【摘要】：由于用戶社會(huì)屬性的存在,復(fù)雜蜂窩移動(dòng)網(wǎng)絡(luò)的業(yè)務(wù)特征和用戶行為在時(shí)域、空域和內(nèi)容等多維度上的分布都呈現(xiàn)出以群體為特征的聚集行為規(guī)律.以往靜態(tài)、孤島式的網(wǎng)絡(luò)資源配置方法造成了網(wǎng)絡(luò)資源的巨大浪費(fèi),因此利用用戶群體行為特征規(guī)律將存在巨大的能效和資源利用提升空間.基于對(duì)實(shí)際運(yùn)營的蜂窩移動(dòng)通信系統(tǒng)中數(shù)據(jù)的采集和測(cè)量,首先從空間、時(shí)間等多個(gè)維度對(duì)用戶群體聚集行為進(jìn)行了深入分析研究,得到了基站流量在空域、時(shí)域和空 時(shí)聯(lián)合的分布規(guī)律.研究表明,業(yè)務(wù)在空間符合Log-normal分布,其參數(shù)與典型區(qū)域類型有關(guān);用戶數(shù)及其產(chǎn)生的業(yè)務(wù)量隨著時(shí)間變化具有明顯的規(guī)律性,正弦疊加模型能夠很好地反映出現(xiàn)網(wǎng)實(shí)際業(yè)務(wù)量的變化情況.其次,通過對(duì)空域和時(shí)域的聯(lián)合分析,得到了能精準(zhǔn)預(yù)測(cè)基站業(yè)務(wù)變化的空 時(shí)聯(lián)合分布模型.與實(shí)際數(shù)據(jù)對(duì)比發(fā)現(xiàn),該模型準(zhǔn)確度可以達(dá)到93%以上.為了更明確地表征用戶群體聚集行為,利用經(jīng)濟(jì)學(xué)中的基尼系數(shù)對(duì)用戶群體聚集行為進(jìn)行了數(shù)學(xué)定義和定量描述.最后,基于所提出的業(yè)務(wù)空 時(shí)模型和用戶群體行為聚集模型,提出了幾種高能效的無線網(wǎng)絡(luò)資源配置方法、傳輸控制方法和基站分級(jí)休眠策略,探索利用用戶群體行為規(guī)律提升無線網(wǎng)絡(luò)能效的新途徑.
[Abstract]:Due to the existence of social attributes of users, the traffic characteristics and user behavior of complex cellular mobile networks are distributed in time domain, spatial domain and content. In the past, the static and isolated network resource allocation method caused a huge waste of network resources, so there will be huge energy efficiency and resource utilization improvement space by using the behavior characteristics of user groups. Based on the collection and measurement of the data in the actual mobile cellular communication system, the aggregation behavior of the user group is analyzed from the space, time and other dimensions, and the traffic of the base station in the airspace is obtained. The distribution law of time domain and space-time joint. The research shows that the service conforms to the Log-normal distribution in space, and its parameters are related to the typical regional type, and the number of users and the amount of business generated have obvious regularity with time. The sinusoidal superposition model can well reflect the change of actual network traffic. Secondly, through the joint analysis of spatial domain and time domain, a joint space-time distribution model which can accurately predict the change of base station traffic is obtained. Compared with the actual data, the accuracy of the model is over 93%. In order to express the aggregation behavior of user group more clearly, the Gini coefficient in economics is used to define and quantitatively describe the aggregation behavior of user group. Finally, based on the proposed space-time model and user group behavior aggregation model, several efficient wireless network resource allocation methods, transmission control methods and base station hierarchical sleep strategy are proposed. To explore a new way to improve wireless network energy efficiency by using user group behavior rules.
【作者單位】： 北京郵電大學(xué)泛網(wǎng)無線通信教育部重點(diǎn)實(shí)驗(yàn)室;中國電信股份有限公司技術(shù)創(chuàng)新中心;
【基金】：國家自然科學(xué)基金(批準(zhǔn)號(hào):61372114,61631005) 國家重點(diǎn)基礎(chǔ)研究計(jì)劃(973)(批準(zhǔn)號(hào):2012CB316005) 北京市科技新星計(jì)劃(批準(zhǔn)號(hào):Z151100000315077)資助項(xiàng)目
【分類號(hào)】：TN929.5
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本文編號(hào)：2139388