本文關(guān)鍵詞： TD-LTE網(wǎng)絡(luò) 故障診斷 BP神經(jīng)網(wǎng)絡(luò) 診斷系統(tǒng)　出處：《寧波大學(xué)》2014年碩士論文　論文類型：學(xué)位論文

【摘要】：TD-LTE（Time Division Long TermEvaluation）網(wǎng)絡(luò)是TD模式的3G長期演進(jìn)型網(wǎng)絡(luò)，是由中國主導(dǎo)的新一代移動(dòng)通信網(wǎng)絡(luò)。與3G網(wǎng)絡(luò)相比，它有著更高的上下行峰值速率，更高效的頻譜資源利用率，更低的系統(tǒng)延時(shí)，在網(wǎng)絡(luò)性能上有了質(zhì)的提升，給用戶帶來了更好的體驗(yàn)感。但同時(shí)，一旦網(wǎng)絡(luò)出現(xiàn)故障將會(huì)給用戶帶來更為明顯的影響，這就要求網(wǎng)絡(luò)運(yùn)營商在網(wǎng)絡(luò)出現(xiàn)故障時(shí)，能夠快速有效的解決網(wǎng)絡(luò)故障，迅速優(yōu)化網(wǎng)絡(luò)性能。而傳統(tǒng)的故障診斷方法，其工作量大，診斷周期較長，很難實(shí)現(xiàn)故障的快速診斷。因此，研究快速、智能化的TD-LTE網(wǎng)絡(luò)故障診斷技術(shù)就顯得很有必要了。 作為人工智能技術(shù)之一的神經(jīng)網(wǎng)絡(luò)，它有著很強(qiáng)的非線性處理能力，是目前實(shí)現(xiàn)復(fù)雜系統(tǒng)故障診斷智能化的一種常用技術(shù)。本文將神經(jīng)網(wǎng)絡(luò)技術(shù)引入到TD-LTE網(wǎng)絡(luò)的故障診斷當(dāng)中，研究了基于神經(jīng)網(wǎng)絡(luò)的TD-LTE網(wǎng)絡(luò)故障診斷技術(shù)。研究工作和主要內(nèi)容分為以下幾個(gè)方面： 1.對(duì)TD-LTE網(wǎng)絡(luò)及常見的一些智能故障診斷方法進(jìn)行了介紹。 2.對(duì)BP神經(jīng)網(wǎng)絡(luò)基本理論和方法進(jìn)行了介紹和分析，在此基礎(chǔ)上結(jié)合網(wǎng)絡(luò)KPI數(shù)據(jù)的特點(diǎn)，提出了基于KPI統(tǒng)計(jì)分布偏離度的BP神經(jīng)網(wǎng)絡(luò)故障診斷方法。該方法首先采集診斷所需KPI的正常歷史數(shù)據(jù)，統(tǒng)計(jì)得到KPI的經(jīng)驗(yàn)分布，通過KPI屬性學(xué)習(xí)算法，生成KPI的屬性集。然后對(duì)網(wǎng)絡(luò)當(dāng)前的KPI數(shù)據(jù)進(jìn)行監(jiān)測，通過異常檢測方法，檢測KPI的異常情況。在KPI出現(xiàn)異常的狀況下，調(diào)用訓(xùn)練好的BP神經(jīng)網(wǎng)絡(luò)進(jìn)行故障診斷，給出診斷結(jié)果。最后通過仿真實(shí)驗(yàn)證明了該方法的可行性和有效性。 3.分析和設(shè)計(jì)了基于上述診斷方法的TD-LTE網(wǎng)絡(luò)故障診斷系統(tǒng)，并通過C#技術(shù)和SQLServer2008數(shù)據(jù)庫實(shí)現(xiàn)了該系統(tǒng)。測試結(jié)果表明該系統(tǒng)可以實(shí)現(xiàn)網(wǎng)絡(luò)故障的快速化、智能化診斷，驗(yàn)證了方案的可行性和可實(shí)現(xiàn)性，同時(shí)也進(jìn)一步驗(yàn)證了本文提出的故障診斷方法的可行性和有效性。
[Abstract]:The TD-LTE(Time Division Long term value) network is a 3G long-evolving network based on TD mode. It is a new generation of mobile communication network dominated by China. Compared with 3G network, it has higher peak and downlink rate, more efficient spectrum resource efficiency and lower system delay. In the network performance has the qualitative enhancement, has brought the better experience feeling to the user, but at the same time, once the network has the breakdown will bring to the user more obvious influence. This requires network operators to solve the network failures quickly and effectively, and optimize the network performance quickly. However, the traditional fault diagnosis method has a large workload and a long diagnosis period. It is difficult to realize the fast fault diagnosis, so it is necessary to study the fast and intelligent TD-LTE network fault diagnosis technology. As one of artificial intelligence technology, neural network has strong nonlinear processing ability. It is a common technology to realize intelligent fault diagnosis of complex system. In this paper, neural network technology is introduced into fault diagnosis of TD-LTE network. The TD-LTE network fault diagnosis technology based on neural network is studied. The research work and main contents are divided into the following aspects: 1. The TD-LTE network and some common intelligent fault diagnosis methods are introduced. 2. The basic theory and method of BP neural network are introduced and analyzed, and the characteristics of network KPI data are combined. A BP neural network fault diagnosis method based on the deviation degree of KPI statistical distribution is proposed. Firstly, the normal historical data of KPI for diagnosis are collected and the empirical distribution of KPI is obtained statistically. The KPI attribute learning algorithm is used to generate the attribute set of KPI. Then the current KPI data of the network are monitored and the method of anomaly detection is used. The abnormal condition of KPI is detected. In the case of abnormal KPI, the trained BP neural network is called for fault diagnosis. Finally, the feasibility and effectiveness of the method are proved by simulation experiments. 3. The TD-LTE network fault diagnosis system based on the above diagnosis method is analyzed and designed. The system is realized by C # technology and SQLServer2008 database. The test results show that the system can realize the rapid and intelligent diagnosis of network faults. The feasibility and realizability of the proposed scheme are verified, and the feasibility and effectiveness of the proposed fault diagnosis method are further verified.
【學(xué)位授予單位】：寧波大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：TN929.5

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