We consider high-dimensional MIMO transmissions in frequency division duplexing (FDD) systems. For precoding, the frequency selective channel has to be measured, quantized and fed back to the base station by the users. When the number of antennas is very high this typically leads to prohibitively high quantization complexity and large feedback. In 5G New Radio (NR), a modular quantization approach has been applied for this, where first a low-dimensional subspace is identified for the whole frequency selective channel, and then subband channels are linearly mapped to this subspace and quantized. We analyze how the components in such a modular scheme contribute to the overall quantization distortion. Based on this analysis we improve the technology components in the modular approach and propose an orthonormalized wideband precoding scheme and a sequential wideband precoding approach which provide considerable gains over the conventional method. We compare the performance of the developed quantization schemes to prior art by simulations in terms of the projection distortion, overall distortion and spectral efficiency, in a scenario with a realistic spatial channel model.

翻译：我们考虑频分双工（FDD）系统中的高维MIMO传输。在发端预编码前，需要由用户测量频率选择性信道并将其量化反馈至基站。当天线数量非常多的时候，这通常会导致量化复杂度过高并存在大量的反馈。在5G New Radio（NR）中，采用了模块化的量化方法，首先对整个频率选择性信道进行低维子空间的识别，然后将子频带信道线性映射到这个子空间并进行量化。我们分析了这种模块化方案中的组成部分对整体量化失真的贡献。基于此分析，我们改进了模块化方法中的技术组件，并提出了一种正交的宽带预编码方案和顺序宽带预编码方法，这些方法相比传统方法提供了相当大的增益。我们通过在具有现实空间信道模型的情况下进行模拟，通过投影失真、整体失真和光谱效率方面比较了所开发量化方案的性能和先前的技术文献。