本文關(guān)鍵詞：移動(dòng)蜂窩網(wǎng)基站與流量空時(shí)分布規(guī)律研究　出處：《浙江大學(xué)》2017年碩士論文　論文類型：學(xué)位論文

  更多相關(guān)文章： 移動(dòng)蜂窩網(wǎng) 重尾分布 α-Stable模型 基站 流量 空時(shí)分布

【摘要】：近十年來,移動(dòng)蜂窩通信經(jīng)歷了天翻地覆的變化,從2G到3G,從LTE到第五代移動(dòng)通信(5G)。隨著移動(dòng)蜂窩通信技術(shù)的快速發(fā)展,移動(dòng)業(yè)務(wù)類型快速增加,移動(dòng)數(shù)據(jù)流量也隨之爆炸式增長(zhǎng),從而加快了基站部署的進(jìn)程�，F(xiàn)如今的移動(dòng)蜂窩網(wǎng)已經(jīng)演變成高度異構(gòu)化的網(wǎng)絡(luò)結(jié)構(gòu)�；究臻g拓?fù)浣Y(jié)構(gòu)和流量時(shí)空特性對(duì)網(wǎng)絡(luò)性能評(píng)估有至關(guān)重要的作用,本論文所研究的移動(dòng)蜂窩網(wǎng)基站與流量空時(shí)分布統(tǒng)計(jì)規(guī)律就是在這樣的背景下提出的。本文首先介紹了典型統(tǒng)計(jì)模型中重尾分布的數(shù)學(xué)概念與性質(zhì),其中著重介紹了 α-Stable分布模型的特點(diǎn),并將其作為后續(xù)研究基站空間分布和流量空間分布建模的基本候選模型。之后,論文列舉了幾種衡量模型擬合優(yōu)度的統(tǒng)計(jì)量。本文的主體部分是基于大量現(xiàn)網(wǎng)實(shí)測(cè)數(shù)據(jù),首先發(fā)現(xiàn)了基站空間分布和流量空間分布均具有重尾現(xiàn)象,且α-Stable分布模型可以較好的對(duì)基站空間密度和流量空間密度分別建模。此外,論文中還發(fā)現(xiàn)在不同蜂窩網(wǎng)絡(luò)場(chǎng)景下,基站空間密度與流量空間密度之間均存在線性關(guān)聯(lián)關(guān)系。另一方面,本文還基于大量實(shí)測(cè)數(shù)據(jù)分析了基站與流量時(shí)空分布的其它統(tǒng)計(jì)特征。具體來說,論文提出了“基于密度策略”(Density-basedMeasure)和“基于距離策略”(Distance-based Measure)兩種方法,從數(shù)學(xué)角度量化基站空間分布的聚集程度。之后又分析了流量序列時(shí)間維度上的統(tǒng)計(jì)特點(diǎn),并且又特別討論了不同基站間流量序列模式的空間相關(guān)性現(xiàn)象,給出了具有一定代表性的研究結(jié)果。最后,論文給出文章總結(jié)以及本研究下一步的可能方向。
[Abstract]:In the last ten years, mobile cellular communication has undergone earth-shaking changes, from 2G to 3G, from LTE to the fifth generation mobile communication. With the rapid development of mobile cellular communication technology. With the rapid increase of mobile service types, mobile data traffic also explodes. The mobile cellular network has evolved into a highly isomerized network structure. The spatial topology of the base station and the space-time characteristics of the traffic are very important to the performance evaluation of the network. In this paper, the statistical law of space-time distribution of base stations and traffic in mobile cellular networks is proposed in this paper. Firstly, this paper introduces the mathematical concept and properties of heavy-tailed distribution in typical statistical models. The characteristics of 偽 -Stable distribution model are emphatically introduced, and it is regarded as the basic candidate model of base station spatial distribution and traffic spatial distribution modeling. The main part of this paper is based on a large number of measured data of the existing network. Firstly, it is found that the spatial distribution of base station and the spatial distribution of traffic have the phenomenon of heavy-tailed. And the 偽 -Stable distribution model can model the spatial density and traffic density of the base station respectively. In addition, the paper also found that in different cellular network scenarios. There is a linear correlation between base station spatial density and traffic spatial density. On the other hand, based on a large number of measured data, this paper also analyzes other statistical characteristics of base station and traffic spatial and temporal distribution. In this paper, Density-Based measure and Distance-based measure are proposed. Two ways. From the point of view of mathematics, the aggregation degree of spatial distribution of base stations is quantified. After that, the statistical characteristics of traffic sequence time dimension are analyzed, and the spatial correlation of traffic sequence patterns among different base stations is discussed in particular. Finally, the paper gives the summary of the paper and the possible direction of this research.
【學(xué)位授予單位】：浙江大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TN929.5

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本文編號(hào)：1407289