蜂窝系统自适应K近邻干扰对齐算法

干扰对齐算法应用于蜂窝网络时，存在计算复杂度高、系统开销大等缺点，本文基于分簇模型，提出了一种自适应K近邻干扰对齐算法，并给出一种无需收发端迭代的干扰对齐预编码向量求解方法。该算法依据信干比门限自适应选取参与干扰对齐的干扰信号，对预筛选的干扰信号利用优化方法进行干扰对齐，降低了算法的计算复杂度和系统开销。仿真分析表明，通过选取合适的信干比门限，本文所提算法在干扰消除性能相当的情况下，其算法复杂度和系统开销显著降低，提高了干扰对齐算法的适用性。 

An Adaptive K-nearest-neighbor Interference Alignment Algorithm in Cellular System

For the disadvantages that the high achievement complexity and the heavy overheads of the system when interference alignment was applied to the cellular system for co-channel interference cancellation, this paper, based on the clustered model, proposed an adaptive K-nearest-neighbor interference alignment algorithm and a solving method to get the precoding vector without uniting the transmitter and the receiver. This algorithm could adaptively choose the interference for interference alignment according to the threshold of the signal-to-interference ratio, which could made the interference prechosen and decrease the achievement complexity of interference alignment. Simulation results show that by choosing an appropriate threshold of signal-to-interference ratio, the proposed algorithm could obtain a quite good performance of interference cancellation while the achievement complexity and the overheads could greatly decreased, which improved the applicability of interference alignment algorithm.