基于最优加权多属性决策的LWA网络接入点选择算法

为了应对LWA网络下eNB和AP大量密集部署，用户需求难以充分满足的现状，该文提出一种基于最优加权多属性决策(OWMAD)的LWA网络接入点选择算法。该算法预先收集接入点属性并建立属性集合，然后设计决策属性的最优权重，将决策矩阵与最优权重向量叠加，最后根据各个接入点综合性能的计算结果确定用户可选择的最佳网络接入点。仿真结果表明，该算法不仅能有效提升边缘地区及系统整体的吞吐量，还能够降低系统平均时延，提升用户的服务质量。

LWA Network Access Point Selection Algorithm Based on Optimal Weighted Multi-Attribute Decision

For the purpose of coping with the intensive deployment of eNB (evolved NodeB) and AP (access point) in LWA (LTE WLAN aggregation) networks, and a situation in which the user is unable to satisfy their needs, this paper proposes an access point selection algorithm for LWA networks based on optimal weighted multi-attribute decision (OWMAD). First, the algorithm pre-collects the access point attributes and establishes the attribute set, then designs the optimal weights of the decision attributes and overlays the decision matrix with the optimal weight vector. Finally, the optimal network access point is determined according to the results of the comprehensive performance of each access point. Simulation results show that the proposed algorithm can effectively improve the throughput of peripheral areas and the overall system, while reducing the average system delay and improving the user's quality of service.