MIMO干扰信道下基于自适应复合代价函数的干扰对齐预编码设计

在多输入多输出(multiple-input multiple-output,MIMO)干扰信道中,针对传统的单边干扰对齐(interference-alignment,IA)算法不能有效地保留期望信号而导致系统容量受限的问题,提出一种利用辅助中间变量实现单边IA的设计思想,并以此为基础,给出一种基于自适应复合代价函数(adaptive composite cost function,ACCF)的IA预编码设计方法。该方法首先定义期望子空间内的残留干扰和有用信号功率的自适应加权差作为代价函数;进而通过一辅助函数,将干扰抑制矩阵转化为中间变量,以构造复合代价函数;最后利用格拉斯曼(Grassmann)流形上的梯度下降法实现复合代价函数的优化求解。数值仿真结果验证了基于ACCF的IA方法在MIMO干扰信道中的有效性。

Precoder design for interference alignment based on adaptive composite cost function over MIMO interference channels

The traditional one side interference alignment (IA) algorithms cannot effectively reserve the desired signals in the interference-free subspace over multiple-input multiple-output (MIMO) interference channels, which causes the degradation of the system capacity. To deal with this, a new IA design concept with auxiliary intermediate variables is put forward, then a method based on adaptive composite cost function (ACCF) is proposed to design the precoder matrices. In the method, the adaptive weighted difference between the powers of the leakage interference and useful signals is firstly defined as the cost function. Then the interference suppression matrices are transformed into the intermediate variables by an auxiliary function in order to obtain the adaptive composite function. Finally, the composite cost function is optimized to obtain the precoder with the modified gradient descent method on the Grassmann manifold. Simulation results verify the effectiveness of the ACCF-based IA method over MIMO interference channels.