论文标题
多源FBMC系统的光谱有效的试点结构和通道估计
Spectrally Efficient Pilot Structure and Channel Estimation for Multiuser FBMC Systems
论文作者
论文摘要
在本文中,我们考虑过滤器库多载体(FBMC)系统的上行链路中的频道估计问题。我们提出了FBMC的试点结构和一种联合多源通道估计方法。与文献中可用的解决方案相反,我们提出的技术不依赖于每个子载波频段上的扁平通道条件,也不依赖于在不同用户飞行员之间放置防护符号的任何要求。我们提出的飞行员结构通过将用户的飞行员在时间和频率上交织来减少训练开销。因此,我们可以在同一带宽内容纳大量的训练信号并提高光谱效率。此外,与使用所有子载波进行训练的解决方案相比,这种试验结构固有地导致峰值与平均功率比(PAPR)降低。我们分析我们提出的方法的CRAMER-RAO下限(CRLB)和均方根误差(MSE)表达式。我们证明这些表达方式是相同的。这证实了我们提出的方法的最佳性,该方法通过模拟对数字进行了评估。依靠其提高的光谱效率,我们提出的方法可以为大量用户提供服务,并放松基于FBMC的大型MIMO系统中的飞行员污染问题。这是通过模拟的单个单元格和多电器方案的命中率性能来证实的。
In this paper, we consider channel estimation problem in the uplink of filter bank multicarrier (FBMC) systems. We propose a pilot structure and a joint multiuser channel estimation method for FBMC. Opposed to the available solutions in the literature, our proposed technique does not rely on the flat-channel condition over each subcarrier band or any requirement for placing guard symbols between different users' pilots. Our proposed pilot structure reduces the training overhead by interleaving the users' pilots in time and frequency. Thus, we can accommodate a larger number of training signals within the same bandwidth and improve the spectral efficiency. Furthermore, this pilot structure inherently leads to a reduced peak-to-average power ratio (PAPR) compared with the solutions that use all the subcarriers for training. We analytically derive the Cramer-Rao lower bound (CRLB) and mean square error (MSE) expressions for our proposed method. We show that these expressions are the same. This confirms the optimality of our proposed method, which is numerically evaluated through simulations. Relying on its improved spectral efficiency, our proposed method can serve a large number of users and relax pilot contamination problem in FBMC-based massive MIMO systems. This is corroborated through simulations in terms of sum-rate performance for both single cell and multicell scenarios.