大规模MIMO作为5G系统的重要技术支撑，其性能潜力有赖于基站对下行信道信息的获取。FDD制式大规模MIMO系统因上下行信道非互易，致使信道信息获取时导频开销过大，且其传输特点又决定了信道信息获取与数据传输要共享基站传输资源，加之硬件损伤等非理想条件，使得信道信息获取问题面临诸多挑战。本项目拟从导频开销、资源利用率、鲁棒性三方面对FDD大规模MIMO系统信道信息获取问题进行研究。首先，从基站天线数本源出发，利用随机矩阵理论分析天线数与导频数以不同速率变化时系统速率渐进性能，获得基于天线选择的导频开销设置准则，进而优化低开销非正交导频信号，并采用闭环联合估计策略提高估计精度。其次，引入能效指标，借助最优化理论和博弈论等，对信道估计和数据传输资源联合分配。最后，对非理想性因素进行建模，综合分析其对信道信息获取造成的影响，根据不同的鲁棒性需求，优化实现低开销、高能效和强鲁棒的信道信息获取方案。

As an important technical support of 5G system, the potential performance benefits of massive MIMO highly depend on the acquisition of the downlink channel state information (CSI) at the base station (BS). For the frequency division duplexing (FDD) MIMO system, the pilot overhead for the CSI acquisition is prohibitive due to the channel non-reciprocity, and the transmission characteristics determines that the resource at the BS will be shared between the CSI acquisition stage and the data transmission stage. Apart from these, there will be non-ideal conditions, e.g., the hardware impairments, which all make the CSI acquisition face many challenges. This project investigates the CSI acquisition problem of FDD massive MIMO system in terms of the pilot overhead, the resource utilization, and the robustness requirements. Firstly, starting from the original number of BS antennas, the asymptotic performance of transmission rate is analyzed with number of antennas and the number of pilots changing at different speeds by using the random matrix theory such that we can obtain the principles of setting pilot overhead based on antenna selection. Then, the non-orthogonal pilot signal with low overhead is optimized, and the closed-loop estimation strategy is designed to improve the estimation accuracy. Secondly, the energy efficiency is introduced, and the joint resource allocation of channel estimation stage and data transmission stage is conducted with the aid of optimization theory and game theory. Finally, the non-ideal factors are modeled, and the impacts of them on the CSI acquisition are analyzed. According to the different robustness requirements, we realize the low cost, energy efficient and robust scheme for CSI acquisition.