【摘要】：數(shù)據(jù)業(yè)務(wù)需求的爆發(fā)式增長(zhǎng)使超密集無(wú)線網(wǎng)絡(luò)成為研究熱點(diǎn)。根據(jù)網(wǎng)絡(luò)中內(nèi)容受歡迎的程度即流行度將熱點(diǎn)內(nèi)容進(jìn)行緩存,將通信、計(jì)算、存儲(chǔ)多維資源進(jìn)行聯(lián)合優(yōu)化,是超密集網(wǎng)絡(luò)研究的新方向。在超密集部署網(wǎng)絡(luò)中,將小蜂窩的基站按照地域位置和信號(hào)強(qiáng)度等條件進(jìn)行分簇,如何分簇對(duì)超密集網(wǎng)絡(luò)的切換次數(shù)和吞吐量將產(chǎn)生很大的影響,這是超密集研究的另一研究熱點(diǎn)。本論文在介紹了超密集無(wú)線網(wǎng)絡(luò)體系架構(gòu)與關(guān)鍵技術(shù)的基礎(chǔ)上,主要研究了以下三個(gè)方面的內(nèi)容:(1)提出在超密集網(wǎng)絡(luò)中將通信、計(jì)算、存儲(chǔ)多維資源進(jìn)行聯(lián)合優(yōu)化的體系架構(gòu),利用分布式存儲(chǔ),使熱點(diǎn)內(nèi)容更接近用戶,同時(shí)減少網(wǎng)絡(luò)的通信量;(2)提出了一種超密集無(wú)線網(wǎng)絡(luò)基于內(nèi)容緩存的能效優(yōu)化方法,能夠幫助一部分節(jié)點(diǎn)和用戶從中繼節(jié)點(diǎn)基站分流流量,從而降低能耗。仿真結(jié)果表明,與隨機(jī)緩存方案相比,所提出的基于內(nèi)容緩存的能效優(yōu)化方法在能效和內(nèi)容訪問命中率方面都具有良好的性能;(3)在超密集無(wú)線網(wǎng)絡(luò)中,基于馬爾科夫模型對(duì)移動(dòng)終端在超密集分簇網(wǎng)絡(luò)下的移動(dòng)狀態(tài)進(jìn)行建模。仿真結(jié)果表明該方法可以有效提高網(wǎng)絡(luò)系統(tǒng)的吞吐量;同時(shí),在合理設(shè)計(jì)參數(shù)情況下也可以降低系統(tǒng)的阻塞概率。最后,對(duì)本論文進(jìn)行概括總結(jié),并對(duì)下一步工作的研究方向和思路進(jìn)行了展望。
[Abstract]:The explosive growth of data service demand makes the ultra-dense wireless network become a research hotspot. According to the popularity of the content in the network, it is a new direction to cache the hot content and to optimize the communication, computation and storage of multi-dimensional resources. In ultra-dense deployment networks, the base stations of small cells are clustered according to the conditions of location and signal strength. How to cluster will have a great impact on the handover times and throughput of the super-dense networks. This is another hot spot in super-intensive research. Based on the introduction of the architecture and key technologies of the ultra-dense wireless network, this paper mainly studies the following three aspects: (1) the architecture of the communication, computing and storage of multi-dimensional resources in the ultra-dense network is proposed. Distributed storage is used to make hot content closer to users, while reducing network traffic. (2) an energy efficiency optimization method based on content cache is proposed for ultra-dense wireless networks. It can help some nodes and users to divert traffic from the relay node base station, thus reducing energy consumption. Simulation results show that the proposed energy efficiency optimization method based on content cache has good performance in terms of energy efficiency and content access hit rate compared with random cache scheme. (3) in ultra-dense wireless networks, Based on Markov model, the mobile state of mobile terminal in super dense clustering network is modeled. The simulation results show that the proposed method can effectively improve the throughput of the network system and reduce the blocking probability of the system under the condition of reasonable design parameters. Finally, the thesis is summarized, and the research direction and thought of the next work are prospected.
【學(xué)位授予單位】：南京郵電大學(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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