Abstract: Location management is used in mobile communication networks to track mobile terminals (MTs). It has two basic operations: location update and paging. Under existing location management schemes, an entire location area consisting of a lot of cells is paged concurrently to locate an MT, which consumes dramatically networks’ resources, since the MT only resides one of the paged cells. Based on reinforcement learning, multi-stage intelligent paging schemes are proposed, which learns MTs’ location information obtained in previous paging processes and the cells included in each paging stage are dynamically adjusted, so that paging cost is reduced. Simulation results illustrate that the paging cost can be reduced considerably by proposed multi-stage paging schemes.

摘要： 移动通信网络中，位置管理用于跟踪移动台，由位置更新和寻呼两个基本操作。现行位置管理策略在查找移动台时对整个位置区进行同步寻呼，由于位置区由众多小区组成，而移动台只在其中一个小区，所以现行策略造成了网络资源的大量浪费。该文基于增强学习理论与方法，提出了自适应的多阶段智能寻呼策略，通过学习寻呼过程所获得的移动台位置信息，动态调整各阶段所寻呼组的小区，以降低寻呼费用。仿真实验结果表明，所提出的寻呼策略能较大地降低寻呼代价。