  In this paper, we propose a novel cooperative multi-relay transmission scheme
for mobile terminals to exploit spatial diversity. By improving the timeliness
of measured channel state information (CSI) through deep learning (DL)-based
channel prediction, the proposed scheme remarkably lowers the probability of
wrong relay selection arising from outdated CSI in fast time-varying channels.
It inherits the simplicity of opportunistic relaying by selecting a single
relay, avoiding the complexity of multi-relay coordination and synchronization.
Numerical results reveal that it can achieve full diversity gain in slow-fading
channels and substantially outperforms the existing schemes in fast-fading
wireless environments. Moreover, the computational complexity brought by the DL
predictor is negligible compared to off-the-shelf computing hardware.
