本文選題：眾包 + 基站　； 參考：《蘭州理工大學(xué)》2017年碩士論文

【摘要】：信息技術(shù)的持續(xù)進(jìn)步帶動(dòng)了通信服務(wù)和智能手機(jī)的迅速發(fā)展,以無(wú)線(xiàn)方式接入網(wǎng)絡(luò)、功能齊全且便于攜帶的智能手機(jī)已成為人們處理通信、上網(wǎng)、娛樂(lè)和辦公等事務(wù)的首選終端,進(jìn)一步促進(jìn)了移動(dòng)通信的發(fā)展。為了滿(mǎn)足用戶(hù)需求,實(shí)現(xiàn)手機(jī)信號(hào)的無(wú)盲區(qū)覆蓋,移動(dòng)通信運(yùn)營(yíng)商在各地部署了大量的手機(jī)基站。基站數(shù)目增加,隨之而來(lái)的是基站故障的增加以及基站帶寬資源分配不合理。運(yùn)營(yíng)商主要通過(guò)遠(yuǎn)程監(jiān)控、用戶(hù)反饋以及人工巡檢定位的方式來(lái)定位故障基站。但遠(yuǎn)程監(jiān)控只能查看基站硬件的損害,無(wú)法查看出軟件的故障;用戶(hù)反饋的方式描述不詳細(xì);人工巡檢會(huì)增加工作人員工作量,巡檢周期較長(zhǎng)。這些方式均無(wú)法滿(mǎn)足現(xiàn)實(shí)應(yīng)用的需求。運(yùn)營(yíng)商對(duì)基站帶寬分配的方式通常是首先按照經(jīng)驗(yàn)分配,然后根據(jù)用戶(hù)的投訴進(jìn)行調(diào)整。當(dāng)用戶(hù)投訴信息少,覆蓋面不夠?qū)拸V時(shí),會(huì)缺乏對(duì)基站性能的客觀(guān)評(píng)價(jià),此時(shí)運(yùn)營(yíng)商迫切希望能夠掌握基站性能全面且真實(shí)的反饋,盡量減少基站帶寬資源過(guò)�；蛘邘捹Y源不足的情況,真正實(shí)現(xiàn)資源按需分配。因此,如何高效的利用用戶(hù)信息,及時(shí)而又準(zhǔn)確的定位故障基站,客觀(guān)的評(píng)價(jià)基站性能成為通信領(lǐng)域亟需解決的問(wèn)題。本文通過(guò)分析手機(jī)切換基站的原理,提出一種廉價(jià)且高效的基于眾包模式的手機(jī)基站故障診斷方法。該方法以用戶(hù)手機(jī)為數(shù)據(jù)采集工具,通過(guò)數(shù)據(jù)的匯總、對(duì)比與分析,實(shí)現(xiàn)故障基站的定位。仿真實(shí)驗(yàn)表明該方法能夠及時(shí)而又準(zhǔn)確的定位故障基站。同時(shí)本文根據(jù)眾包的特點(diǎn),選擇利用人工神經(jīng)網(wǎng)絡(luò)評(píng)價(jià)法對(duì)基站性能進(jìn)行評(píng)價(jià),結(jié)合用戶(hù)評(píng)價(jià)以及智能手機(jī)采集的數(shù)據(jù)的匯聚分析,對(duì)基站性能進(jìn)行排名。實(shí)驗(yàn)表明該方法可以實(shí)現(xiàn)資源的有效利用,準(zhǔn)確而又客觀(guān)的評(píng)價(jià)基站性能。本文的工作包括以下三個(gè)方面:(1)研究如何利用Android平臺(tái)實(shí)現(xiàn)基站故障診斷與性能評(píng)測(cè)相關(guān)數(shù)據(jù)的采集,其中包括:Android平臺(tái)抓包、網(wǎng)速測(cè)量、Ping功能實(shí)現(xiàn)、網(wǎng)絡(luò)模式判別、基站信息獲取。(2)在運(yùn)營(yíng)商制定的手機(jī)切換基站準(zhǔn)則的基礎(chǔ)上,提出一種定位故障基站的新方法。該方法首先根據(jù)基站分布,利用泰森多邊形將城市劃為若干個(gè)區(qū)域,在基站正常工作的情況下,基站信號(hào)所覆蓋區(qū)域內(nèi)的智能手機(jī)會(huì)自動(dòng)連接該基站。一旦基站發(fā)生故障,智能手機(jī)會(huì)自動(dòng)連接覆蓋該區(qū)域的其他基站,通過(guò)記錄這些用戶(hù)的數(shù)據(jù)即可獲取故障基站的位置。(3)分析眾包的特點(diǎn),將人工神經(jīng)網(wǎng)絡(luò)算法應(yīng)用到基站性能評(píng)估中。首先利用智能手機(jī)采集一些能夠反映網(wǎng)絡(luò)性能的數(shù)據(jù),同時(shí)記錄對(duì)應(yīng)的用戶(hù)評(píng)分,然后采用人工神經(jīng)網(wǎng)絡(luò)模型訓(xùn)練該數(shù)據(jù),根據(jù)再次采集的網(wǎng)絡(luò)性能數(shù)據(jù),預(yù)測(cè)出用戶(hù)評(píng)分。最后通過(guò)采集得到的用戶(hù)評(píng)分以及預(yù)測(cè)得到的用戶(hù)評(píng)分對(duì)基站性能進(jìn)行綜合評(píng)價(jià)。最后,通過(guò)仿真實(shí)驗(yàn)驗(yàn)證了本文所提定位故障基站方法的可行性,以及實(shí)驗(yàn)表明利用人工神經(jīng)網(wǎng)絡(luò)對(duì)基站性能評(píng)價(jià)具有良好的實(shí)用性。
[Abstract]:Continuous improvement of information technology led to the rapid development of communication services and intelligent mobile phone, with wireless access network, intelligent mobile phone functions and portability has become people to deal with communication, Internet, preferred terminal entertainment and office affairs, to further promote the development of mobile communication. In order to meet the needs of users, to achieve non blind mobile phone signal coverage, mobile communication operators to deploy a large number of mobile phone base stations around the world. The number of base stations increased, followed by a base station fault and the increase of base station bandwidth resource allocation is not reasonable. Operators mainly through remote monitoring, user feedback and manual inspection positioning to locate the fault. But the base station remote monitoring base station hardware can only view the damage to look for software fault; user feedback is described in detail; the manual inspection work will increase the workload, patrol Check the cycle longer. These methods are unable to meet the needs of practical application. Operators of the base station bandwidth allocation method is usually the first according to the empirical distribution, then adjusted according to user complaints. When the user complaints less information, the coverage is not wide enough, the lack of objective evaluation of the base station, the operators are eager to master station performance feedback comprehensive and true, as far as possible to reduce the base excess bandwidth resources or insufficient bandwidth resources, realize resource allocation on demand. Therefore, how to efficiently use the user information, timely and accurate fault location of base station, the base station performance evaluation become the field of communication problems objectively. By analyzing the principle of mobile phone base station switching, provides a cheap and efficient mobile phone base station fault diagnosis method based on Crowdsourcing model. The method to user machine The data collection tool, through data collection, comparison and analysis, realize the fault location of the base station. The simulation shows that this method can locate the fault station timely and accurate. At the same time, according to the characteristics of Crowdsourcing, choose to use artificial neural network evaluation method to evaluate the performance of the base station, combined with the analysis of user evaluation and acquisition of intelligent mobile phone together the data, to rank the performance of the base station. The effective use of experiment shows that this method can realize the resources, evaluation of the performance of the base station accurately and objectively. The work of this paper includes the following three aspects: (1) research on how to realize the base station fault diagnosis and performance evaluation of data acquisition, using Android platform Android platform capture, including: speed measurement, Ping function realization, network mode discrimination, base station information. (2) based on the criterion of mobile phone base station switching operators to develop on the. A new method for fault location of base station. Firstly, according to the base station distribution, using Tyson polygons will be divided into several areas of the city, at the base station under normal working conditions, the base station signal coverage area of the intelligent mobile phone will automatically connect to the base station. The base station once a fault occurs, the intelligent mobile phone will automatically connect to other base station coverage the area of the base station through acquiring fault record these user data can be located. (3) analysis of the characteristics of Crowdsourcing, the application of artificial neural network algorithm to the base station performance evaluation. First use of intelligent mobile phone collection can reflect the network performance data recorded at the same time, the corresponding user score, then using the artificial neural network model the training data, according to the network performance data collected again, predict user scores. Finally, by collecting the user score and predicted user The performance of the base station is evaluated comprehensively. Finally, the feasibility of the proposed location based fault base station method is verified by simulation experiments, and experiments show that the artificial neural network has good practicability for the base station performance evaluation.

【學(xué)位授予單位】：蘭州理工大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類(lèi)號(hào)】：TN929.5;TP183

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