多目标的跟踪区域列表动态优化算法  

A dynamic optimization algorithm for multi⁃target tracking area lists

作　　者：陈发堂[1] 韩才君 张航 CHEN Fatang;HAN Caijun;ZHANG Hang(School of Communication and Information Engineering,Chongqing University of Posts and Telecommunications,Chongqing 400065,China)

机构地区：[1]重庆邮电大学通信与信息工程学院,重庆400065

出　　处：《南京邮电大学学报（自然科学版）》2023年第2期27-35,共9页Journal of Nanjing University of Posts and Telecommunications：Natural Science Edition

基　　金：教育部-中国移动科研基金(MCM201805-2)资助项目。

摘　　要：5G移动网络要适应多样化和不断增加的用户设备(User Equipment, UE),应对终端巨大的位置管理信令开销是实现这一目标的重要保障。文中提出了一种多目标算法优化跟踪区域列表(Tracking area List, TAL)的策略,目的是寻找TAL中跟踪区(Tracking Area, TA)的最优分布以及如何将TAL分配给UE,以最小化位置管理中冲突的跟踪区更新(Tracking area update, TAU)和寻呼信令开销。在本地侧利用多目标粒子群优化算法实现TAL的最优分布,网络侧根据不同UE的移动特性来分配大小合适的TAL。通过仿真验证,所提方案可以在TAU和寻呼开销之间取得妥协,并在节省总位置管理开销方面得到了大幅度改善。5G mobile networks need to adapt to the diversification and the increasing user equipments(UE),and dealing with the huge location management signaling overhead of terminals can guarantee this goal.In this paper,a multi⁃objective algorithm is proposed to optimize the tracking area list(TAL).This algorithm is to find the optimal distribution of the tracking area(TA)in TAL and the way to assign TAL to UE.Thus,the conflicting tracking area update(TAU)and paging signaling overhead in location management can be minimized.The multi⁃objective particle swarm optimization algorithm is used on the local side to achieve the optimal distribution of TALs,and TALs with appropriate sizes are allocated on the network side according to the mobility characteristics of different UEs.The simulation demonstrates that the proposed scheme can balance between TAU and the paging overhead,and the performance is greatly improved in terms of saving total location management overhead.

关 键 词：位置管理 位置更新和寻呼 跟踪区域列表 多目标粒子群优化 马尔科夫链 

分 类 号：TN929.53[电子电信—通信与信息系统]