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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

Mathematical optimization techniques for resource allocation and spatial multiplexing in spectrum sharing networks

Tang, Jie January 2013 (has links)
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.
2

Channel Access Mechanisms and Protocols for Opportunistic Cognitive Radio Networks

Bany Salameh, Haythem Ahmad Mohammed January 2009 (has links)
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.
3

Uplink Multiuser Scheduling Techniques for Spectrum Sharing Systems

Qaraqe, Marwa 2012 August 1900 (has links)
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.
4

Performance Analysis of Cognitive Radio Networks under Spectrum Sharing and Security Constraints

Sibomana, Louis January 2016 (has links)
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.
5

Design and Implementation of An Emulation Testbed for Optimal Spectrum Sharing in Multi-hop Cognitive Radio Networks

Liu, Tong 14 August 2007 (has links)
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
6

Security and Performance Issues in Spectrum Sharing between Disparate Wireless Networks

Vaka, Pradeep Reddy 08 June 2017 (has links)
The United States Federal Communications Commission (FCC) in its recent report and order has prescribed the creation of Citizens Broadband Radio Service (CRBS) in the 3.5 GHz band to enable sharing between wireless broadband devices and incumbent radar systems. This sharing will be enabled by use of geolocation database with supporting infrastructure termed as Spectrum Access System (SAS). Although using SAS for spectrum sharing has many pragmatic advantages, it also raises potentially serious operational security (OPSEC) issues. In this thesis, we explore OPSEC, location privacy in particular, of incumbent radars in the 3.5 GHz band. First, we show that adversarial secondary users can easily infer the locations of incumbent radars by making seemingly innocuous queries to the database. Then, we propose several obfuscation techniques that can be implemented by the SAS for countering such inference attacks. We also investigate obfuscation techniques' efficacy in minimizing spectral efficiency loss while preserving incumbent privacy. Recently, the 3GPP Rel.13 has specified a new standard to provide wide-area connectivity for IoT, termed as Narrowband IoT (NB-IoT). NB-IoT achieves excellent coexistence with legacy mobile standards, and can be deployed in any of the 2G/3G/4G spectrum (450 MHz to 3.5 GHz). Recent industry efforts show deployment of IoT networks in unlicensed spectrum, including shared bands (e.g., 3.5 GHz band). However, operating NB-IoT systems in the 3.5 GHz band can result in significant BLER and coverage loss. In this thesis, we analyse results from extensive experimental studies on the coexistence of NB-IoT and radar systems, and demonstrate the coverage loss of NB-IoT in shared spectrum. / Master of Science
7

Learning Schemes for Adaptive Spectrum Sharing Radar

Thornton, Charles E. III 08 June 2020 (has links)
Society's newfound dependence on wireless transmission systems has driven demand for access to the electromagnetic (EM) spectrum to an all-time high. In particular, wireless applications related to the fifth generation (5G) of cellular technology along with statically allocated radar systems have contributed to the increasing scarcity of the sub 6 GHz frequency bands. As a result, development of Dynamic Spectrum Access (DSA) techniques for sharing these frequencies has become a critical research area for the greater wireless community. Since among incumbent systems, radars are the largest consumers of spectrum in the sub 6 GHz regime, and are being used increasingly for civilian applications such as traffic control, adaptive cruise control, and collision avoidance, the need for radars which can adaptively tune specific transmission parameters in an intelligent manner to promote coexistence with other systems has arisen. Thus, fully-aware, dynamic, cognitive radar has been proposed as target for radars to evolve towards. In this thesis, we extend current research thrusts towards cognitive radar to utilize Reinforcement Learning (RL) techniques which allow a radar system to learn desired behavior using information obtained from past transmissions. Since radar systems inherently interact with their electromagnetic environment, it is natural to view the use of reinforcement learning techniques as a straightforward extension to previous adaptive techniques. However, in designing learning algorithms for radar systems, we must carefully define goal-driven rewards, formalize the learning process, and consider an appropriate amount of environmental information. In this thesis, we apply well-established and emerging reinforcement learning approaches to meet the demands of modern radar coexistence problems. In particular, function estimation using deep neural networks is examined, as Deep RL presents a scalable learning framework which allows many environmental states to be considered in the decision-making process. We then show how these techniques can be used to improve traditional radar performance metrics, such as interference avoidance, spectral efficiency, and target detectibility with simulated and experimental results. We also compare the learning techniques to each other and naive approaches, such as fixed bandwidth radar and avoiding interference reactively. Finally, online learning strategies are considered which aim to balance the fundamental learning trade-off between exploration and exploitation. We show that online learning techniques can be used to select individual waveforms or applied as a high-level controller in a hierarchical learning scheme based on the biologically inspired concept of metacognition. The general use of RL techniques provides a robust framework for decision making under uncertainty that is more flexible than previously proposed cognitive radar strategies. Further, the wide array of RL models and algorithms allow the underlying structure to be applied to both small and large-scale radar scenarios. / Master of Science / Society's newfound dependence on wireless transmission systems has driven demand for control of the electromagnetic (EM) spectrum to an all-time high. In particular, federal spectrum auctions and the fifth generation of wireless technologies have contributed to the scarcity of frequency bands below 6GHz. These frequencies are widely used by both radar and communications systems due to favorable propagation characteristics. However, current radar systems typically occupy a fixed bandwidth and are tend to be poorly equipped to share their allocated spectrum with other users, which has become a necessity given the growth of wireless traffic. In this thesis, we study learning algorithms which enable a radar to optimize its electromagnetic pulses based on feedback from received signals. In particular, we are interested in reinforcement learning algorithms which allow a radar to learn optimal behavior based on rewards defined by a human. Using these algorithms, radar system designers can choose which metrics may be most important for a given radar application which can then be optimized for the given setting. However, scaling reinforcement learning to real-world problems such as radar optimization is often difficult due to the massive scope of the problem. Here we attempt to identify potential issues with implementation of each algorithm and narrow in on algorithms that are well-suited for real-time radar operation.
8

Privacy and Authentication in Emerging Network Applications

Li, He 07 January 2021 (has links)
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.
9

Interference Avoidance based Underlay Techniques for Dynamic Spectrum Sharing

Menon, Rekha 09 May 2007 (has links)
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.
10

Fundamentals of Efficient Spectrum Access and Co-existence with Receiver Nonlinearity

Padaki, Aditya V. 29 January 2018 (has links)
RF front-ends are nonlinear systems that have nonlinear frequency response and, hence, can impair receiver performance by harmful adjacent channel interference in non-intuitive ways. Next generation wireless networks will see unprecedented diversity across receiver and radio technologies accessing the same band of spectrum in spatio-temporal proximity. Ensuring adjacent channel co-existence is of prime importance for successful deployment and operations of next generation wireless networks. Vulnerabilities of receiver front-end can have a severe detrimental effect on network performance and spectrum co-existence. This dissertation addresses the technological challenges in understanding and accounting for receiver sensitivities in the design of next generation wireless networks. The dissertation has four major contributions. In the first contribution, we seek to understand how receiver nonlinearity impacts performance. We propose a computationally efficient framework to evaluate the adjacent channel interference in a given radio/spectrum environment. We develop novel tractable representation of receiver front-end nonlinearity to specify the adjacent channel signals that contribute to the interference at the desired channel and the total adjacent channel interference power at a given desired channel. In the second contribution, we seek to understand how the impact of receiver nonlinearity performance can be quantified. We quantify receiver performance in the presence of adjacent channel interference using information theoretic metrics. We evaluate the limits on achievable rate accounting for RF front-end nonlinearity and provide a framework to compare disparate receivers by forming generalized metrics. In the third contribution, we seek to understand how the impact of receiver nonlinearity can be managed at the network level. We develop novel and comprehensive wireless network management frameworks that account for the RF nonlinearity, impairments, and diversity of heterogeneous wireless devices. We further develop computationally efficient algorithms to optimize the proposed framework and examine network level performance. We demonstrate through extensive network simulations that the proposed receiver-centric frameworks provide substantially high spectrum efficiency gains over receiver-agnostic spectrum access in dense and diverse next generation wireless networks. In the fourth contribution, we seek to understand how scalable interference networks are with receiver nonlinearity. We propose practical achievable schemes for interference avoidance and assess the scalability of the next generation wireless networks with interference due to receiver nonlinearity. Further, we develop an algorithmic scheme to evaluate the upper bound on scalability of nonlinear interference networks. This provides valuable insights on scalability and schemes for nonlinear adjacent channel interference avoidance in next generation shared spectrum networks. / Ph. D.

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