Machine learning-based method for MIMO detection complexity reduction

A machine learning based multiple-input multiple-output (MIMO) demapper for a wireless device may include a classifier that selects which MIMO demapper to use for samples of a particular tone. For example, a wireless device may receive a plurality of signals including a plurality of tones via a plurality of antennas. The wireless device may determine a selection feature for each of the plurality of tones. The wireless device may select, for each tone, a selected demapper from at least a first MIMO demapper and a second MIMO demapper based on a selection feature by a classifier. The second MIMO demapper may have a different performance characteristic than the first MIMO demapper. The wireless device may detect, for each tone, one or more streams using the selected demapper for the tone. The stream may refer to a sequence of bits. 用于无线设备的基于机器学习的多输入多输出(MIMO)解映射器可包括选择哪个MIMO解映射器以用于特定频调的样本的分类器。例如，无线设备可经由多个天线接收包括多个频调的多个信号。无线设备可针对多个频调中的每个频调确定选择特征。无线设备可针对每个频调通过分类器基于选择特征从至少第一MIMO解映射器和第二MIMO解映射器中选择所选解映射器。第二MIMO解映射器可具有与第