Using a deep autoencoder (DAE) for end-to-end communication in multiple-input
multiple-output (MIMO) systems is a novel concept with significant potential.
DAE-aided MIMO has been shown to outperform singular-value decomposition
(SVD)-based precoded MIMO in terms of bit error rate (BER). This paper proposes
embedding left- and right-singular vectors of the channel matrix into DAE
encoder and decoder to further improve the performance of the MIMO DAE.
SVDembedded DAE largely outperforms theoretic linear precoding in terms of BER.
This is remarkable since it demonstrates that DAEs have significant potential
to exceed the limits of current system design by treating the communication
system as a single, end-to-end optimization block. Based on the simulation
results, at SNR=10dB, the proposed SVD-embedded design can achieve a BER of
about $10^{-5}$ and reduce the BER at least 10 times compared with existing DAE
without SVD, and up to 18 times compared with theoretical linear precoding. We
attribute this to the fact that the proposed DAE can match the input and output
as an adaptive modulation structure with finite alphabet input. We also observe
that adding residual connections to the DAE further improves the performance.

使用深度自动编码器（DAE）通过将通道矩阵的奇异值分解嵌入编码器和解码器来进一步提高 MIMO DAE 的性能，SVD 嵌入 DAE 在 BER 方面大大优于理论线性预编码，并且可以作为自适应调制结构与有限字母输入匹配来优化整个通信系统的性能