基于分层聚类和干扰对齐的MIMO链路调度算法

为了降低干扰对齐所需的处理开销，将链路划分为多个簇分别进行处理成为可行的办法之一。针对现有簇划分算 法中运算复杂度较高的问题，本文提出了一种基于最小信干比的簇划分算法。在此基础上，针对所有簇同时通信造成部分簇内链路接收端信干噪比（Signal to interference plus noise ratio，SINR）较低的问题，本文将以链路为单位的调度问题等效为以簇为单位的调度问题，提出了一种基于层次聚类的簇调度算法。理论与仿真实验结果表明，本文所提出的簇划分算法的运算复杂度明显低于现有算法，且相同条件下的系统平均吞吐量更高。同时，本文提出的基于簇层次聚类的调度算法不同程度地提升了各簇内链路接收端的SINR，系统可根据不同的性能需求进行调度策略选择。

Novel MIMO Link Scheduling Algorithm Based on Hierarchical Clustering and Interference Alignment

The signaling overheads of interference alignment (IA) obtaining global channel state information increase with the number of links. Grouping the links into clusters, within which the interference are processed by IA, becomes an effective method to reduce the overheads. Considering the fact of high computational complexity in the process of link partition, an alternative link partition algorithm based on minimum signal-to-interference-ratio (MinSIR) is proposed. Furthermore, when all the clusters simultaneously transmit in a single timeslot, the signal-to interference-plus-noise-ratio (SINR) at the receivers of several links was insufficient for successful transmission. To solve such a problem, the link scheduling problem was substituted by a novel cluster-based scheduling algorithm using hierarchical clustering. The theoretical analysis and simulation results show that the proposed link partition algorithm obviously reduced the computational complexity, and obtained superiors system throughput. Meanwhile, the cluster-based scheduling algorithm effectively improved the SINR at the receivers of links, which potentially supported the system decision of scheduling scheme for specified performance demand.