Browsing by Subject "wireless networks"
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Item A Study Of Aperiodic (Random) Arrays of Various Geometries(2012-07-16) Buchanan, Kristopher RyanThe use of wireless communication techniques and network centric topologies for portable communication networks and platforms makes it important to investigate new distributed beamforming techniques. Platforms such as micro air vehicles (MAVs), unattended ground sensors (UGSs), and unpiloted aerial vehicles (UAVs) can all benefit from advances in this area by enabling advantages in stealth, enhanced survivability, and maximum maneuverability. Collaborative beamforming is an example of a new technique to utilize these systems which uses a randomly distributed antenna array with a fitting phase coefficient for the elements. In this example, the radiated signal power of each element is coherently added in the far-field region of a specified target direction with net destructive interference occurring in all other regions to suppress sidelobe behavior. A wide variety of topologies can be used to confine geometrically these mobile random arrays for analysis. The distribution function for these topologies must be able to generalize the randomness within the geometry. Gaussian and Uniform distributions are investigated in this analysis, since they provide a way to calculate the statistically averaged beampattern for linear, planar (square and circular), and volumetric (cubical, cylindrical, and spherical) geometries. They are also of practical interest since the impact of array topology on the beampattern can typically be described in closed form. A rigorous analysis is presented first for disc-shaped topologies to motivate the discussion on random array properties and provide several new insights into their behavior. The analyses of volumetric geometries which are of interest to this work are drawn from this planar topology to provide a tractable and coherent discussion on the properties of more complex geometries. This analysis considers Normal and Gaussian distributed array element populations to derive the average beampattern, sidelobe behavior, beamwidth, and directivity. The beampattern is also examined in a similar manor for circular and spherical arrays with a truncated Gaussian distribution. A summary of the random array analysis and its results concludes this thesis.Item Adaptive Resource Allocation for Statistical QoS Provisioning in Mobile Wireless Communications and Networks(2012-02-14) Du, QingheDue to the highly-varying wireless channels over time, frequency, and space domains, statistical QoS provisioning, instead of deterministic QoS guarantees, has become a recognized feature in the next-generation wireless networks. In this dissertation, we study the adaptive wireless resource allocation problems for statistical QoS provisioning, such as guaranteeing the specified delay-bound violation probability, upper-bounding the average loss-rate, optimizing the average goodput/throughput, etc., in several typical types of mobile wireless networks. In the first part of this dissertation, we study the statistical QoS provisioning for mobile multicast through the adaptive resource allocations, where different multicast receivers attempt to receive the common messages from a single base-station sender over broadcast fading channels. Because of the heterogeneous fading across different multicast receivers, both instantaneously and statistically, how to design the efficient adaptive rate control and resource allocation for wireless multicast is a widely cited open problem. We first study the time-sharing based goodput-optimization problem for non-realtime multicast services. Then, to more comprehensively characterize the QoS provisioning problems for mobile multicast with diverse QoS requirements, we further integrate the statistical delay-QoS control techniques ? effective capacity theory, statistical loss-rate control, and information theory to propose a QoS-driven optimization framework. Applying this framework and solving for the corresponding optimization problem, we identify the optimal tradeoff among statistical delay-QoS requirements, sustainable traffic load, and the average loss rate through the adaptive resource allocations and queue management. Furthermore, we study the adaptive resource allocation problems for multi-layer video multicast to satisfy diverse statistical delay and loss QoS requirements over different video layers. In addition, we derive the efficient adaptive erasure-correction coding scheme for the packet-level multicast, where the erasure-correction code is dynamically constructed based on multicast receivers? packet-loss statuses, to achieve high error-control efficiency in mobile multicast networks. In the second part of this dissertation, we design the adaptive resource allocation schemes for QoS provisioning in unicast based wireless networks, with emphasis on statistical delay-QoS guarantees. First, we develop the QoS-driven time-slot and power allocation schemes for multi-user downlink transmissions (with independent messages) in cellular networks to maximize the delay-QoS-constrained sum system throughput. Second, we propose the delay-QoS-aware base-station selection schemes in distributed multiple-input-multiple-output systems. Third, we study the queueaware spectrum sensing in cognitive radio networks for statistical delay-QoS provisioning. Analyses and simulations are presented to show the advantages of our proposed schemes and the impact of delay-QoS requirements on adaptive resource allocations in various environments.Item Capacity and scale-free dynamics of evolving wireless networks(Texas A&M University, 2005-02-17) Iyer, Bharat VishwanathanMany large-scale random graphs (e.g., the Internet) exhibit complex topology, nonhomogeneous spatial node distribution, and preferential attachment of new nodes. Current topology models for ad-hoc networks mostly consider a uniform spatial distribution of nodes and do not capture the dynamics of evolving, real-world graphs, in which nodes "gravitate" toward popular locations and self-organize into non-uniform clusters. In this thesis, we first investigate two constraints on scalability of ad-hoc networks ? network reliability and node capacity. Unlike other studies, we analyze network resilience to node and link failure with an emphasis on the growth (i.e., evolution) dynamics of the entire system. Along the way, we also study important graph-theoretic properties of ad-hoc networks (including the clustering coefficient and the expected path length) and strengthen our generic understanding of these systems. Finally, recognizing that under existing uniform models future ad-hoc networks cannot scale beyond trivial sizes, we argue that ad-hoc networks should be modeled from an evolution standpoint, which takes into account the well-known "clustering" phenomena observed in all real-world graphs. This model is likely to describe how future ad-hoc networks will self-organize since it is well documented that information content distribution among end-users (as well as among spatial locations) is non-uniform (often heavy-tailed). Results show that node capacity in the proposed evolution model scales to larger network sizes than in traditional approaches, which suggest that non-uniformly clustered, self-organizing, very large-scale ad-hoc networks may become feasible in the future.Item Delay-aware Scheduling in Wireless Coding Networks: To Wait or Not to Wait(2012-02-14) Ramasamy, SolairajaWireless technology has become an increasingly popular way to gain network access. Wireless networks are expected to provide efficient and reliable service and support a broad range of emerging applications, such as multimedia streaming and video conferencing. However, limited wireless spectrum together with interference and fading pose signi cant challenges for network designers. The novel technique of network coding has a significant potential for improving the throughput and reliability of wireless networks by taking advantage of the broadcast nature of wireless medium. Reverse carpooling is one of the main techniques used to realize the benefits of network coding in wireless networks. With reverse carpooling, two flows are traveling in opposite directions, sharing a common path. The network coding is performed in the intermediate (relay) nodes, which saves up to 50% of transmissions. In this thesis, we focus on the scheduling at the relay nodes in wireless networks with reverse carpooling. When two packets traveling in opposite directions are available at the relay node, the relay node combines them and broadcasts the resulting packet. This event is referred to as a coding opportunity. When only one packet is available, the relay node needs to decide whether to wait for future coding opportunities, or to transmit them without coding. Though the choice of holding packets exploits the positive aspects of network coding, without a proper policy in place that controls how long the packets should wait, it will have an adverse impact on delays and thus the overall network performance. Accordingly, our goal is to find an optimal control strategy that delicately balances the tradeoff between the number of transmissions and delays incurred by the packets. We also address the fundamental question of what local information we should keep track of and use in making the decision of of whether to transmit uncoded packet or wait for the next coding opportunity. The available information consists of queue length and time stamps indicating the arrival time of packets in the queue. We could also store history of all previous states and actions. However, using all this information makes the control very complex and so we try to find if the overhead in collecting waiting times and historical information is worth it. A major contribution of this thesis is a stochastic control framework that uses state information based on what can be observed and prescribes an optimal action. For that, we formulate and solve a stochastic dynamic program with the objective of minimizing the long run average cost per unit time incurred due to transmissions and delays. Subsequently, we show that a stationary policy based on queue lengths is optimal, and the optimal policy is of threshold-type. Then, we describe a non-linear optimization procedure to obtain the optimal thresholds. Further, we substantiate our analytical ndings by performing numerical experiments under varied settings. We compare systems that use only queue length with those where more information is available, and we show that optimal control that uses only the queue length is as good as any optimal control that relies on knowing the entire history.Item Delay-sensitive Communications Code-Rates, Strategies, and Distributed Control(2012-02-14) Parag, ParimalAn ever increasing demand for instant and reliable information on modern communication networks forces codewords to operate in a non-asymptotic regime. To achieve reliability for imperfect channels in this regime, codewords need to be retransmitted from receiver to the transmit buffer, aided by a fast feedback mechanism. Large occupancy of this buffer results in longer communication delays. Therefore, codewords need to be designed carefully to reduce transmit queue-length and thus the delay experienced in this buffer. We first study the consequences of physical layer decisions on the transmit buffer occupancy. We develop an analytical framework to relate physical layer channel to the transmit buffer occupancy. We compute the optimal code-rate for finite-length codewords operating over a correlated channel, under certain communication service guarantees. We show that channel memory has a significant impact on this optimal code-rate. Next, we study the delay in small ad-hoc networks. In particular, we find out what rates can be supported on a small network, when each flow has a certain end-to-end service guarantee. To this end, service guarantee at each intermediate link is characterized. These results are applied to study the potential benefits of setting up a network suitable for network coding in multicast. In particular, we quantify the gains of network coding over classic routing for service provisioned multicast communication over butterfly networks. In the wireless setting, we study the trade-off between communications gains achieved by network coding and the cost to set-up a network enabling network coding. In particular, we show existence of scenarios where one should not attempt to create a network suitable for coding. Insights obtained from these studies are applied to design a distributed rate control algorithm in a large network. This algorithm maximizes sum-utility of all flows, while satisfying per-flow end-to-end service guarantees. We introduce a notion of effective-capacity per communication link that captures the service requirements of flows sharing this link. Each link maintains a price and effective-capacity, and each flow maintains rate and dissatisfaction. Flows and links update their respective variables locally, and we show that their decisions drive the system to an optimal point. We implemented our algorithm on a network simulator and studied its convergence behavior on few networks of practical interest.Item On delay-sensitive communication over wireless systems(2009-05-15) Liu, LingjiaThis dissertation addresses some of the most important issues in delay-sensitive communication over wireless systems and networks. Traditionally, the design of communication networks adopts a layered framework where each layer serves as a ?black box? abstraction for higher layers. However, in the context of wireless networks with delay-sensitive applications such as Voice over Internet Protocol (VoIP), on-line gaming, and video conferencing, this layered architecture does not offer a complete picture. For example, an information theoretic perspective on the physical layer typically ignores the bursty nature of practical sources and often overlooks the role of delay in service quality. The purpose of this dissertation is to take on a cross-disciplinary approach to derive new fundamental limits on the performance, in terms of capacity and delay, of wireless systems and to apply these limits to the design of practical wireless systems that support delay-sensitive applications. To realize this goal, we consider a number of objectives. 1. Develop an integrated methodology for the analysis of wireless systems that support delay-sensitive applications based, in part, on large deviation theory. 2. Use this methodology to identify fundamental performance limits and to design systems which allocate resources efficiently under stringent service requirements. 3. Analyze the performance of wireless communication networks that takes advantage of novel paradigms such as user cooperation, and multi-antenna systems. Based on the proposed framework, we find that delay constraints significantly influence how system resources should be allocated. Channel correlation has a major impact on the performance of wireless communication systems. Sophisticated power control based on the joint space of channel and buffer states are essential for delaysensitive communications.Item Optimization in Geometric Graphs: Complexity and Approximation(2011-02-22) Kahruman-Anderoglu, SeraWe consider several related problems arising in geometric graphs. In particular, we investigate the computational complexity and approximability properties of several optimization problems in unit ball graphs and develop algorithms to find exact and approximate solutions. In addition, we establish complexity-based theoretical justifications for several greedy heuristics. Unit ball graphs, which are defined in the three dimensional Euclidian space, have several application areas such as computational geometry, facility location and, particularly, wireless communication networks. Efficient operation of wireless networks involves several decision problems that can be reduced to well known optimization problems in graph theory. For instance, the notion of a \virtual backbone" in a wire- less network is strongly related to a minimum connected dominating set in its graph theoretic representation. Motivated by the vastness of application areas, we study several problems including maximum independent set, minimum vertex coloring, minimum clique partition, max-cut and min-bisection. Although these problems have been widely studied in the context of unit disk graphs, which are the two dimensional version of unit ball graphs, there is no established result on the complexity and approximation status for some of them in unit ball graphs. Furthermore, unit ball graphs can provide a better representation of real networks since the nodes are deployed in the three dimensional space. We prove complexity results and propose solution procedures for several problems using geometrical properties of these graphs. We outline a matching-based branch and bound solution procedure for the maximum k-clique problem in unit disk graphs and demonstrate its effectiveness through computational tests. We propose using minimum bottleneck connected dominating set problem in order to determine the optimal transmission range of a wireless network that will ensure a certain size of "virtual backbone". We prove that this problem is NP-hard in general graphs but solvable in polynomial time in unit disk and unit ball graphs. We also demonstrate work on theoretical foundations for simple greedy heuristics. Particularly, similar to the notion of "best" approximation algorithms with respect to their approximation ratios, we prove that several simple greedy heuristics are "best" in the sense that it is NP-hard to recognize the gap between the greedy solution and the optimal solution. We show results for several well known problems such as maximum clique, maximum independent set, minimum vertex coloring and discuss extensions of these results to a more general class of problems. In addition, we propose a "worst-out" heuristic based on edge contractions for the max-cut problem and provide analytical and experimental comparisons with a well known "best-in" approach and its modified versions.