Due to introduction of smart phones with data intensive multimedia and interactive applications and exponential growth of wireless devices, there is a shortage for useful radio spectrum. Even though the spectrum has become crowded, many spectrum occupancy measurements indicate that most of the allocated spectrum is underutilised. Hence radically new approaches in terms of allocation of wireless resources are required for better utilization of radio spectrum. This has motivated the concept of opportunistic spectrum sharing or the so-called cognitive radio technology that has great potential to improve spectrum utilization. The cognitive radio technology allows an opportunistic user namely the secondary user to access the spectrum of the licensed user (known as primary user) provided that the secondary transmission does not harmfully affect the primary user. This is possible with the introduction of advanced resource allocation techniques together with the use of wireless relays and spatial diversity techniques. In this thesis, various mathematical optimization techniques have been developed for the efficient use of radio spectrum within the context of spectrum sharing networks. In particular, optimal power allocation techniques and centralised and distributed beamforming techniques have been developed. Initially, an optimization technique for subcarrier and power allocation has been proposed for an Orthogonal Frequency Division Multiple Access (OFDMA) based secondary wireless network in the presence of multiple primary users. The solution is based on integer linear programming with multiple interference leakage and transmission power constraints. In order to enhance the spectrum efficiency further, the work has been extended to allow multiple secondary users to occupy the same frequency band under a multiple-input and multiple-output (MIMO) framework. A sum rate maximization technique based on uplink-downlink duality and dirty paper coding has been developed for the MIMO based OFDMA network. The work has also been extended to handle fading scenarios based on maximization of ergodic capacity. The optimization techniques for MIMO network has been extended to a spectrum sharing network with relays. This has the advantage of extending the coverage of the secondary network and assisting the primary network in return for the use of the primary spectrum. Finally, instead of considering interference mitigation, the recently emerged concept of interference alignment has been used for the resource allocation in spectrum sharing networks. The performances of all these new algorithms have been demonstrated using MATLAB based simulation studies.

High traffic load over the unlicensed portion of the radiospectrum (a.k.a., ISM bands) along with inefficient usage of thelicensed spectrum gave impetus for a new paradigm in spectrumallocation, whose main purpose is to improve spectrum efficiencythrough opportunistic access. Cognitive radios (CRs) havebeen proposed as a key enabling technology for such paradigm.Operating a CR network (CRN) without impacting the performance oflicensed (primary) users requires new protocols for informationexchange as well as mathematical tools to optimize thecontrollable parameters of the CRN. In this dissertation, wetarget the design of such protocols. First, we develop adistributed CRN MAC (COMAC) protocol that enables unlicensed usersto dynamically utilize the spectrum while limiting theinterference they inflict on primary (PR) users. The main noveltyin COMAC lies in not assuming a predefined CR-to-PR power mask andnot requiring coordination with PR users. Second, we propose anovel distance-dependent MAC protocol for CRNs in whicheach CR is equipped with multiple transceivers. Our protocol(called DDMAC) attempts to maximize the CRN throughput byfollowing a novel probabilistic channel assignment mechanism. Thismechanism exploits the dependence between the signal's attenuationmodel and the transmission distance while considering the trafficprofile. We show that through its distance- and traffic-aware,DDMAC significantly improves network throughput. Finally, weaddress the problem of assigning channels to CR transmissions,assuming one transceiver per CR. The main goal of our design is tomaximize the CRN throughput with respect to both spectrumassignment and transmission power. Specifically, we presentcentralized and distributed solutions that leverage the uniquecapabilities of CRs. Compared with previously proposed protocols,our schemes are shown to significantly improve network throughput.

This thesis focuses on the development of multiuser access schemes for spectrum sharing systems whereby secondary users that are randomly positioned over the coverage area are allowed to share the spectrum with primary users under the condition that the interference observed at the primary receiver is below a predetermined threshold. In particular, two scheduling schemes are proposed for selecting a user among those that satisfy the interference constraints and achieve an acceptable signal-to-noise ratio level above a predetermined signal-to-noise threshold at the secondary base station. The first scheme selects the user that reports the best channel quality. In order to alleviate the high feedback load required by the first scheme, a second scheme is proposed that is based on the concept of switched diversity where the base station scans the users in a sequential manner until an acceptable user is found. In addition, the proposed scheduling schemes operate under two power adaptive settings at the secondary users that are based on the amount of interference available at the secondary transmitter. In the On/Off power setting, users are allowed to transmit based on whether the interference constraint is met or not, while in the full power adaptive setting, users are allowed to vary their transmission power to satisfy the interference constraint. A special case of the proposed schemes is also analyzed whereby all the users are assumed to be at the same position, thus operating under the influence of independent and identically distributed Rayleigh fading channels. Finally, several numerical results are illustrated for the proposed algorithms where the trade-off between the average spectral efficiency and average feedback load of both schemes are shown.

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.

As we move towards the sixth generation (6G) of connectivity, satellites have been identified as an indispensable solution to bridge the digital divide. The satellites offer an extensive coverage footprint and can reach the most remote regions with high throughput, fueled by the large bandwidth available in higher frequency bands. As the low earth orbit (LEO) satellites are closer to the earth and therefore have lower latency, we could use a mega-constellation of LEO satellites to complement the terrestrial networks in 6G. However, the satellite and terrestrial networks may compete for the same spectrum band, thereby being a source of interference for each other. The mmWave bands have attracted the attention of LEO satellite networks and terrestrial mobile operators alike. Specifically, the 28-GHz mmWave band (27.5-29.5 GHz) is licensed to Fixed Satellite Services (FSS) for earth-to-satellite uplink transmissions, while the terrestrial networks will use it for downlink operation. The satellite networks are the primary users of the 28 GHz band, while it is also available for licensing to International Mobile Telecommunication (IMT) networks. In some countries, the 28 GHz band is also used for point-to-multipoint (PMP) wireless backhaul links. Therefore, in this work, we aim to understand the impact of the earth station uplink transmissions on the terrestrial users, viz., the cellular users, and the backhaul points, and suggest methods to facilitate the coexistence of these networks in the 28 GHz band through exclusion zones. The average data rate of the networks is derived through stochastic geometry, which results in expressions that are not closed-form. To optimize the data rates of the coexisting networks jointly, we first approximate the coverage probability expressions as closed-form sigmoid curves. This enables us to use gradient descent methods to determine the optimal radii of the exclusion zones.

In this dissertation, we studied and addressed the privacy-preserving and authentication techniques for some network applications, where existing internet security solutions cannot address them straightforwardly due to different trust and attack models and possibly constrained resources. For example, in a centralized dynamic spectrum access (DSA) system, the spectrum resource licensees called incumbent users (IUs), have strong operational privacy requirements for the DSA service provider called spectrum access system (SAS), and hence SAS is required to perform spectrum computation without knowing IUs' operational information. This means SAS can at most be considered as a semi-trusted party which is honest but curious, and common anonymization and end-to-end encryption cannot address this issue, and dedicated solutions are required. Another example is that in an intra-vehicle Controller Area Network (CAN), the transmitter can only embed 64 bits of message and its authentication tag into on message frame, which makes it difficult to achieve message authentication in real-time with sufficient cryptographic strength. The focus of this dissertation is to fill the gap of existing solutions with stronger security notion and practicability. On the topic of privacy-preserving DSA systems, we firstly explored existing solutions and proposed a comparative study. We additionally proposed a new metric for evaluation and showed the advantages and disadvantages of existing solutions. We secondly studied the IU location privacy in 3.5GHz band ESC-based DSA system and proposed a novel scheme called PriDSA. PriDSA addresses malicious colluding SAS attack model through leveraging different and relatively lightweight cryptography primitive with novel design, granting stronger security notion and improved efficiency as well. We thirdly studied the operational privacy of both IU and secondary users (SUs) in a general centralized SAS based DSA system and proposed a novel framework called PeDSS. Through our novel design that integrates differential privacy with secure multi-party computation protocol, PeDSS exhibits great communication and computation overhead compared to existing solutions. On the topic of lightweight message authentication in resource-constrained networks, we firstly explored message authentication schemes with high cryptographic strength and low communication-overhead and proposed a novel scheme called CuMAC. CuMAC provides a flexible trade-off between authentication delay and cryptographic strength, through the embodiment of a novel concept that we refer to as accumulation of cryptographic strength. We secondly explored the possibility of achieving both high cryptographic strength and low authentication delay and proposed a variant of CuMAC called CuMAC/S. By employing the novel idea of message speculation, CuMAC/S achieves enables the accumulation of cryptographic strength while incurring minimal delay when the message speculation accuracy is high. / Doctor of Philosophy / The privacy-preserving and message authentication issues of some network applications are distinctive from common internet security due to different attack models and possibly constrained resources, and these security and privacy concerns cannot be addressed by applying existing internet security solutions straightforwardly. For example, in a centralized dynamic spectrum access (DSA) system, the spectrum resource licensees called incumbent users (IUs), have strong operational privacy requirements for the DSA service provider called spectrum access system (SAS), and hence SAS is required to perform spectrum computation without knowing IUs' operational information. This means SAS can at most be considered as a semi-trusted party which is honest but curious, and common anonymization and end-to-end encryption cannot address this issue, and dedicated solutions are required. Another example is that in an intra-vehicle Controller Area Network (CAN), the transmitter can only embed 64 bits of message and its authentication tag into on message frame, which makes it difficult to achieve message authentication in real-time with sufficient cryptographic strength. We addressed the privacy issue of DSA systems by proposing novel schemes incorporating efficient cryptographic primitives and various privacy-preserving techniques, achieving a greatly higher efficiency or stronger privacy-preserving level. We addressed the lightweight authentication issue of resource-constrained networks by employing the novel concept of security accumulation and message speculation, achieving high cryptographic strength, low communication overhead, and probable low latency.

Master of Science / The 6 GHz spectrum band (5.925 GHz – 7.125 GHz) is an important frequency range for many industries due to its high bandwidth capabilities, low latency, and ability to support high data transfer rates. Different types of services, both fixed and mobile, are utilizing the 6 GHz frequency band at present. The incumbents of this band comprise governmental and commercial entities that depend on the 6 GHz spectrum for services like transportation and public safety. The 6 GHz spectrum has also been identified for use by various wireless communication systems, including Wi-Fi, Bluetooth, and 5G. Incumbent licensed operators need to be able to access the spectrum without significant interference to operate effectively. As more wireless communication systems are developed and deployed, the demand for spectrum continues to grow. There is a need for spectrum sharing due to the scarcity of coverage-friendly low band spectrum. Indeed, 6G is expected to use spectrum sharing to a much larger extent compared to previous generations of wireless systems. This thesis provides extensive experimentation results using a commercial FML system that can be used to understand resiliency of FML receivers to interference at 6 GHz.

This dissertation considers a deep reinforcement learning (DRL) setting under the practical challenges of real-world wireless communication systems. The non-stationary and partially observable wireless environments make the learning and the convergence of the DRL agent challenging. One way to facilitate learning in partially observable environments is to combine recurrent neural network (RNN) and DRL to capture temporal information inherent in the system, which is referred to as deep recurrent Q-network (DRQN). However, training DRQN is known to be challenging requiring a large amount of training data to achieve convergence. In many targeted wireless applications in the 5G and future 6G wireless networks, the available training data is very limited. Therefore, it is important to develop DRL strategies that are capable of capturing the temporal correlation of the dynamic environment that only requires limited training overhead. In this dissertation, we design efficient DRL frameworks by utilizing echo state network (ESN), which is a special type of RNNs where only the output weights are trained. To be specific, we first introduce the deep echo state Q-network (DEQN) by adopting ESN as the kernel of deep Q-networks. Next, we introduce federated ESN-based policy gradient (Fed-EPG) approach that enables multiple agents collaboratively learn a shared policy to achieve the system goal. We designed computationally efficient training algorithms by utilizing the special structure of ESNs, which have the advantage of learning a good policy in a short time with few training data. Theoretical analyses are conducted for DEQN and Fed-EPG approaches to show the convergence properties and to provide a guide to hyperparameter tuning. Furthermore, we evaluate the performance under the dynamic spectrum sharing (DSS) scenario, which is a key enabling technology that aims to utilize the precious spectrum resources more efficiently. Compared to a conventional spectrum management policy that usually grants a fixed spectrum band to a single system for exclusive access, DSS allows the secondary system to dynamically share the spectrum with the primary system. Our work sheds light on the real deployments of DRL techniques in next generation wireless systems. / Doctor of Philosophy / Model-free reinforcement learning (RL) algorithms such as Q-learning are widely used because it can learn the policy directly through interactions with the environment without estimating a model of the environment, which is useful when the underlying system model is complex. Q-learning performs poorly for large-scale models because the training has to updates every element in a large Q-table, which makes training difficult or even impossible. Therefore, deep reinforcement learning (DRL) exploits the powerful deep neural network to approximate the Q-table. Furthermore, a deep recurrent Q-network (DRQN) is introduced to facilitate learning in partially observable environments. However, DRQN training requires a large amount of training data and a long training time to achieve convergence, which is impractical in wireless systems with non-stationary environments and limited training data. Therefore, in this dissertation, we introduce two efficient DRL approaches: deep echo state Q-network (DEQN) and federated ESN-based policy gradient (Fed-EPG) approaches. Theoretical analyses of DEQN and Fed-EPG are conducted to provide the convergence properties and the guideline for designing hyperparameters. We evaluate and demonstrate the performance benefits of the DEQN and Fed-EPG under the dynamic spectrum sharing (DSS) scenario, which is a critical technology to efficiently utilize the precious spectrum resources in 5G and future 6G wireless networks.

Dynamic spectrum sharing (DSS) is a new paradigm for spectrum allocation that is expected to lead to more efficient spectrum usage and alleviate the spectrum-scarcity that has been perceived in recent years. DSS refers to the opportunistic, dynamic, and uncoordinated use of the spectrum by multiple, possibly non-cooperating, systems. It allows bands which may be underutilized by incumbent or legacy systems to be shared by agile or cognitive radios on a ``do no harm" basis. An ideal DSS technique is one which efficiently uses the allocated spectrum and maximizes the performance of the DSS network while causing no interference to the legacy radio system with which it coexists. We address this issue in our work by investigating desirable features for DSS with respect to the impact on a legacy radio system as well as the performance of a DSS network. It is found that ``ideal" DSS techniques with respect to both objectives are characterized by the removal of the strongest interferers in the system and averaging of the remaining interference. This motivates the use of an interference avoidance (IA) based underlay technique for DSS. The performance benefit provided by this technique, over an IA-based overlay technique, is shown to increase with the transmission bandwidth available to the DSS system. It is also shown that this technique is more robust to inaccuracies in the system knowledge required for implementing IA. An example of an IA-based underlay technique is a spreading-sequence-based transmission scheme that employs sequence adaptation to avoid interference. We use game-theoretic tools to design such schemes for distributed or ad hoc networks. The designed schemes can also be used to avoid interfering with other agile or static radios. We then extend this work to Ultra Wideband systems which can maximally exploit the gains from the proposed scheme due to the large transmission bandwidths. / Ph. D.

Cognitive Radio (CR) capitalizes advances in signal processing and radio technology and is capable of reconfiguring RF and switching to desired frequency bands. It is a frequency-agile data communication device that is vastly more powerful than existing multi-channel multi-radio (MC-MR) technology. In this thesis, we investigate the important problem of multi-hop networking with CR nodes. In a CR network, each node has a set of frequency bands (not necessarily of equal size) that may not be the same as those at other nodes. The uneven size of frequency bands prompts the need of further division into sub-bands for optimal spectrum sharing. We characterize behaviors and constraints for such multi-hop CR network from multiple layers, including modeling of spectrum sharing and sub-band division, scheduling and interference constraints, and flow routing. We give a formal mathematical formulation with the objective of maximizing the network throughput for a set of user communication sessions. Since such problem formulation falls into mixed integer non-linear programming (MINLP), which is NP-hard in general, we develop a lower bound for the objective by relaxing the integer variables and linearization. Subsequently, we develop a nearoptimal algorithm to this MINLP problem. This algorithm is based on a novel sequential fixing (SF) procedure, where the integer variables are determined iteratively via a sequence of linear program (LP). In order to implement and evaluate these algorithms in a controlled laboratory setting, we design and implement an emulation testbed. The highlights of our experimental research include: • Emulation of a multi-hop CR network with arbitrary topology; • An implementation of the proposed SF algorithm at the application layer; • A source routing implementation that can easily support comparative study between SF algorithm and other schemes; • Experiments comparing the SF algorithm with another algorithm called Layered Greedy Algorithm (LGA); • Experimental results show that the proposed SF significantly outperforms LGA. In summary, the experimental research in this thesis has demonstrated that SF algorithm is a viable algorithm for optimal spectrum sharing in multi-hop CR networks. / Master of Science