超密集物联网中的多蜂窝网络选择算法

随着物联网终端爆炸式的增加,物联网致密化成为发展的必然。在海量终端数量和资源严重受限的情况下,如何确定物联网终端设备的接入基站以及如何有效地为接入的用户进行资源分配,成为超密集物联网系统所需解决的重要问题。文章在吞吐量和系统能耗之间进行折中,以系统能效为优化目标,设计了一种超密集物联网中的多蜂窝网络选择算法。该算法为用户和基站设置效用函数,基于匹配理论完成用户的选择过程。最后对该算法和对比算法进行仿真,结果表明,多蜂窝网络选择算法在能耗和能效性能上均优于对比算法。

Multi-cellular Network Selection Algorithm in Ultra-dense IoT

With the explosive growth of IoT terminals,the densification of the IoT has become an inevitable trend.In the case of huge amount of terminals and severely limited resources,how to determine the access base station of the IoT terminals and how to effectively allocate resources for the accessed users become important problems in the ultra-dense IoT system.In this paper,a compromise between throughput and system energy consumption is made.A multi-cellular network selection algorithm in ultra-dense IoT is designed with system energy efficiency as the optimization goal.The algorithm sets utility function for each user and each base station,and completes the user selection process based on the matching theory.Finally,the algorithm and comparison algorithm mentioned in this paper are simulated.The simulation results show that the proposed algorithm outperforms the comparison algorithm in energy consumption and energy efficiency.