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Predictive Relay Selection: A Cooperative Diversity Scheme Using Deep Learning

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posted on 08.02.2021, 16:47 by Wei Jiang, Hans Dieter Schotten
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channel prediction, the proposed scheme remarkably lowers the probability of wrong relay selection arising from outdated CSI in fast time-varying channels.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.

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Email Address of Submitting Author

wei.jiang@dfki.de

ORCID of Submitting Author

https://orcid.org/0000-0002-3719-3710

Submitting Author's Institution

German Research Center for Artificial Intelligence (DFKI)

Submitting Author's Country

Germany

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