认知无线自组织网络拓扑控制研究

发布时间：2018-04-14 00:08

  本文选题：认知无线自组织网络 + 拓扑控制　； 参考：《电子科技大学》2014年硕士论文

【摘要】：移动自组织网络是由一组无线节点构成,不需要固定基础设施的多跳无线网络。该类网络具有自发现、自组织、自愈合的特点,有很好的灵活性。认知无线电通过频谱感知技术,能够动态发现和利用电磁空间的可用频谱,既可以用来提高频谱利用率,也可以用于躲避外部电磁干扰。认知无线自组织网络将认知无线电融入到移动自组织网络中,使自组织网络中的节点具有感知和学习能力,能够动态感知和使用网络区域内的空闲频谱,解决无线网络频谱资源稀缺和分配问题,增强网络拓扑的连通性和网络生存性。认知无线自组织网络中的网络拓扑结构不仅受节点之间的相对位置、节点的发射功率等因素影响,而且还与节点的可用信道有关。本文重点研究认知无线自组织网络鲁棒性的拓扑控制以及基于分簇的拓扑管理问题,主要包括以下几个方面的内容:首先,介绍了认知无线自组织网络的特点及其关键技术,分析了拓扑控制的重要性。对比了传统无线自组织网络和认知无线自组织网络的差异。其次,针对所有节点存在若干公共信道的多接口认知无线自组织网络,即网络节点配有多套收发信机,整个网络有多个可用信道存在的情况,综合考虑网络拓扑的连通度、网络容量和网络拓扑鲁棒性,采用预先分配机制,设计提出了一种鲁棒性的拓扑控制算法RTCA(Robust Topology Control Algorithm)。该算法为网络节点的每个收发信机分配工作信道,分配结果在保障网络连通性的前提下,不仅让网络中的同频干扰最小,使网络容量最大化,而且当网络中某条工作信道不可用时,在受影响的收发信机工作信道切换之前,依然能够保证网络的连通性,使网络拓扑具有很好的鲁棒性。仿真结果表明,RTCA算法能够提升网络的容量,与单纯的干扰感知拓扑控制算法IATA(Interference-Aware Topology control Algorithm)相比,能够保证网络的连通性。然后,针对全网节点不存在公共信道的认知无线自组织网络,采用基于簇结构的拓扑管理机制,网络节点通过分布式的信息交互建立簇结构,使簇内成员有公共的可用信道,簇首节点通过簇内的控制信道进行簇的管理和维护。由于簇内的公共信道数量和簇的规模是两个相互制约的条件,既要考虑簇内公共信道数量,以保证簇结构的稳定性和容量,又要尽量扩大簇的规模以减小网络中簇的数目。因此提出了一种权衡簇内公共信道数和簇规模的分簇算法CTCS(Clustering based on Tradeoff common Channels and cluster Size),把分簇问题转化成偶图模型,使簇内公共信道数在满足要求的前提下,权衡簇内的公共信道数和簇的规模。仿真结果表明,CTCS算法与改进的LCA(Lowest id Cluster Algorithm)算法相比,能够保证簇内有公共信道,且分簇规模较大。最后,总结了全文工作,并对下一步工作进行了展望。
[Abstract]:Mobile ad hoc network is composed of a set of wireless nodes, multi hop wireless networks need not fixed infrastructure. The network has the characteristics of self discovery, self-organization, self-healing, has good flexibility. The cognitive radio spectrum sensing technology to dynamically discover and use the available spectrum of electromagnetic space, both can be used to improve the spectrum utilization rate, can also be used to avoid the external electromagnetic interference. The cognitive organization of cognitive radio network will be integrated into mobile ad in wireless ad hoc networks, the self organizing nodes in a network with perception and learning ability, can use dynamic idle spectrum sensing and network in the region, the wireless spectrum resource scarcity and distribution the problem, enhance network topology connectivity and network survivability. Cognitive network topology organization in the network is not only affected by the relative position between the nodes of the wireless node, the Effects of injection power and other factors, but also the available channel and node. This paper focuses on the research of cognitive wireless self organization network topology control robustness and topology based clustering management problems, mainly including the following aspects: firstly, introduces the cognitive characteristics and key technologies of wireless ad hoc network, analyzes the importance of topology control. Compared the difference of traditional wireless ad hoc networks and cognitive wireless ad hoc networks. Secondly, all nodes for multi interface cognitive some common channel wireless ad hoc network, the network node is equipped with multiple sets of transceiver, the entire network has multiple available channels, considering the network topological connectivity the network capacity, network topology and robustness, the pre allocation mechanism, put forward the design of topology control algorithm RTCA is a robust (Robust Topology Contr Ol Algorithm). The algorithm for each transceiver distribution channel network nodes, distribution results in the premise of ensuring the network connectivity, not only for the same frequency interference in the network is minimal, the network capacity is maximized, and when the network in a channel is not available, before work transceiver channel switching affected, can still guarantee the connectivity of the network, the network topology has good robustness. The simulation results show that RTCA algorithm can improve the network capacity, and interference aware topology control algorithm IATA (Interference-Aware Topology control Algorithm only) compared to guarantee the connectivity of the network. Then, in view of the whole network node does not exist the common channel cognitive wireless ad hoc network, the topology management scheme based on cluster structure, network nodes establish mutual cluster structure through distributed information exchange, the cluster into A member of the public channel, the cluster head nodes through the control channel in cluster cluster management and maintenance. As the number of clusters and the public channel in cluster size is two constrained conditions, it is necessary to consider the number of public channel cluster, in order to ensure the stability of the cluster structure and capacity, but also to the number of expand the scale of clusters to reduce the network cluster. This paper proposes a trade-off between public channel number and cluster cluster scale clustering algorithm CTCS (Clustering based on Tradeoff common Channels and cluster Size), the clustering problem is transformed into a bipartite graph model, the public channel number in the cluster to meet the requirements of the premise the balance of public channel within the cluster, number and size of cluster. The simulation results show that the CTCS algorithm and the improved LCA (Lowest ID Cluster Algorithm) algorithm, can ensure that the cluster in the public channel, and the large scale cluster. Finally, summarizes the The full text work is made and the next step is prospected.

【学位授予单位】：电子科技大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TN929.5
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本文编号：1746822