基于二次规划的干扰对齐编解码矩阵联合优化算法

针对多用户多输入多输出干扰信道中以系统容量表征的目标函数既不是线性函数也不是凸函数,直接求解比较困难的问题,提出一种基于二次规划的联合求解多用户多输入多输出干扰对齐编解码矩阵的迭代算法。在迭代步长很小的前提下,目标函数在局部具有凸函数性质,因此可以将问题转化为传统的二次规划问题。分别给出了3对收发用户和4对收发用户干扰系统的通信速率随信噪比变化的仿真。结果表明,作者提出的干扰对齐编解码矩阵求解方法能够使干扰系统中的多个用户同时进行有效的通信,提出的算法与传统的干扰泄漏最小化干扰对齐方法相比,在低信噪比区间具有较大的速率提升,而在高信噪比区间可以获得相似的性能。

Interference Alignment using Quadratic Programming

Interference alignment (IA) in the multi-user MIMO interference channel with constant channel coefficients was considered. An iterative algorithm for finding the interference alignment solutions was proposed for the case where all interference alignment multiplexing gains are one. Traditional IA algorithm which minimizes the interference leakage (MIL) was not sum rate optimal with finite SNR, so in this paper perfect alignment constraint was relaxed in order to obtain better sum rate performance. The problem was first converted to a convex quadratic program problem based on the small step size assumption then all the precoding and decoding matrices were updated iteratively. Simulation results showed that the proposed algorithm achieves better sum rate performance compared with MIL algorithm at lower SNR, and almost the same at higher SNR.