大规模MIMO系统的全导频RZF预编码方法

发布时间：2018-11-03 16:04

【摘要】：研究了大规模多输入多输出(MIMO)系统的预编码。针对小区间干扰和导频污染会对预编码的有效性产生较大影响的问题,提出了一种改进的全导频正则化迫零(RZF)预编码方法。该方法通过将有限的正交导频信号分配给小区用户来对预编码矩阵中的信道向量进行优化,得到优化后的全导频正则化预编码矩阵,并依此推导出新的包含导频污染函数和用户干扰函数的和速率表达式。另外,综合考虑基站天线数、用户数以及导频重用因子,优化其配置关系,从而用较少的用户信息和更高的导频重用因子来抑制更多的小区间干扰,有效地提升系统性能。实验结果表明,这种改进的RZF预编码算法能够较好地提高系统容量,在完全已知信道状态信息(CSI)和未完全已知CSI两种情况下的频谱效率及和速率均优于传统的RZF方法。
[Abstract]:The precoding of large scale multi-input multi-output (MIMO) systems is studied. Aiming at the problem that inter-cell interference and pilot pollution will greatly affect the effectiveness of precoding, an improved full-pilot regularization zero-forcing (RZF) precoding method is proposed. In this method, the channel vectors in the precoding matrix are optimized by allocating the limited orthogonal pilot signals to the cell users, and the optimized full-pilot regularized precoding matrix is obtained. A new sum rate expression including pilot contamination function and user interference function is derived. In addition, considering the number of base station antennas, the number of users and the pilot reuse factor, the configuration relationship is optimized so that more inter-cell interference can be suppressed with less user information and higher pilot reuse factor, and the system performance can be improved effectively. The experimental results show that the improved RZF precoding algorithm can improve the capacity of the system, and the spectral efficiency and the rate of the improved RZF precoding algorithm are better than those of the traditional RZF method under the condition of complete known channel state information (CSI) and incomplete known CSI.
【作者单位】：江西理工大学信息工程学院;
【基金】：国家自然科学基金(61363076) 江西省自然科学基金(20142BAB207020)资助项目
【分类号】：TN919.3

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