Multiple Input Multiple Output
Multiple-input multiple-output (MIMO) systems utilize multiple antennas at both transmitting and receiving ends to enhance communication efficiency and reliability. Current research focuses on optimizing MIMO performance across diverse applications, including wireless communication, video processing, and radar sensing, employing techniques like deep learning, reinforcement learning, and novel signal processing algorithms to address challenges such as channel estimation, beamforming, and resource allocation. These advancements are driving improvements in data throughput, spectral efficiency, and robustness in various fields, from cellular networks and satellite communications to image processing and robotics.
Papers
End-to-End Autoencoder Communications with Optimized Interference Suppression
Kemal Davaslioglu, Tugba Erpek, Yalin E. Sagduyu
Machine Learning Methods for Spectral Efficiency Prediction in Massive MIMO Systems
Evgeny Bobrov, Sergey Troshin, Nadezhda Chirkova, Ekaterina Lobacheva, Sviatoslav Panchenko, Dmitry Vetrov, Dmitry Kropotov