LTE自优化网络关键技术研究

发布时间：2018-06-21 19:58

本文选题：LTE + 自优化网络　；参考：《华南理工大学》2014年博士论文

【摘要】：3GPP长期演进（LTE）是目前无线通信领域发展的主流技术。在LTE网络系统中，自组织网络（SON）技术是标准化研究工作的重要内容，它被认为是未来管理和维护复杂的移动通信网络，并能有效支撑异构多制式系统、提高网络性能、降低运营成本的有效途径，因此，有关的研究近年来受到了学术界及工业界的广泛关注。 SON的主要目的是实现无线网络的自主完善功能，能有效减少人工参与，降低运营成本。SON的功能主要体现在自配置、自优化、自愈合三个方面。移动鲁棒性优化（MRO）和移动负载均衡（MLB）是自优化中的两个关键的技术。MRO主要用于解决小区内用户设备（UE）的切换问题，保证用户的服务质量；而MLB主要用于解决小区之间负载不均衡问题，提高网络的资源利用率，可以有效地提升热点地区的网络容量。因此，对上述两个技术的理论研究，对于指导实际系统优化网络服务质量、提高网络资源利用率和降低网络运营成本具有重要意义。本论文以无线自优化网络作为研究背景，对MLB与MRO之间的矛盾冲突解决策略、MLB算法设计进行研究。本论文主要的创新成果简介如下： 1、提出一种基于最优化理论的MRO与MLB间冲突避免策略。考虑用户在特定的时间间隔内接收信号强度变化量，对不同用户动态调整切换范围，并对MLB问题进行数学建模，基于最优化理论设计MLB的目标优化函数，将MRO允许的切换参数取值范围作为约束条件，求得调整切换参数的调整区间。此外，考虑小区的负载分布情况，求得切换参数的合理调整值。仿真表明，较之现有的方法，所提的方案不仅能避免MRO与MLB间的冲突发生，而且能更有效的均衡小区间负载，提高网络的各项性能指标。 2、小区间动态负载均衡算法的优劣对网络性能有很大的影响，现有的算法大都顾此失彼，难以保证网络的关键性能指标（如呼叫阻塞率等）达到最佳。为了解决这个问题，本文将负载均衡问题建模为多目标优化问题，，以小区的可用资源数和用户的服务质量要求作为约束条件，对不同服务质量要求的用户分别建模其相应的目标优化函数，对有服务质量要求用户，其目标函数是负载均衡指示函数和网络平均负载函数的联合优化函数，而对没有服务质量要求用户（BE用户），其目标函数是所有BE用户吞吐量的总效用函数。另外，考虑到在实际系统中运行的计算复杂度问题，本文同时给出了一种复杂度较低的启发式算法。仿真结果验证了所提算法的有效性。 3、已有的文献在研究负载均衡算法时，优化目标一般是最大限度的均衡小区间负载，而忽略了网络关键性能指标（KPI），优化后网络的负载均衡指示函数虽然可达到最优，但网络的KPI却不理想，而在实际系统中，KPI才是最重要的参数指标。本文提出了一种以网络的KPI作为负载均衡优化目标的算法，对网络的负载均衡目标是最小化网络的呼叫掉话阻塞率（CDBR），并将小区的可用资源数和用户的服务质量要求作为约束条件。考虑到降低算法的计算复杂度，同时提出了一种分布式负载均衡算法。同样，通过仿真验证了所提算法的有效性。
[Abstract]:3GPP Long Term Evolution ( LTE ) is the mainstream technology in the field of wireless communication . In the LTE network system , self organizing network ( SON ) technology is an important part of standardization research work . It is regarded as an effective way to manage and maintain a complex mobile communication network in the future , and can effectively support the heterogeneous multi - system system , improve the network performance and reduce the operating cost .

The main purpose of SON is to realize the function of self - improvement of wireless network , reduce the labor cost effectively and reduce the operating cost . The function of SON is mainly embodied in the three aspects of self - configuration , self - optimization and self - healing . Mobile robustness optimization ( MRO ) and mobile load balancing ( MLB ) are two key technologies in self - optimization . MRO is mainly used to solve the handover problem of user equipment ( UE ) in the cell area and guarantee the service quality of users ;
and MLB is mainly used for solving the problem of load imbalance between cells , improving the resource utilization rate of the network , effectively improving the network capacity of the hot spot area , and therefore , the theoretical research on the two technologies is of great significance to guide the actual system to optimize the network service quality , improve the network resource utilization rate and reduce the network operation cost .

Taking the wireless self - optimization network as the research background , this paper studies the conflict resolution strategy and MLB algorithm design between MLB and MRO . The main innovations of this paper are as follows :

1 . Based on the optimization theory , the conflict avoidance strategy between MRO and MLB is proposed . In consideration of user ' s received signal strength change amount in certain time interval , the range of switching parameters is dynamically adjusted for different users . Based on the optimization theory , the target optimization function of MLB is designed , and the reasonable adjustment value of the switching parameter is obtained . The simulation shows that the proposed scheme not only can avoid the conflict between MRO and MLB , but also can balance the small interval load more effectively , and improve the performance indexes of the network .

In order to solve the problem , the load balance problem is modeled as a multi - objective optimization problem . In order to solve this problem , the load balance problem is modeled as a multi - objective optimization problem . In order to solve this problem , the load balance problem is modeled as a joint optimization function of the load balance indication function and the network average load function .

3 . When the load balancing algorithm is studied , the optimization goal is usually the maximum balance inter - interval load , but the key performance index ( KPI ) of the network is ignored , but the KPI of the network is not ideal . In the actual system , the KPI is the most important parameter index . In the actual system , the KPI of the network is the most important parameter index . In this paper , a distributed load balancing algorithm is proposed to minimize the computational complexity of the network , and the effectiveness of the proposed algorithm is verified by simulation .
【学位授予单位】：华南理工大学
【学位级别】：博士
【学位授予年份】：2014
【分类号】：TN929.5

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