本文選題：5G　切入點(diǎn)：超密集網(wǎng)絡(luò)　出處：《西南交通大學(xué)》2017年碩士論文

【摘要】：為了滿(mǎn)足數(shù)據(jù)流量井噴式增長(zhǎng)以及用戶(hù)體驗(yàn)速率提高10～100倍的需求,下一代移動(dòng)通信(5G)異構(gòu)網(wǎng)絡(luò)部署將使用超密集網(wǎng)絡(luò)(Ulltra-DenseNetwork,UDN)。超密集網(wǎng)絡(luò)的部署是通過(guò)在原有的異構(gòu)網(wǎng)絡(luò)里增加大量的低功率基站節(jié)點(diǎn)(小小區(qū)Small Cell),包括微蜂窩基站(Microcell)、微微蜂窩基站(Picocell)、毫微微蜂窩基站(Femtocell,又稱(chēng)家庭基站)、端到端節(jié)點(diǎn)(D2D)等。5G系統(tǒng)中節(jié)點(diǎn)的部署密度將超過(guò)現(xiàn)在的10倍以上。雖然超密集網(wǎng)絡(luò)縮小了終端用戶(hù)與節(jié)點(diǎn)基站之間的距離,使得網(wǎng)絡(luò)頻譜效率大幅度提升,系統(tǒng)容量得到擴(kuò)展,但是低功率節(jié)點(diǎn)數(shù)目的劇增,節(jié)點(diǎn)間距離的縮小,越來(lái)越密集的網(wǎng)絡(luò)節(jié)點(diǎn)部署使得網(wǎng)絡(luò)拓?fù)浣Y(jié)構(gòu)更加密集化、異構(gòu)化和復(fù)雜化,這樣就導(dǎo)致干擾環(huán)境更加復(fù)雜化。因此,研究5G異構(gòu)網(wǎng)絡(luò)干擾的建模具有重要意義。傳統(tǒng)的正六邊形網(wǎng)格模型較為固定但并不精確,對(duì)于未來(lái)多層異構(gòu)化的5G超密集網(wǎng)絡(luò)并不適用。對(duì)于這個(gè)問(wèn)題,近幾年比較常用的方法是采用隨機(jī)幾何里的泊松點(diǎn)過(guò)程來(lái)建模網(wǎng)絡(luò)部署,且假設(shè)每一層的基站位置符合相同的點(diǎn)過(guò)程或者使用完全隨機(jī)的泊松點(diǎn)過(guò)程。由于宏蜂窩小區(qū)邊緣區(qū)域(盲區(qū))、宏蜂窩小區(qū)熱點(diǎn)區(qū)域(忙區(qū))以及D2D通信(Device to Device Communication)等特殊區(qū)域中,基站的分布并不是一樣的,且不同場(chǎng)景下用戶(hù)終端的分布也不同,因此,現(xiàn)有簡(jiǎn)單的泊松點(diǎn)過(guò)程模型將不再適用。針對(duì)這個(gè)問(wèn)題,本文針對(duì)不同的場(chǎng)景利用不同的點(diǎn)過(guò)程模型實(shí)現(xiàn)了不同的網(wǎng)絡(luò)模型的模擬,并對(duì)其干擾進(jìn)行了分析。首先,針對(duì)宏小區(qū)邊緣區(qū)域建立了具有層間相關(guān)性(不同類(lèi)型基站間的空間相關(guān)性)的雙層 MPP-PHP(Matern Hard-core Point Processes-Poisson Hole Process)干擾模型。通過(guò)與傳統(tǒng)正六邊形模型和現(xiàn)有簡(jiǎn)單的MPP-PPP(Poisson Point Process)模型進(jìn)行仿真對(duì)比,分析驗(yàn)證了本模型的準(zhǔn)確性和適用性,并仿真分析了該模型的干擾分布和PHP排斥半徑對(duì)系統(tǒng)性能的影響,得到了在本文給定仿真參數(shù)下使系統(tǒng)性能最好的最佳排斥半徑。其次,針對(duì)宏小區(qū)熱點(diǎn)區(qū)域建立了具有層內(nèi)相關(guān)性(同一類(lèi)型基站間的空間相關(guān)性)的雙層MPP-MCP(Matern ClusterProcess)干擾模型。通過(guò)與傳統(tǒng)正六邊形模型和現(xiàn)有簡(jiǎn)單的PPP-MCP模型進(jìn)行仿真對(duì)比分析,驗(yàn)證了本模型的準(zhǔn)確性和適用性,并仿真分析了該模型的干擾分布。最后,針對(duì)D2D場(chǎng)景建立了具有層間相關(guān)性的三層MPP-PHP-PPP干擾模型。與前面所建的雙層MPP-PHP模型進(jìn)行仿真對(duì)比分析,驗(yàn)證了本模型的準(zhǔn)確性,并仿真分析了該模型的干擾分布和D2D對(duì)間距離對(duì)系統(tǒng)性能的影響,得到了在本文給定仿真參數(shù)下D2D對(duì)之間的距離對(duì)系統(tǒng)性能有一定的影響,隨著距離的增大系統(tǒng)性能會(huì)變差,但影響并不是很大的結(jié)論的結(jié)論。
[Abstract]:In order to meet the demand of data flow blowout growth and the increase of user experience rate by 10 to 100 times, Ulltra-DenseNetworkUDNs will be used for deployment of heterogeneous networks in the next generation of mobile communications. The deployment of ultra-dense networks is achieved through the addition of a large number of low-power base station nodes in the original heterogeneous networks (small cell Small cell, including microcellular base stations, microcellular base-stations, microcellular base-stations, microcellular base-stations, microcellular base-stations, microcellular base-stations, microcellular base-stations, and microcellular base-stations). The deployment density of nodes in the microcellular base station / Picocellcell, femto cell (also known as cell base station, end-to-end node / D2D) and other .5G systems will be more than 10 times higher than the present one, although the ultra-dense network reduces the distance between the end user and the node base station. The spectral efficiency of the network is greatly improved and the system capacity is expanded. However, the number of low-power nodes, the reduction of the distance between nodes, and the increasingly dense deployment of network nodes make the network topology more dense. Because of isomerization and complication, the interference environment becomes more complicated. Therefore, it is important to study the modeling of 5G heterogeneous network interference. The traditional hexagonal mesh model is fixed but not accurate. For the future multilayer isomerization of 5G super-dense networks, a more common method in recent years is to model the network deployment by using Poisson point process in random geometry. It is assumed that the base station positions of each layer conform to the same point process or use a completely random Poisson point process. Due to the edge area of the macro cell (blind area, hot spot area of the macro cell) and D2D communication device to Device, the location of the base station in each layer is assumed to be the same. In special areas such as communication, The distribution of base stations is not the same, and the distribution of user terminals is different in different scenarios. Therefore, the existing simple Poisson point process model will no longer be applicable. In this paper, we use different point process models to simulate different network models for different scenes, and analyze their interference. A two-layer MPP-PHP(Matern Hard-core Point Processes-Poisson Hole process interference model with interlayer correlation (spatial correlation between different types of base stations) is established for the edge region of macro cell. The interference model is based on the traditional hexagonal model and the existing simple MPP-PPP(Poisson Point process model. To carry on the simulation contrast, The accuracy and applicability of the model are verified, and the influence of disturbance distribution and PHP repulsion radius on the system performance is analyzed by simulation. The optimal rejection radius is obtained to make the system performance the best under the given simulation parameters. A two-layer MPP-MCP(Matern cluster process interference model with interlayer correlation (spatial correlation between the same type of base stations) is established for hot spots in macro cell. The model is compared with the traditional hexagonal model and the existing simple PPP-MCP model. The accuracy and applicability of the model are verified, and the interference distribution of the model is simulated and analyzed. Finally, a three-layer MPP-PHP-PPP jamming model with interlayer correlation is established for D2D scene. The accuracy of the model is verified, and the influence of the interference distribution of the model and the distance between D2D pairs on the performance of the system is analyzed. It is concluded that the distance between the D2D pairs has a certain effect on the system performance under the given simulation parameters in this paper. With the increase of distance, the performance of the system will become worse, but the effect is not a big conclusion.
【學(xué)位授予單位】：西南交通大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類(lèi)號(hào)】：TN929.5

【參考文獻(xiàn)】

相關(guān)期刊論文 前3條

1 郭蕊;朱賀新;王笑洋;;5G網(wǎng)絡(luò)中D2D通信資源分配的研究現(xiàn)狀[J];北京工業(yè)職業(yè)技術(shù)學(xué)院學(xué)報(bào);2017年01期

2 尼俊紅;申振濤;趙云偉;;部分頻率復(fù)用下的終端直通資源分配方案[J];科學(xué)技術(shù)與工程;2016年30期

3 任承蒙;張劍峰;王聰;謝威;徐友云;;基于類(lèi)Matern點(diǎn)過(guò)程模型的異構(gòu)蜂窩網(wǎng)建模[J];應(yīng)用科學(xué)學(xué)報(bào);2014年05期

，

本文編號(hào)：1674489