A Note on Implementation Methodologies of Deep Learning-Based Signal Detection for Conventional MIMO Transmitters

Abstract

Baek et al. proposed a deep learning-based signal detector for conventional MIMO systems, which is a pioneering work of applying artificial intelligence into wireless communications. Although this work works well under static fading channels, it is worth notable that it fails to work under block-fading channels. In particular, the detection BER under block-fading channels is around 0.5 even in the high regime of SNR. To explain this unexpected result, we provide some simple yet efficient theoretical analysis, which clearly verifies that the proposed detector cannot decouple the phases between the channel parameters and transmitted signals and hence it fails to detect the transmitted signals under block-fading channels. The results in this paper can help understand and improve the detector. In particular, the detector structure should incorporate the channel state information for the application under block-fading channels.