Joint covariance matrix estimation and pilot allocation in massive MIMO systems
Joint covariance matrix estimation and pilot allocation in massive MIMO systems
复制标题
DOI：
10.1109/icc.2017.7996476
复制
发表时间：
2017-05
期刊：
影响因子：
--
通讯作者：
David Neumann;Kamel Shibli;M. Joham;W. Utschick
中科院分区：
文献类型：
--
作者：
David Neumann;Kamel Shibli;M. Joham;W. Utschick
导频污染是蜂窝大规模MIMO系统中的吞吐量限制因素。以前的工作表明，导频污染的影响可以减少利用信道协方差矩阵的形式的结构信息。此外，通过协调的用户分配可以获得显著的增益。在本文中，我们将这些方法扩展到一个现实的情况下，不完善的知识的信道及其分布在基站。我们制定了一个优化问题分配用户的可用导频序列，这在同一时间考虑到估计的协方差矩阵，并提出了一个次优贪婪算法的有效实施。与建立的物理信道模型的仿真结果表明，所提出的方法在基站的协方差矩阵的不完善的知识的情况下，显着的性能增益。
Pilot contamination is a throughput limiting factor in cellular massive MIMO systems. Previous work has shown that the impact of pilot-contamination can be reduced by exploiting structural information in form of channel covariance matrices. Additionally, significant gains can be obtained through coordinated user assignment. In this paper, we extend these approaches to a realistic scenario with imperfect knowledge of the channel and its distribution at the base station. We formulate an optimization problem for assigning users to the available pilot sequences, which at the same time takes the estimation of the covariance matrices into account and propose a suboptimal greedy algorithm for efficient implementation. Simulation results with established physical channel models demonstrate the significant performance gains of the proposed method in the case of imperfect knowledge of the covariance matrices at the base station.