大规模MIMO系统基于结构化压缩感知的信道估计中导频设计新方法研究

项目名称： 大规模MIMO系统基于结构化压缩感知的信道估计中导频设计新方法研究

项目编号： No.61501248

项目类型： 青年科学基金项目

立项/批准年度： 2016

项目学科： 无线电电子学、电信技术

项目作者： 何雪云

作者单位： 南京邮电大学

项目金额： 22万元

中文摘要： 为了满足日益增长的用户数量和数据速率的需求，未来的十年里，超4代移动通信系统需要提供更高的数据速率。大规模MIMO（massive MIMO）技术最有希望成为超4代移动通信系统的核心技术。与传统MIMO系统相比，massive MIMO 将大幅度提高系统容量和系统能量有效性。但是这些优势的获得必须以基站准确获得下行信道状态信息（CSI）来进行下行预编码为前提条件。因此，研究频谱有效性高的信道估计新方法成为massive MIMO系统应用中一个至关重要的问题。结构化压缩感知已经应用于massive MIMO系统的信道估计中以减少导频的数量。然而，基于结构化压缩感知信道估计的导频设计方法与传统信道估计中的方法不同，现有文献还没有对其优化设计展开研究。本项目将研究massive MIMO系统基于结构化压缩感知信道估计中的最优导频的设计问题，从而在使用很少导频符号的前提下获得优异的估计性能。

中文关键词： 大规模MIMO；信道估计；结构化压缩感知；导频设计

英文摘要： In order to meet the rapidly increase in the number of users and the amount of data traffic, the future networks, i.e., beyond 4G networks will be scaled up to reach the gigabit data rates range over the next 10 years. The massive MIMO system has great potential as the key technology for future beyond 4G cellular systems, in terms of its high spectral efficiency and energy efficiency. However, these advantages are all on the basis of obtaining accurate down-link channel state information (CSI) to perform the pre-coding for down-link data transmission. So, exploring the spectral-efficient channel estimation methods is a challenging problem in massive MIMO systems. The structured compressive sensing theory has been employed in the channel estimation of massive MIMO systems to decrease the pilot symbols. However, the optimal pilots design in structured compressive sensing based channel estimation has not been intensively researched, which is different from the question in traditional channel estimation methods. Our project focuses on the optimal pilots design for structured compressive sensing based channel estimation, which can lead to superior estimation performance of CSI by employing only a few pilots.

英文关键词： Massive MIMO;Channel Estimation;Structured Compressive Sensing;Pilots Design