Abstract
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lowers the probability of wrong relay selection arising from outdated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.