Cognitive radio networks (CRNs) are a promising solution to the channel (spectrum) congestion problem. This dissertation presents work on the two main issues in CRNs: spectrum management and cross-layer protocol design. The objective of spectrum management is to enable the efficient usage of spectrum resources in CRNs, which protects primary users' activities and ensures the effective spectrum sharing among nodes. We consider to improve the spectrum sensing efficiency and accuracy, so that the spectrum sensing cost is reduced. We consider the pre-phase of spectrum sensing and provide structures for sensing assistance. Besides the spectrum sensing phase, the sharing of spectrum, or the channel allocation, among nodes is also the main component in the spectrum management. We provide our approach to achieve a reliable and effective channel assignment. The channel availabilities for different nodes in CRNs are dynamic and inconsistent. This poses challenges on the MAC layer protocols for CRNs. Moreover, due to the lack of knowledge on primary users, they can suddenly become available during the secondary users' data transmission. Therefore, for a end-to-end data transmission in CRNs, the routing algorithm is different from the existing routing algorithms in traditional networks. We consider the cross-layer protocol design, and propose the solutions for efficient data transmission. We propose the novel routing protocol design considering the boundaries of PUs. Also, an effective structure for reliable end-to-end data transmission is presented, which makes use of the area routing protocol. We build a USRP/Gnuradio testbed for the performance evaluation of our protocols. / Computer and Information Science

Video communications play a vital role in present and future wireless ad hoc networks. One of the key requirements for a successful deployment of multimedia applications in multihop wireless networks is the ability to provide an acceptable video quality, even under a highly dynamic and perhaps unfriendly (or hostile) environment (e.g., in the presence of frequent node/link failure, interference, shadowing, fading, and so forth). Existing ad hoc routing protocols work well for data communications, but are not optimized for video, which is sensitive to latency and packet loss. Moreover, traditional end system based error control mechanisms alone cannot guarantee a sustainable video quality. Conventional QoS approaches typically optimize one or more network layer metrics, but they are usually agnostic to any kind of application layer performance. Consequently, new methodologies must be explored to improve the performance of video applications in multihop wireless networks. This dissertation directly addresses this important problem area by leveraging recent advances in video coding techniques along with novel cross-layer formulations and powerful optimization techniques. We follow an application centric cross-layer approach to address multimedia service provisioning over ad hoc networks. Our research efforts show that video communications over multihop wireless networks can substantially benefit from a cross-layer design principle by factoring in application layer video quality into routing algorithmic designs at the network layer. There are three components in this investigation, namely, (1) concurrent routing, (2) path selection and rate allocation, and (3) multipath routing for multiple description video. Each component addresses one or more unique challenges that hinder video communications in multihop wireless networks. Although we expect that a cross-layer approach will be more effective than a network centric (single-layer) approach in addressing application performance, it also brings in complex problems that cannot be effectively solved using traditional methods, and thus, calls for the design of customized algorithms. In concurrent routing, we focus on issues that arise while supporting multiple concurrent video communication sessions in an ad hoc network. These sessions compete for limited network resources (such as bandwidth) while interacting with each other. Such inter-session interactions couple the performance of an individual flow with that of other flows. Applying a video centric cross-layer design principle, we model the end-to-end video distortion as a function of network layer behavior, and formulate a network-wide optimal routing problem that minimizes the total video distortion. Results based on computational experiments performed using randomly generated network topologies establish the relative efficacy and robustness of the proposed genetic algorithm based solution approach. Specifically, we demonstrate that our approach outperforms other trajectory based metaheuristic approaches as well as with conventional network centric routing algorithms such as shortest path and disjoint shortest path routing. The joint path selection and rate allocation problem considers not only selecting the best set of paths for video communication, but also, computing the optimal video encoding rate and partitioning it among the chosen set of paths. The end-to-end video distortion is modeled as a function of network layer resources by capturing the tight coupling that exists between the optimal encoding rate for each video session, the selection of paths for video transmission, and the allocation of traffic among these selected paths. This problem is formulated as a nonlinear nonconvex programming problem, for which a tight linear programming relaxation is constructed via the Reformulation-Linearization Technique (RLT). This construct is embedded within a specialized branch-and-bound algorithm to achieve global optimality. Computational experience is reported for various problem instances, and the results validate the robustness of the proposed algorithmic procedure. The results exhibit the advantage of the solution approach over the popularly used max-min rate allocation scheme. The emergence of Multiple Description (MD) coding technique offers great potential for multipath routing of video in multihop wireless networks. In studying multipath routing for MD coding, we show that MD coded video, when used in combination with multipath routing in wireless networks, has tremendous advantages over traditional layered video coding techniques. We discuss how to implement an MD video codec and formulate a cross-layer optimization problem that can find a set of optimal paths, (one for each description) such that the overall video quality at the receiver is maximized. We further devise a specialized RLT-based branch-and-bound solution procedure for the ensuing 0-1 mixed integer nonconvex optimization problem. Convergence behavior of the proposed solution procedure is observed for various network topologies and the results further demonstrate the performance advantage of the proposed cross-layer approach over non-cross-layer approaches. The scope of this research is highly interdisciplinary. It intersects video communication, networking, optimization, and algorithm design. We expect that the theoretical and algorithmic results of this investigation will serve as important building blocks in developing a comprehensive methodology for addressing complex cross-layer problems in the area of wireless ad hoc networks. / Ph. D.

For complex computer networks with many tunable parameters and network performance objectives, the task of selecting the ideal network operating state is difficult. To improve the performance of these kinds of networks, this research proposes the idea of the cognitive network. A cognitive network is a network composed of elements that, through learning and reasoning, dynamically adapt to varying network conditions in order to optimize end-to-end performance. In a cognitive network, decisions are made to meet the requirements of the network as a whole, rather than the individual network components. We examine the cognitive network concept by first providing a definition and then outlining the difference between it and other cognitive and cross-layer technologies. From this definition, we develop a general, three-layer cognitive network framework, based loosely on the framework used for cognitive radio. In this framework, we consider the possibility of a cognitive process consisting of one or more cognitive elements, software agents that operate somewhere between autonomy and cooperation. To understand how to design a cognitive network within this framework we identify three critical design decisions that affect the performance of the cognitive network: the selfishness of the cognitive elements, their degree of ignorance, and the amount of control they have over the network. To evaluate the impact of these decisions, we created a metric called the price of a feature, defined as the ratio of the network performance with a certain design decision to the performance without the feature. To further aid in the design of cognitive networks, we identify classes of cognitive networks that are structurally similar to one another. We examined two of these classes: the potential class and the quasi-concave class. Both classes of networks will converge to Nash Equilibrium under selfish behavior and in the quasi-concave class this equilibrium is both Pareto and globally optimal. Furthermore, we found the quasi-concave class has other desirable properties, reacting well to the absence of certain kinds of information and degrading gracefully under reduced network control. In addition to these analytical, high level contributions, we develop cognitive networks for two open problems in resource management for self-organizing networks, validating and illustrating the cognitive network approach. For the first problem, a cognitive network is shown to increase the lifetime of a wireless multicast route by up to 125\%. For this problem, we show that the price of selfishness and control are more significant than the price of ignorance. For the second problem, a cognitive network minimizes the transmission power and spectral impact of a wireless network topology under static and dynamic conditions. The cognitive network, utilizing a distributed, selfish approach, minimizes the maximum power in the topology and reduces (on average) the channel usage to within 12\% of the minimum channel assignment. For this problem, we investigate the price of ignorance under dynamic networks and the cost of maintaining knowledge in the network. Today's computer networking technology will not be able to solve the complex problems that arise from increasingly bandwidth-intensive applications competing for scarce resources. Cognitive networks have the potential to change this trend by adding intelligence to the network. This work introduces the concept and provides a foundation for future investigation and implementation. / Ph. D.

Wireless ad-hoc networks are easily deployed, untethered to infrastructure, and have virtually an unlimited number of applications. However, this flexibility comes at the cost of finite and often unreplenishable power supplies. Once a node has consumed all of its power, it can no longer receive, transmit, gather information, or otherwise participate in the network. Therefore, reducing the amount of energy necessary for node communication has been an area of intense research. Previous work has investigated the use of directional antennas as a method to reduce inter-node power requirements. However, most proposed methods ignore inter-session interference, propose heuristic solution methods, and ignore the use of directional antennas for signal reception. We develop a flexible mixed-integer linear program (MILP) designed to optimize max-min multicast path lifetime for directional antenna equipped networks in the presence of interference. The MILP is utilized to perform a comparison directional antenna use for signal transmission and reception. Results indicate that directional reception is slightly superior to transmission for the defined max-min lifetime metric, and vastly superior when considering cumulative power use. We further analyze the performance of interference-ignorant link-based heuristics designed for both directional transmission and directional reception as they perform in our more realistic model. Our results show that interference-ignorant methods cannot find feasible solutions unless all nodes are equipped with high gain, high efficiency directional antennas. Even in these cases, directional reception outperforms directional transmission. Because of the superiority of directional reception, we focus our attention on this method. A heterogeneity study is performed, and two heuristic methods for approximating the MILP optima are developed. We find that even under heterogeneous conditions, directional reception can increase network lifetime. Finally, a genetic algorithm (GA) and semi-distributed heuristic method are developed as alternatives to the MILP. Results show that the GA often can find solutions with lifetimes 85% as long as the optimal. Our semi-distributed heuristic, designed to be even more computationally simple than the GA, and to serve as a basis for a distributed protocol, is almost as effective as the GA as approximating optimal solutions. We conclude that directional reception is the superior method of antenna use for extending max-min multicast tree lifetime, that it works well in heterogeneous conditions, and lends itself well to heuristic design. / Ph. D.

Recent advancements in frequency-agile radio technology and dynamic spectrum access network have created a huge space for improving the utilization efficiency of wireless spectrum. Existing algorithms and protocols, however, have not taken full advantage of the new technologies due to obsolete network design ideologies inherited from conventional network design, such as static spectrum access and static channelization. In this dissertation, we propose new resource management models and algorithms that capitalize on the frequency-agility of next generation radios and the dynamic spectrum access concepts to increase the utilization efficiency of wireless spectrum. We first propose a new analytical model for Dynamic Spectrum Access (DSA) networks. Compared to previous models, the new model is able to include essential DSA mechanisms such as spectrum sensing and primary interference avoidance into solid mathematical representation and thus drastically increase the accuracy of our model. The subsequent numerical study conforms well with existing empirical studies and provides fundamental insights on the design of future DSA networks. We then take advantage of partially overlapped channel in frequency-agile radio networks and propose simple joint channel scheduling and flow routing optimization algorithm that maximizes network throughput. The model quantifies the impact of fundamental network settings, such as node density and traffic load, on the performance of partially overlapped channel based networks. We then propose a cross-layer radio resource allocation algorithm JSSRC (Joint Spectrum Sharing and end-to-end data Rate Control) that iteratively adapts a frequency-agile radio network to optimum with regard to aggregate network spectrum utilization. Subsequently, we extend JSSRC to include routing and present TRSS (joint Transport, Routing and Spectrum Sharing) to solve the much more complex joint transport, routing and spectrum sharing optimization problem. Both JSSRC and TRSS enjoy theoretical convergence and achieve optimum with appropriate scheduling algorithms. The works together strive to improve efficiency of spectrum utilization in frequency-agile radio networks. Numerical and simulation studies show the effectiveness of our designs to reduce the so-called spectrum shortage problem. / Ph. D.

Over the last decade, the wide deployment of wireless access technologies (e.g. WiFi, 3G, and LTE) and the remarkable growth in the volume of streaming video content have significantly altered the telecommunications field. These developments introduce new challenges to the research community including the need to develop new solutions (e.g. traffic models and transport protocols) to address changing traffic patterns and the characteristics of wireless links and the need for new evaluation methods that generate higher fidelity results under more realistic scenarios. Unfortunately, for the last two decades, simulation studies have been the main tool for researchers in wireless networks. In spite of the advantages of simulation studies, overall they have had a negative influence on the credibility of published results. In partial response to this simulation crisis, the research community has adopted testing and evaluation using implementation-based experiments. Implementation-based experiments include field experiments, prototypes, emulations, and testbeds. An example of an implementation-based experiment is the MANIAC Challenge, a wireless networking competition that we designed and hosted, which included creation and operation of ad hoc networks using commodity hardware. However, the lack of software tools to facilitate these sorts of experiments has created new challenges. Currently, researchers must practice kernel programming in order to implement networking experiments, and there is an urgent need to lower the barriers of entry to wireless network experimentation. With respect to the growth in video traffic over wireless networks, the main challenge is a mismatch between the design concepts of current internet protocols (e.g. the Transport Control Protocol (TCP)) and the reality of modern wireless networks and streaming video techniques. Internet protocols were designed to be deployed over wired networks and often perform poorly over wireless links; video encoding is highly loss tolerant and delay-constrained and yet, for reasons of expedience is carried using protocols that emphasize reliable delivery at the cost of potentially high delay. This dissertation addresses the lack of software tools to support implementation-based networking experiments and the need to improve the performance of video streaming over wireless access networks. We propose a new software tool that allows researchers to implement experiments without a need to become kernel programmers. The new tool, called the Flexible Internetwork Stack (FINS) Framework, is available under an open source license. With our tool, researchers can implement new network layers, protocols, and algorithms, and redesign the interconnections between the protocols. It offers logging and monitoring capabilities as well as dynamic reconfigurability of the modules' attributes and interconnections during runtime. We present details regarding the architecture, design, and implementation of the FINS Framework and provide an assessment of the framework including both qualitative and quantitative comparison with significant previous tools. We also address the problem of HTTP-based adaptive video streaming (HAVS) over WiFi access networks. We focus on the negative influence of wireless last-hop connections on network utilization and the end-user quality of experience (QoE). We use a cross-layer approach to design three controllers. The first and second controllers adopt a heuristic cross-layer design, while the third controller formulates the HAVS problem as a Markov decision process (MDP). By solving the model using reinforcement learning, we achieved 20% performance improvement (after enough training) with respect to the performance of the best heuristic controller under unstable channel conditions. Our simulation results are backed by a system prototype using the FINS Framework. Although it may seem predictable to achieve more gain in performance and in QoE by using cross-layer design, this dissertation not only presents a new technique that improves performance, but also suggests that it is time to move cross-layer and machine-learning-based approaches from the research field to actual deployment. It is time to move cognitive network techniques from the simulation environment to real world implementations. / Ph. D.

Spatial diversity, in the form of employing multiple antennas (i.e., MIMO), has proved to be very effective in increasing network capacity and reliability. However, equipping a wireless node with multiple antennas may not be practical, as the footprint of multiple antennas may not fit on a wireless node (particularly on handheld wireless devices). In order to achieve spatial diversity without requiring multiple antennas on the same node, the so-called cooperative communications (CC) has been introduced. Under CC, each node is equipped with only a single antenna and spatial diversity is achieved by exploiting the antennas on other nodes in the network through cooperative relaying. The goal of this dissertation is to maximize throughput at network level through CC at the physical layer. A number of problems are explored in this investigation. The main contributions of this dissertation can be summarized as follows. <b>1. Optimal Relay Assignment.</b> We first consider a simple CC model where each source-destination pair may employ only a single relay. For this three-node model, the choice of a relay node (among a set of available relay nodes) for a given session is critical in the overall network performance. We study the relay node assignment problem in a cooperative ad hoc network environment, where multiple source-destination pairs compete for the same pool of relay nodes in the network. Our objective is to assign the available relay nodes to different source-destination pairs so as to maximize the minimum data rate among all pairs. We present an optimal polynomial time algorithm, called ORA, that solves this problem. A novel idea in this algorithm is a "linear marking" mechanism, which maintains linear complexity at each iteration. We offer a formal proof of optimality for ORA and use numerical results to demonstrate its capability. <b>2. Incorporating Network Coding.</b> It has been shown that network coding (NC) can reduce the time-slot overhead when multiple session share the same relay node in CC. Such an approach is called network-coded CC (or NC-CC). Most of the existing works have mainly focused on the benefits of this approach. The potential adverse effect under NC-CC remains unknown. We explore this important problem by introducing the concept of network coding noise (NC noise). We show that due to NC noise, NC may not be always beneficial to CC. We substantiate this important finding in two important scenarios: analog network coding (ANC) in amplify-and-forward (AF) CC, and digital network coding (DNC) in decode-and-forward (DF) CC. We analyze the origin of NC noise via a careful study of signal aggregation at a relay node and signal extraction at a destination node. We derive a closed-form expression for NC noise at each destination node and show that the existence of NC noise could diminish the advantage of NC in CC. Our results shed new light on how to use NC in CC effectively. <b>3. Session Grouping and Relay Node Selection.</b> When there are multiple sessions in the network, it may be necessary to combine sessions into different groups, and then have each group select the most beneficial relay node for NC-CC. We study this joint grouping and relay node selection problem for NC-CC. By studying matching problems in hypergraphs, we show that this problem is NP-hard. We then propose a distributed and online algorithm to solve this problem. The key idea in our algorithm is to have each neighboring relay node of a newly joined session determine and offer the best group for this session from the groups that it is currently serving; and then to have the source node of this newly joined session select the best group among all received offers. We show that our distributed algorithm has polynomial complexity. Using extensive numerical results, we show that our distributed algorithm is near-optimal and adapts well to online network dynamics. <b>4. Grouping and Matching for Multi-Relay Cooperation.</b> Existing models of NC-CC consider only single relay node for each session group. We investigate how NC-CC behaves when multiple relay nodes are employed. For a given session, we develop closed form formulas for the mutual information and achievable rate under multi-relay NC-CC. In multi-relay NC-CC, the achievable rate of a session depends on the other sessions in its group as well as the set of relay nodes used for NC-CC. Therefore, we study NC-CC via joint optimization of grouping and matching of session and relay groups in an ad hoc network. Although we show that the joint problem is NP-hard, we develop an efficient polynomial time algorithm for grouping and matching (called G²M). G²M first builds beneficial relay groups for individual sessions. This is followed by multiple iterations during which sessions are combined with other sessions to form larger and better session groups (while corresponding relay groups are merged and updated accordingly). Using extensive numerical results, we show the efficiency and near optimality of our G²M algorithm. / Ph. D.

Quality-of-Service (QoS) to users is a critical requirement of resource allocation in wireless networks and has drawn significant research attention over a long time. However, the QoS requirements differ vastly based on the wireless network paradigm. At one extreme, we have a millimeter wave small-cell network for streaming data that requires very high throughput and low latency. At the other end, we have Machine-to-Machine (M2M) uplink traffic with low throughput and low latency. In this dissertation, we investigate and solve QoS-aware resource allocation problems for diverse wireless paradigms. We first study cross-layer dynamic spectrum allocation in a LTE macro-cellular network with fractional frequency reuse to improve the spectral efficiency for cell-edge users. We show that the resultant optimization problem is NP-hard and propose a low-complexity layered spectrum allocation heuristic that strikes a balance between rate maximization and fairness of allocation. Next, we develop an energy efficient downlink power control scheme in a energy harvesting small-cell base station equipped with local cache and wireless backhaul. We also study the tradeoff between the cache size and the energy harvesting capabilities. We next analyzed the file read latency in Distributed Storage Systems (DSS). We propose a heterogeneous DSS model wherein the stored data is categorized into multiple classes based on arrival rate of read requests, fault-tolerance for storage etc. Using a queuing theoretic approach, we establish bounds on the average read latency for different scheduling policies. We also show that erasure coding in DSS serves the dual purpose of reducing read latency and increasing the energy efficiency. Lastly, we investigate the problem of delay-efficient packet scheduling in M2M uplink with heterogeneous traffic characteristics. We classify the uplink traffic into multiple classes and propose a proportionally-fair delay-efficient heuristic packet scheduler. Using a queuing theoretic approach, we next develop a delay optimal multiclass packet scheduler and later extend it to joint medium access control and packet scheduling for M2M uplink. Using extensive simulations, we show that the proposed schedulers perform better than state-of-the-art schedulers in terms of average delay and packet delay jitter. / PHD

In recent years, Software Defined and Cognitive Radios (SDRs and CRs) have become popular topics of research. Game theory has proven to be a useful set of tools for analyzing wireless networks, including Cognitive Networks (CNs). This thesis provides a game theoretic cross-layer mechanism that can be used to control SDRs and CRs. We have constructed an upper-layer Topology Control (TC) game, which decides which links each node uses. A TDMA algorithm which we have adapted is then run on these links. The links and the TDMA schedule are then passed to a lower-layer game, the Link Adaptation Game (LAG), where nodes adjust their transmit power and their link parameters, which in this case are modulation scheme and channel coding rate. It is shown that both the TC game and the LAG converge to a Nash Equilibrium (NE). It is also shown that the solution for the TC game approximates the topology that results from maximizing the utility function when appropriate link costs are used. Also seen is the increase in throughput provided by the LAG when compared to the results of Greedy Rate Packing (GRP). / Master of Science

Escalating demands for high performance wireless systems requires the confluence of smart communication methods, network protocols and ongoing advances in fabrication technologies, in order to bring smaller form factor mobile handsets to market. On par with these trends, this thesis focuses on two main areas, namely, Multiple Antenna Systems and Adaptive MAC Design to improve wireless system performance. The first part of this research work presents a mathematical framework for characterizing the performance of cellular mobile radio systems equipped with smart antennas at the mobile handset to suppress a few dominant cochannel interferers (CCI) out of a total of L active independent but non-identically distributed Rayleigh faded CCI signals. Earlier works on this subject chose an unrealistic i.i.d assumption for the cochannel interferers. Since the CCI signals are of dissimilar signal strengths in practical operating environments, the premise of i.n.d fading statistics for the cochannel interferers is more realistic. In the subsequent section an analytical framework to investigate the benefits of a hybrid antenna array using selective interference nulling (SIN) and maximal ratio combining (MRC) in mobile radio environments is developed. In the second part of this thesis, we explore the performance gains that can be achieved by exploiting the synergy resulting from the combination of the MAC and the physical layer of a wireless network. As in a traditional design, the physical layer is responsible for providing error protection for the transmission packets while the MAC layer allocates transmission bandwidth to the contending users. However, in the proposed scheme the MAC layer makes slot assignment decisions based on the channel state information (CSI) from the physical layer. / Master of Science