基于SINR的无线网络拓扑控制算法的设计与分析

发布时间：2018-06-08 07:33

本文选题：无线传感器网络 + 物理干扰模型　；参考：《曲阜师范大学》2017年硕士论文

【摘要】：拓扑控制有助于减少网络能耗和干扰,改进网络吞吐量和生存周期,同时传感器节点因其体积小,部署方便等优势广泛用于无线网络,但由于节点本身物理特性的限制导致节点的能量有限,加之实际环境中存在干扰和背景噪声,无线网络的链路质量容易受到影响。因此,采取有效方法而不是忽略干扰的存在是研究无线网络中拓扑控制的一个热门问题。现有的拓扑控制算法,相当大一部分都是基于图模型,而其过分简单化节点之间的通信,没有考虑干扰的影响。近年来,基于物理干扰模型(Signal to Interference plus Noise Ratio,SINR)的拓扑控制算法受到广泛关注,本文主要讨论物理干扰模型下的拓扑控制算法。本文首先介绍无线网络方面的基础知识,以及当前的一些研究现状、经典算法。基于两个维度提出两个物理干扰模型下的拓扑控制算法,并通过理论分析验证了算法的正确性。最后,运用仿真与其他算法对比,证明了算法性能的优越性。本文研究内容如下:在第三章,由于图模型的拓扑控制不足以正确的表示干扰程度,导致高干扰和低吞吐量,因此我们研究物理干扰模型下的拓扑控制问题,目的是最大限度的减少干扰延长网络的生存周期。提出为解决这一问题的随机分布模型下的集中式算法MinPD(Minimum Path Distance)。同时引入休眠机制,使不同类型的节点采取不同的休眠机制,减少空闲监听时不必要的能量消耗。与已有算法MaxSR相比,第一个算法能保证网络中的节点有更小的干扰度。第二个算法引入休眠机制提高网络的生存期。仿真表明任意随机分布比泊松分布更适用于节点的大范围部署。由于物理干扰模型下通常假设初始网络连通,我们提出一个在物理干扰模型下的初始网络连通构造算法ICBS(Initial Connectivity based SINR),使得网络以概率1连通,而不是以某一概率p,p(27)1,指出该算法比较适用于节点规模较小的情况,并通过仿真实验证明节点规模和算法执行时间并不是严格的正比例关系。在第四章,提出PRR(Packet Reception Rate)和SINR相结合的PRR-S算法,目的是在实际的物理环境中,在满足网络连通的前提下,提高网络中链路的质量。引入社会学中的六度分隔理论,首先对六度分隔理论在无线网络中的适用性做出理论分析,然后通过仿真证明当节点的度大于等于6时,网络以高概率连通,这与之前的理论分析结论相同;同时与已有的算法相比,SINR的阈值有了明显的提升,数据包接收率也明显提高,链路质量明显提高。
[Abstract]:Topology control can reduce network energy consumption and interference, improve network throughput and lifetime, and sensor nodes are widely used in wireless networks because of their small size and easy deployment. However, due to the limitation of the physical characteristics of the nodes, the energy of the nodes is limited, in addition to the interference and background noise in the actual environment, the link quality of the wireless network is easily affected. Therefore, it is a hot issue to study topology control in wireless networks by adopting effective methods rather than ignoring the existence of interference. Most of the existing topology control algorithms are based on graph models, but they oversimplify the communication between nodes without considering the influence of interference. In recent years, the topology control algorithm based on signal to interference plus noise (SINR) has received extensive attention. In this paper, the topology control algorithm based on physical interference model is mainly discussed. This paper first introduces the basic knowledge of wireless network, as well as some current research status, classical algorithms. Based on two dimensions, a topology control algorithm based on two physical interference models is proposed, and the correctness of the algorithm is verified by theoretical analysis. Finally, the performance of the algorithm is proved by comparison between simulation and other algorithms. The main contents of this paper are as follows: in Chapter 3, because the topological control of the graph model is not enough to represent the degree of interference correctly, it leads to high interference and low throughput, so we study the topology control problem under the physical interference model. The aim is to minimize interference and prolong the lifetime of the network. In order to solve this problem, a centralized algorithm, MinPD-Minimum path distance, is proposed under the stochastic distribution model. At the same time, the dormancy mechanism is introduced to make different types of nodes adopt different sleep mechanism, which can reduce the unnecessary energy consumption in idle listening. Compared with the existing MaxSR algorithm, the first algorithm can ensure that the nodes in the network have a smaller degree of interference. The second algorithm introduces sleep mechanism to improve the lifetime of the network. Simulation results show that arbitrary random distribution is more suitable for large scale deployment than Poisson distribution. Due to the assumption of initial network connectivity in physical disturbance model, we propose an initial network connectivity algorithm called ICBS initial Connectivity based SINRN, which makes the network connected with probability 1. Instead of using a certain probability, it is pointed out that the algorithm is more suitable for the small node size, and the simulation results show that the size of the node and the execution time of the algorithm are not strictly proportional to each other. In chapter 4, a PRR-S algorithm combining PRR packet Reception Rateand SINR is proposed, which aims to improve the quality of the link in the real physical environment under the premise of satisfying the network connectivity. The six-degree separation theory in sociology is introduced to analyze the applicability of the six-degree separation theory in wireless networks, and then the simulation results show that when the degree of nodes is greater than or equal to 6, the network is connected with high probability. Compared with the existing algorithms, the threshold of SINR is obviously improved, the packet reception rate is improved, and the link quality is improved.
【学位授予单位】：曲阜师范大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TP212.9;TN929.5

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