Theses and Dissertations from UMD
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New submissions to the thesis/dissertation collections are added automatically as they are received from the Graduate School. Currently, the Graduate School deposits all theses and dissertations from a given semester after the official graduation date. This means that there may be up to a 4 month delay in the appearance of a give thesis/dissertation in DRUM
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Item Utilization of Channel State Information in Transmission Control for Wireless Communication Networks(2013) Hany, Mohamed Tawfeek Kashef; Ephremides, Anthony; Electrical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)This dissertation deals with the utilization of channel knowledge in improving the performance of wireless communication systems. The first part is about energy harvesting networks. The transmission policies in energy harvesting wireless systems need to adapt to the harvested energy availability and the channel characteristics. We start by considering the scheduling policy for a single energy harvesting source node that operates over a time varying channel. The goal of the source is to maximize the average number of successfully delivered packets per time slot. The transmission decisions depend on the available channel information and the length of the energy queue. Then, we investigate the case in which the source is helped by a relay through a network-level cooperation protocol. We investigate the case of a single relay node in which we optimize the transmission control based on channel measurements. Then, we assess the benefits of using partial relaying. We provide an exact characterization of the stability region of a network which consists of a source, a relay and a destination with random data arrivals to both the source and the relay. We derive the optimal value of the relaying parameter to maximize the stable throughput of the source for a given data arrival rate to the relay. Finally, we introduce the problem of general relaying cost minimization for cooperative energy harvesting networks with multiple relays. Then, we introduce the energy consumption as a cost criterion for the optimization problem to find an energy-efficient partial relaying protocol. In the second part, we investigate the techniques to optimally exploit channel information in transmission control for interfering sources. We discuss the scheduling problem for different levels of channel knowledge because learning instantaneous channels states may be costly or infeasible. We consider a network that consists of two transmitter-receiver pairs which operate over time varying channels. We derive the optimal scheduling policies which maximize the expected weighted sum-rate of the network per time slot. The decision depends on the information about the channels between nodes. In the third part, we investigate the effect of channel estimation on the performance of a secondary network in a cognitive radio system. We focus on estimating the sensing-channel from the primary source to the secondary source which helps in assessing the reliability of the sensing decision. The channel is estimated opportunistically when the secondary source senses the primary source to be active. We consider the performance criterion to be the energy consumed by the secondary system constrained by a required average data transmission rate for the secondary system and an allowable average failure probability for the primary system.Item COOPERATIVE NETWORKING AND RELATED ISSUES: STABILITY, ENERGY HARVESTING, AND NEIGHBOR DISCOVERY(2013) Jeon, Jeongho; Ephremides, Anthony; Electrical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)This dissertation deals with various newly emerging topics in the context of cooperative networking. The first part is about the cognitive radio. To guarantee the performance of high priority users, it is important to know the activity of the high priority communication system but the knowledge is usually imperfect due to randomness in the observed signal. In such a context, the stability property of cognitive radio systems in the presence of sensing errors is studied. General guidelines on controlling the operating point of the sensing device over its receiver operating characteristics are also given. We then consider the hybrid of different modes of operation for cognitive radio systems with time-varying connectivity. The random connectivity gives additional chances that can be utilized by the low priority communication system. The second part of this dissertation is about the random access. We are specifically interested in the scenario when the nodes are harvesting energy from the environment. For such a system, we accurately assess the effect of limited, but renewable, energy availability on the stability region. The effect of finite capacity batteries is also studied. We next consider the exploitation of diversity amongst users under random access framework. That is, each user adapts its transmission probability based on the local channel state information in a decentralized manner. The impact of imperfect channel state information on the stability region is investigated. Furthermore, it is compared to the class of stationary scheduling policies that make centralized decisions based on the channel state feedback. The backpressure policy for cross-layer control of wireless multi-hop networks is known to be throughput-optimal for i.i.d. arrivals. The third part of this dissertation is about the backpressure-based control for networks with time-correlated arrivals that may exhibit long-range dependency. It is shown that the original backpressure policy is still throughput-optimal but with increased average network delay. The case when the arrival rate vector is possibly outside the stability region is also studied by augmenting the backpressure policy with the flow control mechanism. Lastly, the problem of neighbor discovery in a wireless sensor network is dealt. We first introduce the realistic effect of physical layer considerations in the evaluation of the performance of logical discovery algorithms by incorporating physical layer parameters. Secondly, given the lack of knowledge of the number of neighbors along with the lack of knowledge of the individual signal parameters, we adopt the viewpoint of random set theory to the problem of detecting the transmitting neighbors. Random set theory is a generalization of standard probability theory by assigning sets, rather than values, to random outcomes and it has been applied to multi-user detection problem when the set of transmitters are unknown and dynamically changing.Item Spectrum Sensing Security in Cognitive Radio Networks(2010) Khawar, Awais; Clancy, Thomas Charles; Electrical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)This thesis explores the use of unsupervised machine learning for spectrum sensing in cognitive radio (CR) networks from a security perspective. CR is an enabling technology for dynamic spectrum access (DSA) because of a CR's ability to reconfigure itself in a smart way. CR can adapt and use unoccupied spectrum with the help of spectrum sensing and DSA. DSA is an efficient way to dynamically allocate white spaces (unutilized spectrum) to other CR users in order to tackle the spectrum scarcity problem and improve spectral efficiency. So far various techniques have been developed to efficiently detect and classify signals in a DSA environment. Neural network techniques, especially those using unsupervised learning have some key advantages over other methods mainly because of the fact that minimal preconfiguration is required to sense the spectrum. However, recent results have shown some possible security vulnerabilities, which can be exploited by adversarial users to gain unrestricted access to spectrum by fooling signal classifiers. It is very important to address these new classes of security threats and challenges in order to make CR a long-term commercially viable concept. This thesis identifies some key security vulnerabilities when unsupervised machine learning is used for spectrum sensing and also proposes mitigation techniques to counter the security threats. The simulation work demonstrates the ability of malicious user to manipulate signals in such a way to confuse signal classifier. The signal classifier is forced by the malicious user to draw incorrect decision boundaries by presenting signal features which are akin to a primary user. Hence, a malicious user is able to classify itself as a primary user and thus gains unrivaled access to the spectrum. First, performance of various classification algorithms are evaluated. K-means and weighted classification algorithms are selected because of their robustness against proposed attacks as compared to other classification algorithm. Second, connection attack, point cluster attack, and random noise attack are shown to have an adverse effect on classification algorithms. In the end, some mitigation techniques are proposed to counter the effect of these attacks.Item Cognitive Multiple Access for Cooperative Communications and Networking(2009) El Sherif, Amr; Liu, K. J. Ray; Electrical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)In cooperative communications different network nodes share their antennas and resources to form a virtual antenna array and improve their performance through spatial diversity. This thesis contributes to the advancement of cooperative communications by developing and analyzing new multiple access cooperation protocols that leverage the benefits of cooperation to upper network layers. For speech communications networks, we propose a cooperative multiple access protocol that exploits inherent characteristics of speech signals, namely, long periods of silence, to enable cooperation without incurring bandwidth efficiency losses. Using analytical and simulation results we show that the proposed protocol achieves significant increase in network throughput, reduction in delay, and improved perceptual speech quality. In TDMA networks, we investigate the problem of sharing idle time slots between a group of cooperative cognitive relays helping primary users, and a group of cognitive secondary users. Analytical results reveal that, despite the apparent competition between relays and secondary users, and even in case of mutual interference between the two groups, both primary and secondary users will significantly benefit in terms of maximum stable throughput from the presence of relays. For random access networks, we find a solution to the problem of achieving cooperation gains without suffering from increased collision probability due to relay transmissions. A novel cooperation protocol is developed and analyzed for that purpose. Analytical and simulation results reveal significant improvements in terms of throughput and delay performance of the network. Moreover, collision probability is decreased. Finally, in the framework of a cognitive radio network, we study the negative effects of spectrum sensing errors on the performance of both primary and secondary networks. To alleviate those negative effects, we propose a novel joint design of the spectrum sensing and channel access mechanisms. Results show significant performance improvement in the maximum stable throughput region of both networks.