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

【摘要】：為了滿足數(shù)據(jù)流量井噴式增長以及用戶體驗速率提高10～100倍的需求,下一代移動通信(5G)異構(gòu)網(wǎng)絡部署將使用超密集網(wǎng)絡(Ulltra-DenseNetwork,UDN)。超密集網(wǎng)絡的部署是通過在原有的異構(gòu)網(wǎng)絡里增加大量的低功率基站節(jié)點(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,又稱家庭基站)、端到端節(jié)點(D2D)等。5G系統(tǒng)中節(jié)點的部署密度將超過現(xiàn)在的10倍以上。雖然超密集網(wǎng)絡縮小了終端用戶與節(jié)點基站之間的距離,使得網(wǎng)絡頻譜效率大幅度提升,系統(tǒng)容量得到擴展,但是低功率節(jié)點數(shù)目的劇增,節(jié)點間距離的縮小,越來越密集的網(wǎng)絡節(jié)點部署使得網(wǎng)絡拓撲結(jié)構(gòu)更加密集化、異構(gòu)化和復雜化,這樣就導致干擾環(huán)境更加復雜化。因此,研究5G異構(gòu)網(wǎng)絡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,對于未來多層異構(gòu)化的5G超密集網(wǎng)絡并不適用。對于這個問題,近幾年比較常用的方法是采用隨機幾何里的泊松點過程來建模網(wǎng)絡部署,且假設每一層的基站位置符合相同的點過程或者使用完全隨機的泊松點過程。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,且不同場景下用戶終端的分布也不同,因此,現(xiàn)有簡單的泊松點過程模型將不再適用。針對這個問題,本文針對不同的場景利用不同的點過程模型實現(xiàn)了不同的網(wǎng)絡模型的模擬,并對其干擾進行了分析。首先,針對宏小區(qū)邊緣區(qū)域建立了具有層間相關(guān)性(不同類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。通過與傳統(tǒng)正六邊形模型和現(xiàn)有簡單的MPP-PPP(Poisson Point Process)模型進行仿真對比,分析驗證了本模型的準確性和適用性,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,針對宏小區(qū)熱點區(qū)域建立了具有層內(nèi)相關(guān)性(同一類型基站間的空間相關(guān)性)的雙層MPP-MCP(Matern ClusterProcess)干擾模型。通過與傳統(tǒng)正六邊形模型和現(xiàn)有簡單的PPP-MCP模型進行仿真對比分析,驗證了本模型的準確性和適用性,并仿真分析了該模型的干擾分布。最后,針對D2D場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模型進行仿真對比分析,驗證了本模型的準確性,并仿真分析了該模型的干擾分布和D2D對間距離對系統(tǒng)性能的影響,得到了在本文給定仿真參數(shù)下D2D對之間的距離對系統(tǒng)性能有一定的影響,隨著距離的增大系統(tǒng)性能會變差,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.
【學位授予單位】：西南交通大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：TN929.5

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本文編號：1674489