超密集组网下基于链路效率的多连接小区选择算法

A Multi-connectivity Cell Selection Algorithm Based on Link Efficiency for Ultra-dense Networks

在5G超密集网络场景下,通过用户双/多连接技术可提高用户吞吐量,降低频繁切换带来的链路失效率。但是,随着链接数的增加,链路管理和资源分配带来的控制信令开销将增加,多链路带来的边际效益递减。为此,提出了多连接链路效率的概念,据此设计了基于链路效率的小区选择算法。该算法基于最大化用户和平均链路速率问题,在基站端及用户端采用变量松弛和拉格朗日对偶分解法来求解。仿真结果表明,多连接的小区选择问题能提高系统吞吐量,在获得更大的用户和速率的同时,也带来链路使用效率的提升。

In the 5G ultra-dense network(UDN)scenarios,the user′s throughput can be improved through the dual/multi-connectivity technology and the link failure efficiency caused by frequent switching can be reduced.However,with the increasing number of links,the control signaling overhead from link management and resource allocation increases,but the marginal benefit of multi-links declines.The concept of multi-connectivity link efficiency is proposed,and a cell selection algorithm based on link efficiency is designed.Based on maximizing sum user′s average link rate,variable slack and Lagrangian dual decomposition are used to solve the problem in the base station and the user equipment.The simulation results demonstrate that the proposed multi-connectivity cell selection algorithm can improve the system throughput and user sum-rate with increasing link efficiency.