Techniques which leverage channel state information (CSI) at a transmitter to adapt wireless signals to changing propagation conditions have been shown to improve the reliability of modern multiple input multiple output (MIMO) communication systems. Due to the difficulty of estimating downlink CSI at the transmitter in many wireless systems, CSI...
In this work, we propose a novel deep learning-based framework for the adaptive configuration of DMRS used for MIMO CCE. Specifically, a neural network architecture is proposed at the terminal side which based on statistical learning indicates to the network the preferred configuration of DMRS in time, frequency, and code...
Next generation Terabit per second (Tbps) wireless communication systems aim for sub-THz and THz bands where noise and hardware impairments are known to be dominantly non-linear and lack accurate closed form analytical models. The physical layer (PHY) blocks designed under linearity and Gaussian noise assumptions will fall short of satisfying...