移动用户群体聚集行为模型及其高能效资源配置方法
发布时间：2018-07-23 12:16
【摘要】：由于用户社会属性的存在,复杂蜂窝移动网络的业务特征和用户行为在时域、空域和内容等多维度上的分布都呈现出以群体为特征的聚集行为规律.以往静态、孤岛式的网络资源配置方法造成了网络资源的巨大浪费,因此利用用户群体行为特征规律将存在巨大的能效和资源利用提升空间.基于对实际运营的蜂窝移动通信系统中数据的采集和测量,首先从空间、时间等多个维度对用户群体聚集行为进行了深入分析研究,得到了基站流量在空域、时域和空 时联合的分布规律.研究表明,业务在空间符合Log-normal分布,其参数与典型区域类型有关;用户数及其产生的业务量随着时间变化具有明显的规律性,正弦叠加模型能够很好地反映出现网实际业务量的变化情况.其次,通过对空域和时域的联合分析,得到了能精准预测基站业务变化的空 时联合分布模型.与实际数据对比发现,该模型准确度可以达到93%以上.为了更明确地表征用户群体聚集行为,利用经济学中的基尼系数对用户群体聚集行为进行了数学定义和定量描述.最后,基于所提出的业务空 时模型和用户群体行为聚集模型,提出了几种高能效的无线网络资源配置方法、传输控制方法和基站分级休眠策略,探索利用用户群体行为规律提升无线网络能效的新途径.
[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.
【作者单位】： 北京邮电大学泛网无线通信教育部重点实验室;中国电信股份有限公司技术创新中心;
【基金】：国家自然科学基金(批准号:61372114,61631005) 国家重点基础研究计划(973)(批准号:2012CB316005) 北京市科技新星计划(批准号:Z151100000315077)资助项目
【分类号】：TN929.5
，
本文编号：2139388
[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.
【作者单位】： 北京邮电大学泛网无线通信教育部重点实验室;中国电信股份有限公司技术创新中心;
【基金】：国家自然科学基金(批准号:61372114,61631005) 国家重点基础研究计划(973)(批准号:2012CB316005) 北京市科技新星计划(批准号:Z151100000315077)资助项目
【分类号】：TN929.5
，
本文编号：2139388
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