异构网络中的网络选择算法研究

发布时间：2018-06-30 04:15

本文选题：异构网络 + 无线资源管理　；参考：《南京邮电大学》2014年硕士论文

【摘要】：下一代无线网络必将是一个能够将现有的、未来即将出现的各种不同无线接入网络融合在一起的异构无线网络(HWNs),其目的是利用系统内不同网络之间的异构性结合移动终端的多模特性,给用户提供多样化、个性化的生活。然而异构网络环境下的无线资源管理却始终面临着一系列问题和挑战,其中异构无线网络的选择是异构网络环境中用户或移动终端所要面对的首要问题,关于异构网络选择算法的研究已经成为非常重要的课题。本文从多属性决策算法及其性能比较、Markov在选择算法性能分析中的应用、OWA算子在网络选择场景下的应用等方面对异构网络选择算法进行了分析和研究。论文对简单加权法(SAW)、乘法指数加权法(MEW)、接近理想值排序法(TOPSIS)、灰色关联分析法(GRA)、加权马尔科夫链法(WMC)、淘汰选择法ELECTRE、多准则妥协解排序法VIKOR等七种多属性决策算法进行了研究和仿真,并对算法性能进行了分析比较,就网络选择结果而言,SAW、MEW、TOPSIS和VIKOR算法提供了一个比较保守的等级划分,而ELECTRE、GRA和WMC算法能够更加综合考虑,适用更多影响因子的情况。为了更全面地分析异构网络选择算法性能,本文在TDMA和WCDMA的异构网络中,结合语音业务和数据业务两种业务类型,建立了四维马尔科夫链,在状态转移过程中,加入了状态权重变量,该变量的取值对应于不同的网络选择算法。在分析算法性能时,结合之前的研究成果中关于异构网络切换率的分析及结论,计算出该四维马尔科夫模型下的业务接入率、切换率、服务率及状态权重等模型参数,进而对马尔科夫链的稳态分布进行求解,得到网络选择算法的性能诸如网络接入阻塞率、网络切换阻塞率及网络吞吐量等性能参数闭合公式。为了证明该模型分析算法的合理性,分别对随机选择网络算法、基于业务类型1选择算法、基于业务类型2选择算法、基于负载均衡选择算法的算法性能进行了分析比较。仿真结果表明,本文所提出的四维马尔科夫模型对网络选择算法性能的分析是合理的。OWA算子在模糊逻辑、多属性决策及群组决策等领域已有广泛运用,本文将OWA算子运用到异构网络选择场景,在由无线局域网(WLAN)、无线城域网(WiMAX)和通用移动通讯系统(UMTS)构成的异构网络中,提出了一种基于OWA算子的异构网络选择算法。该算法先对各个候选网络的网络属性进行归一化处理,进而选择其中的“最大因素”进行合理赋权,即采用非平均赋权方法,最后利用OWA算子的定义式计算出各个候选网络的OWA算子值大小,进而进行网络选择,通过与SAW、TOPSIS和GRA网络选择算法的性能仿真比较,可以验证该算法的合理性及正确性。
[Abstract]:The next generation of wireless networks is bound to be able to In the future, heterogeneous wireless networks (HWNs) with different wireless access networks will come into being. The purpose of HWNs is to combine the heterogeneity of different networks in the system with the multi-mode characteristics of mobile terminals, and to provide users with diversified and personalized lives. However, wireless resource management in heterogeneous network environment is always facing a series of problems and challenges, among which, the choice of heterogeneous wireless network is the most important problem for users or mobile terminals in heterogeneous network environment. The research of heterogeneous network selection algorithm has become a very important topic. This paper analyzes and studies the heterogeneous network selection algorithm from the aspects of multi-attribute decision making algorithm and its performance comparison the application of Markov in the performance analysis of the selection algorithm and the application of OWA operator in the network selection scenario. This paper deals with seven kinds of multi-attribute decision making algorithms, such as simple weighting method (saw), multiplicative exponential weighting method (Mew), near ideal value ranking method (TOPSIS), grey relational analysis (GRA), weighted Markov chain method (WMC), elimination selection method (ELECTREE), multi-criteria compromise solution ranking method (VIKOR), and so on. Research and simulation, The performance of the algorithm is analyzed and compared. As far as the network selection results are concerned, SAW / MEWN TOPSIS and VIKOR provide a conservative classification, while the ELECTREGRA and WMC algorithms can be considered more synthetically and can be applied to the situation of more influence factors. In order to analyze the performance of heterogeneous network selection algorithm more comprehensively, in the heterogeneous network of TDMA and WCDMA, a four-dimensional Markov chain is established in the process of state transition by combining the two types of voice service and data service. The state weight variable is added, and the value of the variable corresponds to different network selection algorithms. When analyzing the performance of the algorithm, combined with the analysis and conclusion of the handoff rate of heterogeneous network in previous research results, the model parameters such as service access rate, handoff rate, service rate and state weight under the four-dimensional Markov model are calculated. Then the steady-state distribution of Markov chain is solved, and the performance of the network selection algorithm such as network access blocking rate, network handoff blocking rate and network throughput are obtained. In order to prove the rationality of the model analysis algorithm, the performance of random selection network algorithm, traffic type 1 selection algorithm, service type 2 selection algorithm and load balancing selection algorithm are analyzed and compared respectively. The simulation results show that the proposed four-dimensional Markov model is reasonable in analyzing the performance of the network selection algorithm. OWA operator has been widely used in the fields of fuzzy logic, multi-attribute decision-making and group decision. In this paper, the OWA operator is applied to the heterogeneous network selection scenario. In the heterogeneous network composed of WLAN, WiMAX and UMTS, an OWA operator based heterogeneous network selection algorithm is proposed. The algorithm firstly normalizes the network attributes of each candidate network, and then selects the "maximum factor" for reasonable weighting, that is, adopting the non-average weighting method. Finally, the OWA operator value of each candidate network is calculated by using the definition of OWA operator, and then the network selection is carried out. The rationality and correctness of the algorithm can be verified by comparing with the performance simulation of SAWN TOPSIS and GRA network selection algorithm.
【学位授予单位】：南京邮电大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TN929.5

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