【摘要】：移動通信技術(shù)發(fā)展日新月異,人們在享受3G網(wǎng)絡帶來的便捷的同時,也察覺到了 3G網(wǎng)絡的弊端,如某些區(qū)域3G信號不強或者存在干擾等,這都會嚴重影響用戶的3G體驗。目前國內(nèi)各大通信運營商對基站站點規(guī)劃與工程參數(shù)設置主要采用的是工程師的主觀判斷、現(xiàn)網(wǎng)試錯、復測驗證的模式,這種模式在后期需要大量的優(yōu)化調(diào)整工作,而優(yōu)化調(diào)整工作主要依靠人工經(jīng)驗多次嘗試,缺乏精確性;在網(wǎng)絡覆蓋評估方面,采用傳統(tǒng)的經(jīng)驗型方式進行覆蓋優(yōu)化,這種手段無法準確定位問題,需要進行大量路測來對通信網(wǎng)絡進行評估,并且對網(wǎng)絡性能排查大部分都是被動觸發(fā),事后檢查。本文設計開發(fā)了一個網(wǎng)絡規(guī)劃網(wǎng)絡優(yōu)化系統(tǒng),該系統(tǒng)基于射線跟蹤模型對復雜室內(nèi)以及城區(qū)環(huán)境下基站天線功率覆蓋分析預測,從而真實準確地獲得基站天線的覆蓋范圍,該系統(tǒng)克服了以往利用經(jīng)驗模型進行基站天線覆蓋范圍預測準確性差的缺點,從而為后續(xù)的鄰區(qū)規(guī)劃和頻點規(guī)劃的準確性提供有效保證。在鄰區(qū)規(guī)劃方面,本文提出一種基于天線功率覆蓋結(jié)果的鄰區(qū)列表解算算法,該算法能夠準確有效地為不同覆蓋范圍的基站天線解算出其鄰區(qū)列表,從而解決了現(xiàn)有鄰區(qū)規(guī)劃方案準確性不夠以及引起的功率消耗過大問題,通過福建移動提供的三明地區(qū)的實測數(shù)據(jù)驗證了該算法的準確性與可行性。在頻點規(guī)劃方面,本文提出一種基于染色算法的頻點規(guī)劃算法,該算法能準確有效地對不同規(guī)模下的鄰區(qū)列表進行頻點規(guī)劃,為通信網(wǎng)絡中各個小區(qū)分配與其所有鄰區(qū)不同的頻點,從而避免小區(qū)與其鄰區(qū)之間的干擾,該算法彌補了現(xiàn)有的頻點方案中的準確性差以及頻點浪費問題。在網(wǎng)絡優(yōu)化方面,本文設計的覆蓋盲區(qū)優(yōu)化方案支持修改基站天線參數(shù)和添加基站天線兩種方式來進行覆蓋盲區(qū)優(yōu)化,對福建三明地區(qū)的覆蓋盲區(qū)優(yōu)化結(jié)果顯示場景優(yōu)化之前場景中大于-90dBm的覆蓋面積是98.49%,優(yōu)化之后場景中大于-90dBm的覆蓋面積是99.07%。
[Abstract]:With the rapid development of mobile communication technology, people not only enjoy the convenience brought by 3G network, but also notice the disadvantages of 3G network, such as weak 3G signals or interference in some regions, which will seriously affect the 3G experience of users. At present, the major communication operators in China mainly use the subjective judgment of engineers, the trial and error mode of the present network, the re-test and verification mode for the base station site planning and engineering parameter setting. This mode needs a lot of optimization and adjustment work in the later stage. But the optimization adjustment work mainly depends on the artificial experience many times attempts, lacks the accuracy; In the aspect of network coverage evaluation, the traditional empirical method is used to optimize the coverage. This method can not locate the problem accurately, and a large number of road measurements are needed to evaluate the communication network. And the network performance check is mostly passive trigger, post-check. A network planning network optimization system is designed and developed in this paper. Based on the ray tracing model, the power coverage of base station antenna in complex indoor and urban environment is analyzed and forecasted, so that the coverage range of base station antenna can be obtained truthfully and accurately. The system overcomes the shortcoming of using the empirical model to predict the coverage of base station antenna, which provides an effective guarantee for the accuracy of the subsequent neighborhood planning and frequency planning. In the aspect of neighborhood planning, a neighborhood list algorithm based on antenna power coverage results is proposed in this paper. This algorithm can accurately and effectively solve the neighbor list of base station antenna with different coverage range. Therefore, the problems of poor accuracy and excessive power consumption caused by the existing planning schemes in adjacent areas are solved. The accuracy and feasibility of the algorithm are verified by the measured data in Sanming area provided by Fujian Mobile. In the aspect of frequency point planning, this paper presents a frequency point planning algorithm based on coloring algorithm. Each cell in the communication network is assigned different frequency points from all its neighbors, thus avoiding the interference between the cell and its adjacent area. The algorithm makes up for the accuracy difference and frequency waste problems in the existing frequency point scheme. In the aspect of network optimization, the blind area optimization scheme designed in this paper supports to modify the base station antenna parameters and add base station antenna to optimize the coverage blind area. The result of blind area optimization in Sanming area of Fujian shows that the coverage area of the scene larger than-90dBm is 98.49 before the scene optimization, and the coverage area of the scene larger than-90dBm after the optimization is 99.07.
【學位授予單位】：哈爾濱工程大學
【學位級別】：碩士
【學位授予年份】：2014
【分類號】：TN929.53

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