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Resource allocation strategies for cognitive and cooperative MIMO communications: Algorithm and protocol design.

机译：认知和协作MIMO通信的资源分配策略：算法和协议设计。

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摘要

Dynamic Spectrum Access (DSA) and multi-input multi-output (MIMO) communications are among the most promising solutions to address the ever-increasing wireless demand. Cognitive radio (CR) is the enabling technology for DSA. In this dissertation, we propose several resource allocation strategies for multiuser and cooperative MIMO communications in the context of DSA/CR systems and wireless sensor networks (WSNs). First, to maximize the Cognitive MIMO (CMIMO) network throughput, we develop a low-complexity distributed algorithm that configures the transmit antenna radiation directions and allocates power to all data streams over both frequency and space/antenna dimensions. We formulate the joint power, spectrum allocation, and MIMO beamforming problem as a noncooperative game. We prove that the game always admits at least one Nash Equilibrium (NE). To improve the efficiency of this NE (i.e., network throughput), we derive user-dependent pricing policies that force MIMO transmitters to steer their beams away from nearby unintended receivers. Second, we propose beamforming games (with and without pricing policies) that jointly improve the power and spectrum efficiency while meeting various rate demands. We derive sufficient conditions under which a given rate-demand profile can be supported. To account for user fairness, we develop a channel assignment and power allocation mechanism based on the Nash Bargaining solution. The proposed scheme allows CMIMO links to first propose their rate demands, and then cooperate and bargain in the process of determining their channel assignment, power allocation, and "precoding" matrices. In the context of WSNs where energy efficiency is a key design metric, we propose a cooperative MIMO framework. The framework partitions a WSN into various clusters in which several single-antenna sensors cooperate and form a virtual MIMO node so as to conserve power through harvesting MIMO's diversity gain. Extensive simulations show that our proposed schemes achieve significant throughput and energy efficiency improvement compared with state-of-the-art designs.
机译：动态频谱访问（DSA）和多输入多输出（MIMO）通信是满足不断增长的无线需求的最有前途的解决方案。认知无线电（CR）是DSA的使能技术。本文在DSA / CR系统和无线传感器网络（WSNs）的背景下，提出了几种用于多用户和协作式MIMO通信的资源分配策略。首先，为了最大化认知MIMO（CMIMO）网络的吞吐量，我们开发了一种低复杂度的分布式算法，该算法可配置发射天线的辐射方向，并在频率和空间/天线尺寸上为所有数据流分配功率。我们将联合功率，频谱分配和MIMO波束成形问题表述为非合作博弈。我们证明游戏总是允许至少一个纳什均衡（NE）。为了提高此NE的效率（即网络吞吐量），我们得出了依赖于用户的定价策略，这些策略迫使MIMO发射机将其波束转向附近的意外接收机。其次，我们提出了波束成形游戏（有和没有定价政策），它们可以在满足各种速率需求的同时共同提高功率和频谱效率。我们得出了可以支持给定速率需求曲线的充分条件。为了解决用户公平问题，我们基于Nash讨价还价解决方案开发了一种渠道分配和功率分配机制。所提出的方案允许CMIMO链路首先提出其速率要求，然后在确定其信道分配，功率分配和“预编码”矩阵的过程中进行合作和讨价还价。在以能效为关键设计指标的WSN中，我们提出了一种协作MIMO框架。该框架将WSN划分为多个群集，其中几个单天线传感器协作并形成一个虚拟MIMO节点，以便通过收集MIMO的分集增益来节省功率。大量的仿真表明，与最新设计相比，我们提出的方案可显着提高吞吐量和能效。

著录项

  • 作者

    Nguyen, Diep Ngoc.;

  • 作者单位

    The University of Arizona.;

  • 授予单位 The University of Arizona.;
  • 学科 Engineering Electronics and Electrical.;Engineering System Science.
  • 学位 Ph.D.
  • 年度 2013
  • 页码 185 p.
  • 总页数 185
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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