… a deep detector with an architecture which is specifically designed for MIMO detection that
… have presented deep neural networks as a general framework for MIMO detection. We have …

… for MIMO detectors, which can automatically determine internal parameters of an unfolding-based
MIMO detector to … expectation propagation-based MIMO detector. In particular, we …

… We present optimal and near-optimal detection principles specifically designed for the …
-scale MIMO detection for the sake of designing complexity-scalable MIMO detection algorithms …

… We consider a specific model-driven NN-based MIMO detector that can be trained on the
basis of channel statistics rather than channel realizations to solve the first problem. A meta …

… Our network uses different linear estimators … network more flexible. Different from these
works in [14], [16], which are only designed for a fixed channel, our network can perform MIMO …

… Finally, we would like to mention that the linear MIMO detector can also be designed from
the perspective of a linear equalizer [253], [377], since the mathematical models of the …

… tion of its inference (online) detection computational cost … network.based MIMO detector
design, where com. plexity can be adjusted at inference while achieving a competitive detection …

… instance-wise models for the MIMO detection problem as a case study. Inspired by the
layer upon layer structures of MIMO detectors, we will design instance-wise models that have …

… [53] proposed to design the structure of the detection network by unfolding the conjugate
gradient method and ISTA, respectively, which have achieved promising results for massive …

… The model-driven DL detectors are designed from the traditional iterative detection algorithms,
each layer of which represents a single iteration with added trainable parameters [21]–[23]…