超密集网络中基于聚类的资源分配方案

超密集网络(ultra-dense network, UDN)中,毫微微基站(femto-cell base station, FBS)的密集和随机部署会导致严重的小区间干扰。为了减轻干扰、保障用户服务质量(quality of service, QoS),提出了一种UDN中基于聚类的资源分配方案。首先,设计了一种基于加权密度的改进K-means聚类算法,将FBS动态划分为不同的簇。然后,以最大化UDN系统吞吐量为目标提出了一种两阶段时频资源分配方案:第一阶段,每个聚类内使用贪婪算法执行时频资源块的分配;第二阶段,利用资源补偿分配算法分配剩余的资源块,在考虑用户公平性的同时保证用户QoS。仿真结果表明,本文提出的资源分配方案能够有效提升系统吞吐量,同时保证用户QoS和公平性。

Cluster-based resource allocation scheme in ultra-dense network

In the ultra-dense networks (UDN), dense and random deployment of the femto-cell base station (FBS) can cause severe inter-cell interference. In order to mitigate interference and guarantee the quality of service (QoS), a cluster-based resource allocation scheme in UDN is proposed. Firstly, an improved K-means clustering algorithm based on weighted density is designed to dynamically divide the FBS into different clusters. Then, aiming at maximizing the throughput of the UDN system, a two-stage time-frequency resource allocation scheme is proposed. In the first stage, the allocation of time-frequency resource blocks is performed by using a greedy algorithm in each cluster. In the second stage, the resource compensation allocation algorithm is proposed to allocate the remaining resource blocks to ensure user QoS while considering user fairness. The simulation results show that the proposed resource allocation scheme can effectively improve the system throughput while ensuring user QoS and fairness.