摘要
首先从子空间对齐的角度将干扰信号功率和有用信号功率联合优化的问题建模于Grassmannian流形上,有约束的最优化问题被转化为降维的无约束的最优化问题。然后利用Grassmannian流形的几何特性,提出了一种基于Grassmannian流形上共轭梯度算法的联合干扰对齐预编码方案。计算机仿真表明,该算法兼顾干扰信号功率的最小化和有用信号功率的最大化,可以有效提高系统的和速率性能,而且该算法可以有效解决Grassmannian流形上最陡下降算法每次寻优的90°转折问题,具有更高的收敛速度。
Firstly, from the perspective of subspace alignment, the joint optimization problem of the in- terference signal power and the useful signal power is modeled on the Grassmannian manifold. The constrained optimization problem is transformed into the unconstrained optimization problem with lower dimension. Then, using the geometric properties of the Grassmannian manifold, a joint interference align- ment precoding scheme based on conjugate gradient algorithm on the Grassmannian manifold is proposed. Computer simulation results show that the proposed scheme improves the sum rate performance of the multiuser MIMO interference system by jointly considering the minimization of the interference signal power and the maximization of the useful signal power, and also improves the convergence speed by effectively solving the 90° turning problem of the Grassmannian steepest descent algorithm.
出处
《数据采集与处理》
CSCD
北大核心
2017年第6期1115-1124,共10页
Journal of Data Acquisition and Processing
基金
国家自然科学基金(61771254
61471200)资助项目
江苏省自然科学基金(BK20140881)资助项目
南京邮电大学(2016外71)资助项目
