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Cross-layer Resource Allocation In Wireless Networks Based On Convex Optimization

Posted on:2009-12-23Degree:DoctorType:Dissertation
Country:ChinaCandidate:P ChengFull Text:PDF
GTID:1118360242992016Subject:Communication and Information System
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Wireless resource allocation is a vital way to handel the conflict between the limited wireless resource and the increasing Quality of Service (QoS) requirement of multimedia traffics. However, with the development of multi-hop and heterogeneity techniques, the future wireless networks will consist of multi-hop cellular network, wireless mesh network, and cognitive radio network. These new types of networks have solved many problems that exist in the traditional wireless networks, e.g., lack of expansibility and robustness. However, just as every coin has two sides, these novel and powerful techniques will also change the way of utilizing wireless resource, and further become a challenge for the traditional layered resource allocation algorithm. In fact, significant performance gains can be achieved by various cross-layer approaches in these networks, and cross-layer resource allocation (CLRA) is necessary for the future wireless network protocol stack design. In this dissertation, under the guidance of information theory, network theory and convex optimization, the cross-layer resource allocation techniques in the typical three emerging types of wireless networks are intensively studied. The contents of this work are listed as follows:Two different CLRA methods are proposed for traditional cellular networks and multi-hop cellular networks, respectively. For the former case, a downlink system combining AMC and ARQ is considered. We study the problem of spectral efficiency maximization for QoS-guaranteed services, and propose a cross-layer link adaption algorithm to get the global optimal solution. For the multi-hop cellular network, a two-hop wireless link employing AMC and finite-length buffers is considered. We propose a multi-hop queuing model to analyze the network throughput and delay performance. Furthermore, we consider the problem of optimal power and bandwidth allocation for QoS-guaranteed services. We first discuss the optimal bandwidth allocation and the optimal power allocation. Then, we propose a joint allocation algorithm, which can iteratively find the optimal power-bandwidth pair and thereby improve the network performance.For CLRA in wireless mesh networks, we consider the problem of joint optimization of source coding, power control, ARQ control, and delay partitioning functionalities, our studied problem is to maximize the video quality under strict end-to-end delay con- straints through adjusting the source coding rate, end-to-end delay distribution, and each node's transmit power. First, the performances of application, physical, MAC, and network layers are modelled by some classical models under reasonable assumptions. Then, we formulate the studied problem as a mathematical optimization problem. This optimization problem is proved to be a nonlinear but log-convex one. Finally, we propose a centralized solution based on the geometric programming theory, as well as a partially distributed solution based on the Lagrangian dual decomposition technique. And both solutions are proved to converge to the global optimum of the above problem.For CLRA in cognitive radio networks, we study two types of problems, which are heterogeneous network coexisting and distributed dynamic spectrum access. With respect to the former case, we study the problem of 3G cellular network coexisting with 2G cellular network and the problem of 3G cellular network coexisting with WLAN, respectively. From the view of multiuser information theory, cognitive users' optimal access method and optimal power control policy are proposed for these two problems, respective. Then, for the case of dynamic spectrum access, the problem of wireless resource management in broadband cognitive OFDMA networks is addressed. The objective is to maximize cognitive users' weighted rate sum by jointly adjusting their rate, frequency, and power resource, under the constraints of multiple primary users' interference temperatures. We formulate the studied problem as two nonlinear and non-convex optimization problems, and propose a centralized greedy algorithm to solve one problem, as well as a centralized algorithm based on Lagrangian duality theory for the other. The two centralized algorithms are shown to be optimal, and both have polynomial time complexities. Finally, we present that the two centralized algorithms can be distributively implemented by introducing the idea of virtual clock.
Keywords/Search Tags:cross-layer resource allocation (CLRA), information theory, network theory, convex optimization, QoS, distributed algorithm, cellular network, wireless mesh network, cognitive radio network
PDF Full Text Request
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