无线自组织网络容量算法研究

发布时间：2018-03-12 22:28

本文选题：动态容量　切入点：信噪比模型　出处：《浙江工业大学》2016年博士论文　论文类型：学位论文

【摘要】：无线自组织网络(Wireless Mobile Ad Hoc Networks,MANET)是由若干个可移动的无线收发装置以自组织的方式形成的一个灵活、多跳、无中心网络。由于无线自组织网络具备组网过程不需要依靠任何预设的基础设施等众多优势,被广泛地应用于军事、医疗、救灾、商务会议等各种实践领域。其中,如何计算无线自组织网络整体信道特性和传输协议下所能够支持的最大信息流,便是无线自组织网络容量问题,属于网络研究和设计的热点领域。由于无线自组织网络的特殊性(节点能量受限、拓扑结构灵活多变、多路径衰落效应等)使得无线自组织网络平均吞吐量远远小于有线网络,并不能直接应用香农公式计算无线自组织网络容量。因此,针对无线自组织网络的特点,设计算法计算网络容量并设法提高网络容量成为一个非常关键而有意义的课题。在深入分析相关研究后,发现经典的无线网络容量定义考虑不够全面,比如并未包含网络服务质量保障等约束要求。现实应用中,网络路由协议、节点能量消耗模型与网络容量计算结果密切相关。本文在网络节点一阶能量损耗数学模型的基础上,分析了两类无线自组织网络系统的容量计算方法:当网络拓扑结构不确定时,推导无线自组织网络容量上界与下界闭合数学表达式;当网络拓扑结构确定时,建立网络生存容量和动态容量的计算模型。在分析影响网络容量的若干因素后,本文还提出了一种中继节点功率优化控制的协作通信系统,提高网络信息的传输速率、降低网络信息的传输中断概率,以此达到提到网络容量的目的。本文的主要工作和研究成果如下:1.在Steven Weber等人信噪比网络容量模型的基础上,分析无线自组织网络信息的多跳传输概率,提出了一种基于生存时间的多跳无线自组织网络容量计算方法,并推导网络容量上界和下界的闭合数学表达式。针对节点位置服从均匀分布以及泊松点过程分布两类随机网络,采用MATLAB软件进行数值计算,分析网络节点数量与节点通信半径对于网络连通特性、网络单跳容量、网络多跳容量、网络生存时间以及基于生存时间的多跳容量的变化规律。得到如下结论:基于泊松点过程分布的无线自组织网络在多跳传输容量方面的表现要优于基于均匀分布的网络,且无线自组织网络的多跳特性有助于提高网络传输容量。2.本文将网络生存时间内所能传输的信息总量定义为网络生存容量,将某时刻网络的可用容量定义为网络剩余容量,亦可以称为网络动态容量,并建立整数规划数学模型描述网络生存容量与网络动态容量。考虑到路由策略与网络生存容量之间的关系,为获得更大的生存容量,本文提出了一种基于Grover算法的能量感知路由策略。最后,建立仿真模型分析基于Grover算法的能量感知路由策略与经典的AODV路由策略基础上网络生存容量、网络动态容量的变化趋势。得到如下结论:基于Grover算法的能量感知路由策略所获得的网络生存容量随着网络节点数量、通信半径的增加而增加。基于Grover算法的能量感知路由策略在容量方面的表现要优于经典的AODV路由策略,同时发现:无线自组织网络节点的移动性有助于提高网络生存容量、延缓网络动态容量的下降速度。3.在分析网络容量定义以及网络容量计算方法后,发现受限的网络带宽和网络资源是限制网络容量增长的关键因素,改善网络传输速率、降低中断概率对提升网络容量起着至关重要的作用。为此,本文提出了节点协作通信与功率优化分配两种方式提高无线自组织网络容量。首先本文提出了一种节点中继相互协作模式提高网络平均传输速率,并在基于Grover算法的能量感知路由协议中引入节点标号方式予以实现网络的最大流传输。然后,讨论当网络总功率受限时,建立优化数学模型对中继节点进行功率优化分配,并采用遗传算法求解最优功率分配方案。最后,采用MATLAB软件进行数值仿真,对比多中继协作且功率优化分配与非中继协作且功率均匀分配两种策略在中断概率、网络容量等方面的表现。得到如下结论:中继合作模式、能量优化分配可以提高网络传输容量,降低网络传输的中断概率。
[Abstract]:Wireless self-organizing network (Wireless Mobile Ad Hoc Networks, MANET) is formed by a plurality of mobile wireless transceiver in a self-organizing way a flexible, multi hop, no center network. The wireless self-organizing network with the network process without any predetermined infrastructure and many other advantages, is widely used in military, medical, disaster relief, business meetings and other various practical fields. Among them, how to calculate the maximum flow of information to support wireless ad hoc network overall channel characteristics and transmission protocol of wireless ad hoc network is the capacity of the network belongs to the research and design of the hot field. Because of the special wireless ad hoc network (of limited node energy, flexible topology, multi path fading effect) wireless self organization network is far less than the average throughput of the cable network, and can not be directly applied Shannon Calculation of wireless ad hoc network capacity. Therefore, in view of the wireless self-organizing network, algorithm design and calculation of network capacity and improving the capacity of the network become a very crucial and meaningful topic. In the analysis of relevant research, found that the classical definition of wireless network capacity is not comprehensive enough to consider for example does not include the service quality of the network security other constraints. In applications, network routing protocol, the node energy consumption model and the calculation results are closely related to the capacity of the network. In this paper, a mathematical model of network node order energy loss calculation method on the analysis of two types of wireless ad hoc network system capacity: when the network topology is uncertain, the capacity of wireless ad the organization network mathematical upper and lower bounds of closed form expressions; when determining the network topology, network computing model of survival capacity and the dynamic capacity. In the analysis of some factors influencing the network capacity, we propose a cooperative communication system with relay node power optimization control, improve the transmission rate of network information, network information transmission to reduce the outage probability, so as to achieve the purpose of network capacity mentioned. The main work and research results are as follows: 1. in Steven Weber et al. Noise ratio based network capacity model, analysis of multi hop wireless ad hoc network information transmission probability, is proposed based on the survival time of multi hop wireless self organization network capacity calculation method, and derive the network capacity of the upper and lower bounds on the closed mathematical expressions. The node location distribution and uniform distribution of two kinds of Poisson point process random network obey, numerical calculation is carried out by using MATLAB software, analysis of the number of the network nodes and node communication radius for network connectivity, single hop network capacity, Multi hop network capacity, network lifetime as well as based on the variation of survival time in multi hop capacity. Conclusions are as follows: Poisson point process distribution performance of self organization network in wireless multi hop transmission capacity is better than the uniform distribution network based on network is helpful to improve the transmission capacity of.2. the total information network can define transmission time as the network survival capacity and multi hop wireless ad hoc network characteristics, will be available at a time of network capacity is defined as the network residual capacity, can also be called dynamic network capacity, and establishes an integer programming model to describe the network survival capacity and dynamic network capacity. Considering the relationship between routing strategy with the network survival capacity, in order to obtain greater survival capacity, this paper proposes an energy aware routing strategy based on Grover algorithm. Finally, establish the simulation model Type analysis of Grover algorithm and energy aware routing strategy with the classic AODV routing strategy based on network capacity based on dynamic change of network capacity. The conclusions are as follows: the energy aware routing strategy based on Grover algorithm of the network survival capacity with the number of the network nodes, increase communication radius increased. At the same time that performance of energy aware the routing strategy of Grover algorithm in terms of capacity to AODV routing strategy is better than the classic based on wireless ad hoc network node mobility is helpful to improve the network survival capacity, network delay dynamic capacity decreasing rate of.3. in the analysis of calculation method of network capacity and network capacity definition, found limited network bandwidth and cyber source is the key factors limiting the growth of network capacity, improve the network transmission rate, reduce the outage probability to improve the capacity of the network to play An important role. Therefore, this paper proposes a node cooperative communication and power allocation in two ways to improve the capacity of wireless ad hoc networks. Firstly, this paper proposes a relay cooperation mode to improve the average transmission rate of the network, and the maximum flow transmission energy aware routing algorithm in Grover is introduced to achieve network node labeling based on the discussion. Then, when the total power network limited, establishes the optimization mathematical model for optimal power allocation of the relay nodes, and the genetic algorithm for solving the optimal power allocation scheme. Finally, numerical simulation is carried out by using MATLAB software, and the comparison of multi relay cooperative and non cooperative power allocation and equal power allocation strategies in the two interrupt the probability of the network capacity and performance. The conclusions are as follows: relay cooperation mode, energy allocation can improve the network transmission Capacity to reduce the interruption probability of network transmission.

【学位授予单位】：浙江工业大学
【学位级别】：博士
【学位授予年份】：2016
【分类号】：TN929.5

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