MIMO Detection Algorithms – Deep Learning Based and Traditional Methods

Applications of deep learning have not been adequately studied in communication systems, though it is a tremendously popular approach in many other fields. This study focuses on the utilization of various deep learning (DL) based detection approaches for multiple-input multiple-output (MIMO) systems, which is a promising technology for current and future wireless networks. Both data-driven and model-based DL algorithms are discussed in addition to the traditional approaches for MIMO signal detection in this study. The simulation results show that both DL approaches may have superior performance for MIMO systems in terms of computational complexity and bit error rate.