【摘要】：隨著配電自動(dòng)化、用電智能化的發(fā)展和變革,配用電通信網(wǎng)中的業(yè)務(wù)信息正在多元化、數(shù)字化、網(wǎng)絡(luò)化和大信息量化地發(fā)展。蜂窩無(wú)線網(wǎng)絡(luò)憑借著其建設(shè)所需成本相對(duì)較低、施工難度相對(duì)較小、網(wǎng)絡(luò)后續(xù)升級(jí)相對(duì)靈活等特點(diǎn),逐漸成為智能配用電通信網(wǎng)中重要的通信技術(shù)之一,而在無(wú)線通信網(wǎng)大規(guī)模部署和優(yōu)化的過程中,高能耗問題也逐漸成為無(wú)線網(wǎng)絡(luò)需要考慮的核心問題之一。本文分析配用電通信網(wǎng)架構(gòu)和業(yè)務(wù)需求,在建立綠色基站的能耗模型的基礎(chǔ)上,將其融入到配用電無(wú)線通信網(wǎng)的規(guī)劃和優(yōu)化過程中。為了合理部署配用電無(wú)線通信網(wǎng),本文提出了一種適用于配用電通信網(wǎng)的分層異構(gòu)無(wú)線網(wǎng)絡(luò)規(guī)劃方法,該規(guī)劃方法將網(wǎng)絡(luò)基站規(guī)劃中的規(guī)劃因素分為兩種:正相關(guān)因素和負(fù)相關(guān)因素。選擇不同類型的規(guī)劃因素作為基站站址優(yōu)化的目標(biāo),并將不同層的基站統(tǒng)一規(guī)劃考慮,利用多目標(biāo)遺傳算法求解最優(yōu)結(jié)果,從而得出規(guī)劃結(jié)果。該方法考慮到配用電業(yè)務(wù)在異構(gòu)網(wǎng)絡(luò)中的應(yīng)用問題,利用無(wú)線網(wǎng)絡(luò)的重疊覆蓋,保證配用電業(yè)務(wù)能夠自由切換到不同層的接入網(wǎng),從而提高了業(yè)務(wù)的可靠性,同時(shí)有效減少了能耗。為了合理優(yōu)化配用電通信網(wǎng)的覆蓋范圍,本文提出了一種針對(duì)綠色基站的覆蓋優(yōu)化調(diào)整算法。該算法將休眠基站的覆蓋區(qū)域劃分為多個(gè)小區(qū)域塊,利用基站間的協(xié)作覆蓋策略合理分配覆蓋補(bǔ)償?shù)膮^(qū)域。該算法能夠根據(jù)區(qū)域內(nèi)的負(fù)載狀況,在確保業(yè)務(wù)質(zhì)量和覆蓋服務(wù)的前提下實(shí)現(xiàn)最大限度的能量節(jié)省,自適應(yīng)地進(jìn)行能耗最小化的覆蓋優(yōu)化。本文重點(diǎn)在于將能耗作為配用電無(wú)線通信網(wǎng)的規(guī)劃和優(yōu)化過程中的一個(gè)重要因素,建立優(yōu)化模型,求解模型最優(yōu)解,并將結(jié)果的性能和其他算法進(jìn)行對(duì)比,從而驗(yàn)證本文規(guī)劃方法的有效性。
[Abstract]:With the development and reform of distribution automation and intelligent power consumption, the service information in the distribution communication network is developing in a diversified, digital, networked and quantitative way. Cellular wireless network has become one of the important communication technologies in intelligent distribution communication network because of its relatively low construction cost, relatively small construction difficulty, relatively flexible network follow-up upgrade and so on. In the process of large-scale deployment and optimization of wireless communication networks, the problem of high energy consumption has gradually become one of the core issues to be considered in wireless networks. In this paper, the architecture and service requirements of distribution communication network are analyzed. On the basis of establishing the energy consumption model of green base station, it is integrated into the planning and optimization process of distribution power wireless communication network. In order to reasonably deploy the distribution wireless communication network, a hierarchical heterogeneous wireless network planning method is proposed in this paper, which is suitable for the distribution communication network. The planning method divides the planning factors into two kinds: positive correlation factor and negative correlation factor. Different types of planning factors are selected as the target of base station address optimization, and the unified planning of base stations in different layers is considered, and the multi-objective genetic algorithm is used to solve the optimal results, and the planning results are obtained. This method takes into account the application of distribution service in heterogeneous networks, and makes use of the overlapping coverage of wireless networks to ensure that distribution services can freely switch to different layers of access networks, thus improving the reliability of services. At the same time, the energy consumption is reduced effectively. In order to optimize the coverage of distribution communication network, this paper presents an optimal coverage adjustment algorithm for green base stations. In this algorithm, the coverage area of dormant base station is divided into several small area blocks, and the coverage compensation area is allocated reasonably by the cooperative coverage strategy among the base stations. According to the load condition in the region, the algorithm can achieve the maximum energy saving while ensuring the service quality and coverage service, and adaptively optimize the coverage with minimum energy consumption. In this paper, the energy consumption is regarded as an important factor in the planning and optimization of wireless communication network, and the optimization model is established, the optimal solution of the model is solved, and the performance of the result is compared with other algorithms. The effectiveness of the proposed programming method is verified.
【學(xué)位授予單位】：華北電力大學(xué)(北京)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TN929.5;TM73

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本文編號(hào)：2275684