MIMO-FBMC/OQAM系统稀疏信道估计方法研究

Multiple input multiple output-filter bank multicarrier with offset quadrature amplitude modulation (MIMO-FBMC/OQAM) system utilizes the multiple antennas technology, and it provides more advantages than conventional FBMC/OQAM system. However, due to the inherent imaginary interference and inter-antenna interference in MIMO-FBMC/OQAM systems, channel estimation is relatively difficult, and the conventional channel estimation methods cannot be directly applied to MIMO-FBMC/OQAM systems. In this project, the effective sparse channel estimation algorithms for MIMO-FBMC/OQAM systems are studied by utilizing the sparse characteristics and correlation of MIMO channels. For the sparse statistical characteristics of channels, sparse channel estimation methods based on fast Bayesian matching pursuit are proposed. For the correlation of MIMO channels, channel estimation methods based on distributed compressed reconstruction are proposed. Finally, by combing both the sparse characteristics and correction of MIMO channels, channel estimation methods based on distributed joint sparse Bayesian learning are proposed. These methods are proposed to solve the problem of high accuracy channel estimation for MIMO-FBMC/OQAM systems in the presence of multiple interference.

多输入多输出滤波器组多载波偏移幅度调制（MIMO-FBMC/OQAM）系统利用多天线技术，比传统FBMC/OQAM系统具有更多的优势。然而，由于MIMO-FBMC/OQAM系统中存在固有虚部干扰和天线间干扰，使得信道估计相对困难，传统信道估计方法无法直接应用到该系统中。本项目通过利用MIMO信道的稀疏统计特性和相关性，研究MIMO-FBMC/OQAM系统有效稀疏信道估计方法。针对信道的稀疏统计特性，提出基于快速贝叶斯匹配追踪的信道估计方法；针对MIMO信道间的相关性，提出基于分布式压缩重构的信道估计方法；最后联合MIMO信道的稀疏特性和相关性，提出基于分布式联合稀疏贝叶斯学习的信道估计方法。解决多干扰条件下，MIMO-FBMC/OQAM系统的高准确度信道估计问题。

多输入多输出（Multiple-Input Multiple-Output,MIMO）技术由于其技术特点及优势，已成为第五代移动通信的核心技术。多输入多输出滤波器组多载波偏移幅度调制（MIMO-FBMC/OQAM）系统利用多天线技术，比传统FBMC/OQAM系统具有更多的优势。然而，由于MIMO-FBMC/OQAM系统中存在固有虚部干扰和天线间干扰，使得信道估计相对困难，传统信道估计方法无法直接应用到该系统中。本项目通过利用MIMO信道的稀疏统计特性和相关性，研究MIMO-FBMC/OQAM系统有效稀疏信道估计方法。针对信道的稀疏统计特性，提出基于贝叶斯方法的信道估计方法；针对传统压缩感知方法复杂度高的问题，提出低复杂度压缩感知自适应信道估计方法；针对MIMO信道间的相关性，提出基于分布式压缩重构的信道估计方法；解决MIMO-FBMC/OQAM系统的高准确度信道估计问题。相关研究丰富了现有研究的内容，填补了部分研究空白。