能量捕获驱动的异构网络资源调度与优化研究

发布时间：2018-03-10 04:35

本文选题：能量捕获技术　切入点：无线能量传输　出处：《中国科学技术大学》2016年博士论文　论文类型：学位论文

【摘要】：随着能量捕获(Energy Harvesting,EH)技术的发展和政府对绿色通信的积极倡导,近年来,基于能量捕获的无线通信系统得到了广泛深入的研究,同时无线能量传输技术(Wireless Energy Transfer or Wireless Power Transfer, WET or WPT)的发展也使得无线携能通信系统(Simultaneous Wireless Information and Power Transfer, SWIPT)成为了新的研究热点。如何高效地使用能量捕获网络中的能量进行数据业务的传输是能量捕获无线网络中具有实际意义的热点问题。本论文使用随机优化理论,对能量捕获无线通信系统进行数学建模和理论分析,针对不同场景下的无线网络传输效用最大化问题进行了研究,具体工作如下：1.首先,研究了点对点能量捕获无线通信系统的传输效用最大化问题,为了保证数据传输的服务质量(Quality of Service, QoS)和避免由于能量到达的随机性和间歇性引起的数据传输中断,将传输效用最大化问题建模为队列稳定性约束条件下的平均传输效用最大化问题。采用Lyapunov优化理论设计了在线的平均传输效用最大化算法,该算法不依赖于能量捕获过程和无线信道的先验知识。最后,通过Matlab数值仿真实验验证了所提出的平均传输效用最大化算法的有效性。2.研究了能量捕获通信系统中可伸缩编码(Scalable Video Coding, SVC)视频的自适应传输问题,在能量随机到达的条件下,为了保证视频的不间断传输以及减少可伸缩视频层频繁切换所引起的抖动效应,将可伸缩视频的自适应传输问题建模为带约束的最大化视频传输效用问题。采用Lyapunov优化理论对问题进行转化,提出了在线的动态视频层传输算法,所提出的算法不依赖于对能量捕获过程和信道的假设条件,具有较低的复杂度。最后,采用真实可伸缩视频序列进行了数值仿真实验,实验结果验证了所提算法的性能。3.考虑能量捕获通信系统中可伸缩视频的自适应传输问题,为了保证可伸缩视频基本层的不间断传输,将可充电电池中的能量预留作为一个约束,可伸缩视频传输效用最大化问题建模为CMDP模型。采用近似动态规划理论对模型设计了在线学习算法,同时采用高斯混合模型(Gaussian Mixture Model, GMM)和在线的期望最大化(Expectation Maximization, EM)算法对能量分布进行学习,利用学习得到的信息来提高算法的性能和收敛速度。最后用真实视频序列设计仿真实验,验证了所提出的在线学习算法的有效性。4.考虑辐射式无线携能通信系统,定义了发射器和接收器的状态和状态间的转移过程,此外定义了无线携能通信系统中的信令和能量交互过程。无线携能通信协议的提出符合无线能量传输技术标准化和产业化的需求,是对无线携能通信系统的积极探索。
[Abstract]:With the development of energy capture technology and the active advocacy of green communication by the government, wireless communication systems based on energy capture have been studied extensively and deeply in recent years. At the same time, the development of wireless Energy Transfer or Wireless Power transfer (WET or WPTT) also makes wireless portable Wireless Information and Power transfer (SWIPT) become a new research hotspot. How to use energy efficiently to capture the energy in the network. The transmission of data services is a hot issue of practical significance in energy capture wireless networks. The mathematical modeling and theoretical analysis of the energy capture wireless communication system are carried out, and the problem of maximizing the utility of wireless network transmission under different scenarios is studied. The specific work is as follows: 1. In order to ensure the quality of service (QoS) of data transmission and avoid the interruption of data transmission caused by randomness and intermittency of energy arrival, the problem of maximizing the transmission utility of point-to-point energy capture wireless communication system is studied. The transmission utility maximization problem is modeled as the average transmission utility maximization problem under the constraint of queue stability. An online average transmission utility maximization algorithm is designed using Lyapunov optimization theory. The algorithm does not depend on the energy capture process and prior knowledge of the wireless channel. Finally, The effectiveness of the proposed average transmission utility maximization algorithm is verified by Matlab numerical simulation. 2. The adaptive transmission of scalable Video coding (SVC) video in the energy capture communication system is studied. Under the condition of random energy arrival, the adaptive transmission of scalable Video coding (SVC) video is studied. In order to ensure the continuous transmission of video and reduce the jitter effect caused by frequent switching in scalable video layer, The adaptive transmission problem of scalable video is modeled as the problem of maximizing the utility of video transmission with constraints. The problem is transformed by Lyapunov optimization theory, and an online dynamic video layer transmission algorithm is proposed. The proposed algorithm is independent of the assumptions of the energy capture process and the channel, and has low complexity. Finally, the real scalable video sequences are used for numerical simulation. The experimental results verify the performance of the proposed algorithm. 3. Considering the adaptive transmission of scalable video in the energy capture communication system, in order to ensure the continuous transmission of scalable video base layer, The problem of maximizing the utility of scalable video transmission is modeled as CMDP model by taking the energy reservation in rechargeable battery as a constraint, and an online learning algorithm is designed based on approximate dynamic programming theory. At the same time, the Gao Si hybrid model Gaussian Mixture Model (GMMM) and the online expectation maximization maximization (EMMM) algorithm are used to study the energy distribution, and the learning information is used to improve the performance and convergence speed of the algorithm. Finally, the simulation experiments are designed with real video sequences. The validity of the proposed online learning algorithm is verified. 4. Considering the radiative wireless portable communication system, the state and the state transfer process between the transmitter and receiver are defined. In addition, the signaling and energy interaction process in wireless portable communication system is defined. The proposed wireless energy communication protocol conforms to the requirements of standardization and industrialization of wireless energy transmission technology, and is an active exploration of wireless energy carrying communication system.
【学位授予单位】：中国科学技术大学
【学位级别】：博士
【学位授予年份】：2016
【分类号】：TN915.0

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