  Multiuser massive multiple-input multiple-output (MU-MIMO) systems can be
used to meet high throughput requirements of 5G and beyond networks. In an
uplink MUMIMO system, a base station is serving a large number of users,
leading to a strong multi-user interference (MUI). Designing a high performance
detector in the presence of a strong MUI is a challenging problem. This work
proposes a novel detector based on the concepts of expectation propagation (EP)
and graph neural network, referred to as the GEPNet detector, addressing the
limitation of the independent Gaussian approximation in EP. The simulation
results show that the proposed GEPNet detector significantly outperforms the
state-of-the-art MU-MIMO detectors in strong MUI scenarios with equal number of
transmit and receive antennas.
