Browsing by Subject "effective capacity"
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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 Delay-sensitive communication over wireless multihop channels(2009-05-15) Ali, Omar AhmedWireless systems of today face the dual challenge of both supporting large traffic flows and providing reliable quality of service to different delay-sensitive applications. For such applications, it is essential to derive meaningful performance measures such as queue-length distribution and packet loss probability, while providing service guarantees. The concepts of effective bandwidth and effective capacity offer a powerful cross-layer approach that provides suitable performance metrics for the bandwidth and capacity of wireless channels supporting delay-sensitive traffic. Many wireless systems rely on multihop forwarding to reach destinations outside the direct range of the source. This work extends part of the methodology available for the design of wireless systems to the multihop paradigm. It describes the analysis of a communication system with two hops using this cross-layer approach. A framework is developed to study the interplay between the allocation of physical resources across the wireless hops and overall service quality as defined by a queueing criterion based on large deviations. Decoupling techniques introduce simple ways of analyzing the queues independently. Numerical analysis helps identify fundamental performance limits for Rayleigh block fading wireless channel models with independent and identically distributed blocks. Simulation studies present comparable results akin to that obtained using the analytical framework. These results suggest that it is imperative to account for queueing aspects while analyzing delay-sensitive wireless communication systems.Item Distributed Control Approaches to Network Optimization(2010-07-14) Sah, SankalpThe objective of this research is to develop distributed approaches to optimizing network traffic. Two problems are studied, which include exploiting social networks in routing packets (coupons) to desired network nodes (users in the social network), and developing a rate based transport protocol, which will guarantee that all the flows in a network (e.g. Internet) meet a delay constraint per packet. Firstly, we will study social networks as a means of obtaining information about a system. They are increasingly seen as a means of obtaining awareness of user preferences. Such awareness could be used to target goods and services at them. We consider a general user model, wherein users could buy different numbers of goods at a marked and at a discounted price. Our first objective is to learn which users would be interested in a particular good. Second, we would like to know how much to discount these users such that the entire demand is realized, but not so much that profits are decreased. We develop algorithms for multihop forwarding of such discount coupons over an online social network, in which users forward coupons to each other in return for a reward. Coupling this idea with the implicit learning associated with backpressure routing (originally developed for multihop wireless networks), we would like to demonstrate how to realize optimal revenue. We will then propose a simpler heuristic algorithm and try to show, using simulations, that its performance approaches that of backpressure routing. As the second problem, we look at the traditional formulation of the total value of information transfer, which is a multi-commodity flow problem. Here, each data source is seen as generating a commodity along a fixed route, and the objective is to maximize the total system throughput under some concept of fairness, subject to capacity constraints of the links used. This problem is well studied under the framework of network utility maximization and has led to several different distributed congestion control schemes. However, this idea of value does not capture the fact that flows might associate value, not just with throughput, but with link-quality metrics such as packet delay, jitter and so on. The traditional congestion control problem is redefined to include individual source preferences. It is assumed that degradation in link quality seen by a flow adds up on the links it traverses, and the total utility is maximized in such a way that the quality degradation seen by each source is bounded by a value that it declares. Decoupling source-dissatisfaction and link-degradation through an ?effective capacity? variable, a distributed and provably optimal resource allocation algorithm is designed, to maximize system utility subject to these quality constraints. The applicability of our controller in different situations is illustrated, and results are supported through numerical examples.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 Quality of service analysis for hybrid-ARQ(2009-05-15) Gunaseelan, Nirmal K.Data intensive applications, requiring reliability and strict delay constraints, have emerged recently and they necessitate a different approach to analyzing system performance. In my work, I establish a framework that relates physical channel parameters to the queueing performance for a single-user wireless system. I then seek to assess the potential benefits of multirate techniques, such as hybrid-ARQ (Automatic Repeat reQuest), in the context of delay-sensitive communications. Present methods of analysis in an information theoretic paradigm define capacity assuming that long codewords can be used to take advantage of the ergodic properties of the fading wireless channel. This definition provides only a limited characterization of the channel in the light of delay constraints. The assumption of independent and identically distributed channel realizations tends to over-estimate the system performance by not considering the inherent time correlation. A finite-state continuous time Markov channel model that I formulate enables me to partition the instantaneous data-rate received at the destination into a finite number of states, representing layers in a hybrid-ARQ scheme. The correlation of channel has been incorporated through level crossing rates as transition rates in the Markov model. The large deviation principle governing the buffer overflow of the Markov model, is very sensitive to channel memory, is tractable, and gives a good estimate of the system performance. Metrics such as effective capacity and probability of buffer overflow, that are obtained through large deviations have been related to the wireless physical layer parameters through the model. Using the above metrics under QoS constraints, I establish the quantitative performance advantage of using hybrid-ARQ over traditional systems. I conduct this inquiry by restricting attention to the case where the expected transmit power is fixed at the transmitter. The results show that hybrid-ARQ helps us in obtaining higher effective capacity, but it is very difficult to support delay sensitive communication over wireless channel in the absence of channel knowledge and dynamic power allocation strategies.