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We propose a novel soft-output joint channel estimation and data detection(JED) algorithm for multiuser (MU) multiple-input multiple-output (MIMO)wireless communication systems. Our algorithm approximately solves a maximuma-posteriori JED optimization problem using deep unfolding and generatessoft-output information for the transmitted bits in every iteration. Theparameters of the unfolded algorithm are computed by a hyper-network that istrained with a binary cross entropy (BCE) loss. We evaluate the performance ofour algorithm in a coded MU-MIMO system with 8 basestation antennas and 4 userequipments and compare it to state-of-the-art algorithms separate channelestimation from soft-output data detection. Our results demonstrate that ourJED algorithm outperforms such data detectors with as few as 10 iterations.

Soft-Output Joint Channel Estimation and Data Detection using Deep Unfolding