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Energy Efficiency and Load Balancing in Next-Generation Wireless Cellular Networks.

机译：下一代无线蜂窝网络中的能源效率和负载平衡。

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摘要

This dissertation focuses on the resource allocation problem in next-generation cellular wireless networks. Our goal is to design and evaluate algorithms and procedures to provide a balanced load and to improve the energy-efficiency of these networks, while satisfying the quality-of-service constraints of the users. The contributions of this dissertation are (i) a new handover policy to balance the load in Long Term Evolution (LTE) Heterogeneous Networks (HetNets), (ii) an analytical characterization of the efficiency and fairness trade-off of LTE uplink schedulers, and (iii) energy-efficient resource allocation algorithms for LTE HetNets with quality-of-service constraints (QoS).;First, we address the load balancing problem in HetNets deployments. We focus on the cell selection and handover policies as more base stations with different properties and functionalities are deployed. Conventional methods such as the strongest cell approach, used in single-layer network architectures, do not offer balanced loading or optimal performance for the HetNets due to the transmit power differences, backhaul, and access constraints of different base station types. Therefore, we propose a new handover decision policy that employs cell breathing, which dynamically adjusts the cell coverage regions based on the uplink interference measurements and current system load. The proposed policy also contributes to the self-adaptive and self-organization goals of the next-generation cellular systems.;Next, we investigate the uplink resource scheduling problem in single carrier frequency-domain multiple access systems. We present an efficient implementation method that translates these scheduling problems into set partitioning problems. Then, we discuss a family of utility functions that enable us to investigate the performance of different frequency domain schedulers such as the sum-rate maximization, proportional fair, and max-min fair schedulers. We use the price of fairness as a metric to analytically quantify the efficiency and fairness trade-offs in the schedulers and provide several upper bounds. We believe that this type of analysis can provide guidelines for the network operators to control the efficiency and fairness trade-off as the data traffic grows.;Finally, we investigate the multi-cell multi-carrier network energy efficiency problem where we propose utility-based energy-efficient resource allocation algorithms. We consider a linearized load-adaptive power consumption model at the base stations. We study the interference pricing mechanisms which include the inter-cell interference contributions and penalize the transmissions based on the interference they create. We propose two types of power control algorithms. First, we propose an iterative multi-level water-filling algorithm for multi-cell wireless networks. Second, we employ the gradient ascent method to control the transmit power of base stations. Both of these frameworks are extended to include QoS constraints such as the minimum rate constraints for each user. We present the optimality conditions and convergence of both algorithms, along with their performance evaluations.
机译：本文主要研究下一代蜂窝无线网络中的资源分配问题。我们的目标是设计和评估算法和过程，以提供均衡的负载并提高这些网络的能源效率，同时满足用户的服务质量约束。本文的贡献是：（i）一种新的切换策略，以平衡长期演进（LTE）异构网络（HetNets）中的负载；（ii）LTE上行调度器的效率和公平性折衷的分析表征，以及（iii）具有服务质量约束（QoS）的LTE HetNets的节能资源分配算法。首先，我们解决了HetNets部署中的负载平衡问题。随着更多具有不同特性和功能的基站的部署，我们将重点放在小区选择和切换策略上。由于不同基站类型的发射功率差异，回程和访问限制，用于单层网络体系结构的常规方法（如最坚固的小区方法）无法为HetNet提供平衡的负载或最佳性能。因此，我们提出了一种采用小区呼吸的新切换决策策略，该策略根据上行链路干扰测量和当前系统负载来动态调整小区覆盖范围。所提出的策略也有助于下一代蜂窝系统的自适应和自组织目标。接下来，我们研究单载波频域多址系统中的上行资源调度问题。我们提出了一种有效的实现方法，可以将这些调度问题转换为集合分区问题。然后，我们讨论了一系列实用程序功能，这些功能使我们能够研究不同频域调度器的性能，例如和率最大化，比例公平和最大最小公平调度器。我们使用公平价格作为度量标准，以分析性地量化调度程序中的效率和公平权衡，并提供几个上限。我们认为，这种分析方法可以为网络运营商提供控制准则，以随着数据流量的增长控制效率和公平性。最后，我们研究了多小区多载波网络的能效问题，其中提出了效用-基于节能的资源分配算法。我们考虑基站的线性负载自适应功耗模型。我们研究了包括小区间干扰贡献在内的干扰定价机制，并根据它们产生的干扰对传输进行惩罚。我们提出两种类型的功率控制算法。首先，我们为多小区无线网络提出了一种迭代的多级注水算法。其次，我们采用梯度上升方法来控制基站的发射功率。这两个框架都被扩展为包括QoS约束，例如每个用户的最小速率约束。我们介绍了两种算法的最优性条件和收敛性，以及它们的性能评估。

著录项

  • 作者

    Davaslioglu, Kemal.;

  • 作者单位

    University of California, Irvine.;

  • 授予单位 University of California, Irvine.;
  • 学科 Electrical engineering.;Operations research.
  • 学位 Ph.D.
  • 年度 2015
  • 页码 188 p.
  • 总页数 188
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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