论文标题
与统计CSIT的下行链路大规模MIMO的能效优化
Energy Efficiency Optimization for Downlink Massive MIMO With Statistical CSIT
论文作者
论文摘要
我们研究了单细胞大量多输入多输出（MIMO）下行链路传输的能源效率（EE）优化，仅在基站可用的统计通道状态信息（CSI）。我们首先表明，通过为最佳传输协方差矩阵的特征向量推导封闭形式的溶液，梁域的传输有利于大量MIMO下行链路中的能源效率。通过这个结论，EE优化问题将减少为实现的电源分配问题，该问题比原始的大维复杂矩阵值预编码的设计问题要容易得多。我们进一步提出了一种具有低复杂性和保证收敛性的迭代填充结构梁域功率分配算法，从顺序优化，分数优化和随机矩阵理论中利用了这些技术。数值结果证明了我们提出的统计CSI辅助EE优化方法的近乎最佳性能。
We investigate energy efficiency (EE) optimization for single-cell massive multiple-input multiple-output (MIMO) downlink transmission with only statistical channel state information (CSI) available at the base station. We first show that beam domain transmission is favorable for energy efficiency in the massive MIMO downlink, by deriving a closed-form solution for the eigenvectors of the optimal transmit covariance matrix. With this conclusion, the EE optimization problem is reduced to a real-valued power allocation problem, which is much easier to tackle than the original large-dimensional complex matrix-valued precoding design problem. We further propose an iterative water-filling-structured beam domain power allocation algorithm with low complexity and guaranteed convergence, exploiting the techniques from sequential optimization, fractional optimization, and random matrix theory. Numerical results demonstrate the near-optimal performance of our proposed statistical CSI aided EE optimization approach.
