Deep Learning-Aided Spatial Multiplexing with Index Modulation
Abstract
In this paper, deep learning (DL)-aided data detection of spatial multiplexing (SMX) multiple-input multiple-output (MIMO) transmission with index modulation (IM) (Deep-SMX-IM) has been proposed. Deep-SMX-IM has been constructed by combining a zero-forcing (ZF) detector and DL technique. The proposed method uses the significant advantages of DL techniques to learn transmission characteristics of the frequency and spatial domains. Furthermore, thanks to using subblockbased detection provided by IM, Deep-SMX-IM is a straightforward method, which eventually reveals reduced complexity. It has been shown that Deep-SMX-IM has significant error performance gains compared to ZF detector without increasing computational complexity for different system configurations.
Keywords
Cite
@article{arxiv.2202.02856,
title = {Deep Learning-Aided Spatial Multiplexing with Index Modulation},
author = {Merve Turhan and Ersin Ozturk and Hakan Ali Cirpan},
journal= {arXiv preprint arXiv:2202.02856},
year = {2022}
}