论文标题
深度学习辅助的空间多路复用索引调制
Deep Learning-Aided Spatial Multiplexing with Index Modulation
论文作者
论文摘要
在本文中，已经提出了带有索引调制（IM）（Deep-SMX-IM）的空间多路复用（SMX）多输入多输出（MIMO）传输的深度学习（DL）辅助数据检测。 Deep-SMX-IM是通过组合零强化（ZF）检测器和DL技术来构建的。所提出的方法使用DL技术的显着优势来学习频率和空间域的传输特征。此外，由于使用了IM提供的基于子块的检测，DeepSMX-IM是一种简单的方法，最终揭示了降低的复杂性。已经表明，与ZF检测器相比，DeepSMX-IM具有显着的错误性能增长，而没有增加不同系统配置的计算复杂性。
In this paper, deep learning (DL)-aided data detection of spatial multiplexing (SMX) multiple-input multiple-output (MIMO) transmission with index modulation (IM) (Deep-SMX-IM) has been proposed. Deep-SMX-IM has been constructed by combining a zero-forcing (ZF) detector and DL technique. The proposed method uses the significant advantages of DL techniques to learn transmission characteristics of the frequency and spatial domains. Furthermore, thanks to using subblockbased detection provided by IM, Deep-SMX-IM is a straightforward method, which eventually reveals reduced complexity. It has been shown that Deep-SMX-IM has significant error performance gains compared to ZF detector without increasing computational complexity for different system configurations.
