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。对于预编码，频率选择性信道需由用户测量、量化并反馈至基站。当天线数量极大时，这通常会导致极高的量化复杂度和庞大的反馈开销。在5G新空口（NR）中，针对此问题采用了模块化量化方法：首先针对整个频率选择性信道识别一个低维子空间，随后将子带信道线性映射至该子空间并进行量化。我们分析了此类模块化方案中各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，并提出了一种正交归一化宽带预编码方案和一种顺序宽带预编码方法，相较于传统方法带来了显著性能提升。我们通过仿真，在真实空间信道模型场景下，从投影失真、总失真和频谱效率三个方面，将所提量化方案的性能与现有技术进行了比较。