subscribers and high demand for data intensive multimedia applications, the useful radio spectrum is becoming a scarce resource. For this reason, two way relay network and cognitive radio technologies are required for better utilization of radio spectrum. Compared to the conventional one way relay network, both the uplink and the downlink can be served simultaneously using a two way relay network. Hence the effective bandwidth efficiency is considered to be one time slot per transmission. Cognitive networks are wireless networks that consist of different types of users, a primary user (PU, the primary license holder of a spectrum band) and secondary users (SU, cognitive radios that opportunistically access the PU spectrum). The secondary users can access the spectrum of the licensed user provided they do not harmfully affect to the primary user. In this thesis, various resource allocation and optimization techniques have been investigated for wireless relay and cognitive radio networks.

Although the primary purpose of the signal received by amobile handset or smartphone is to enable wireless communication, the information extracted can be reused to provide a number of additional services. Two such services discussed in this thesis are: mobile speed estimation and signal anomaly detection. The proposed algorithms exploit the propagation environment specific information that is already imprinted on the received signal and therefore do not incur any additional signalling overhead. Speed estimation is useful for providing navigation and location based services in areas where global navigation satellite systems (GNSS) based devices are unusable while the proposed anomaly detection algorithms can be used to locate signal faults and aid spectrum sensing in cognitive radio systems. The speed estimation algorithms described within this thesis require a receiver with at least two antenna elements and a wideband radio frequency (RF) signal source. The channel transfer function observed at the antenna elements are compared to yield an estimate of the device speed. The basic algorithm is a one-dimensional and unidirectional two-antenna solution. The speed of the mobile receiver is estimated from a knowledge of the fixed inter-antenna distance and the time it takes for the trailing antenna to sense similar channel conditions previously observed at the leading antenna. A by-product of the algorithm is an environment specific spatial correlation function which may be combined with theoretical models of spatial correlation to extend and improve the accuracy of the algorithm. Results obtained via computer simulations are provided. The anomaly detection algorithms proposed in this thesis highlight unusual signal features while ignoring events that are nominal. When the test signal possesses a periodic frame structure, Kullback-Leibler divergence (KLD) analysis is employed to statistically compare successive signal frames. A method of automatically extracting the required frame period information from the signal is also provided. When the signal under test lacks a periodic frame structure, information content analysis of signal events can be used instead. Clean training data is required by this algorithm to initialise the reference event probabilities. In addition to the results obtained from extensive computer simulations, an architecture for field-programmable gate array (FPGA) based hardware implementations of the KLD based algorithm is provided. Results showing the performance of the algorithms against real test signals captured over the air are also presented. Both sets of algorithms are simple, effective and have low computational complexity – implying that real-time implementations on platforms with limited processing power and energy are feasible. This is an important quality since location based services are expected to be an integral part of next generation cognitive radio handsets.

Recently, wireless access has become an essential part of modern society. Consequently, the demand for new wireless applications and services, as well as the number of wireless users, are gradually increasing. Given that this amount of expansion is eventually controlled by the available radio frequency spectrum, government regulatory agencies have recently adopted a strict approach to the licensing of limited amounts of spectrum to different entities (e.g., public safety, military, service providers, unlicensed devices, and TV). All of them possess exclusive transmissions to their assigned frequency channels. A new study on spectrum efficiency revealed big geographic and temporal variations in spectrum utilisation, ranging from 15-85% in the bands below 3GHz. These variations were less at frequencies above this figure. Recently, the Cognitive Radio (CR) has risen as an encouraging piece of technology to improve spectrum efficiency and to solve the problem of spectrum scarcity. This is because CR allows the secondary (unlicensed) users to occupy unused licensed spectrum bands temporarily, given that the interference of the primary (licensed) users is prohibited or minimised. In this thesis, various spectrum handoff management schemes have been proposed in order to improve the performance evaluation for CR networks. The proposed spectrum handoff schemes use the Opportunistic Spectrum Access (OSA) concept to utilise available spectrum bands. The handoff Secondary Users (SUs) have a higher priority to occupy available spectrum channels in the licensed and unlicensed spectrum bands without interfering with the legacy spectrum owner, i.e. primary users (PUs). However, existing spectrum handoff management schemes in CR networks do not provide high transmission opportunities for handoff secondary users to utilise the available radio spectrum resources. The first part of this thesis addresses the issue of spectrum handoff management in a licensed spectrum band environment. In this case, both reactive and proactive spectrum handoff schemes are proposed. Queuing theory or/and simulation experiments have been used to evaluate the performance of the proposed schemes and compare them with other existing schemes. Handoff delay has mainly been used to investigate the impact of successive handoff operations on the performance of the proposed CR networks. Implemented models have shown an improvement in the adopted performance measures. According to the achieved results, the improvement of the proposed, prioritised handoff schemes in some cases is approximately 75% when compared with existing schemes. On the other hand, the second part of this research proposed a prioritised spectrum handoff scheme in a heterogeneous spectrum environment, which is composed of a pool of licensed and unlicensed spectrum channels. In general, the availability of substantial numbers of the licensed spectrum channels is the key benefit of using this type of radio spectrum channel. Whereas, accessing with equal rights for all types of users is the main advantage of using unlicensed spectrum channels. In this respect, no transmission interruptions occur once a user obtains a channel. In addition, the proposed schemes use only the unlicensed spectrum channels as their backup channels. This enables the user to resume interrupted transmission in the case of the spectrum handoff operation (mainly; due to the appearance of the primary users), and thus facilitates a SUs communication. The proposed principle is investigated using a retrial queuing theory as well as extensive simulation experiments, and is compared with another non-prioritised scheme which do not give any preference to handoff SUs over new SUs. The results indicate that the proposed model has improved on current average handoff delay. This thesis contributes to knowledge by further enhancing the efficient utilisation of available radio spectrum resources and therefore subsequently provides an improvement in the spectrum capacity for wireless cognitive radio networks.