异构网络中基于轨迹预测的资源预分配方案

Pre-allocation of resources based on trajectory prediction in heterogeneous networks

针对轨迹预测的网络资源管理方法研究中普遍存在的轨迹特征学习不充分、轨迹预测结果精度低、颗粒粗单等问题,提出双向循环神经网络的轨迹预测算法。通过深度挖掘用户的移动规律,实现对用户的移动预测。根据用户的移动预测信息设计网络资源预分配方案、移动行为划分网络资源,实现对多小区的协作式资源优化管理。仿真试验结果表明,在轨迹预测问题中,双向循环神经网络的轨迹预测算法比普通神经网络算法有更好的综合性能。在网络资源管理中,轨迹预测的网络资源管理预分配方案能够较准确地预测用户所连接的基站,使基站具有较高的资源利用率。

Aiming at the problems of insufficient trajectory feature learning,low precision of trajectory prediction results,and coarse particles in the research of network resource management methods for trajectory prediction,a trajectory prediction algorithm of bidirectional recurrent neural network was proposed.Through in-depth mining of the user′s movement rules,the user′s movement prediction was realized.According to the user′s mobile prediction information,the network resource pre-allocation plan was designed and the mobile behavior was divided into network resources,then the collaborative resource optimization management of multiple cells was realized.The simulation results showed that in the trajectory prediction problem,the trajectory prediction algorithm of the bidirectional recurrent neural networked had better comprehensive performance than the ordinary neural network algorithm.In the problem of network resource management,the network resource management pre-allocation scheme of trajectory prediction could accurately predict the base station connected by users,so that the base station had a higher resource utilization rate.