Preprint Article Version 1 This version is not peer-reviewed

Initial Results on Deep Learning-Based Pilot Contamination Mitigation in Massive MIMO Systems

Version 1 : Received: 7 July 2019 / Approved: 14 August 2019 / Online: 14 August 2019 (16:01:48 CEST)

How to cite: Pereira de Figueiredo, F.A. Initial Results on Deep Learning-Based Pilot Contamination Mitigation in Massive MIMO Systems. Preprints 2019, 2019080165 (doi: 10.20944/preprints201908.0165.v1). Pereira de Figueiredo, F.A. Initial Results on Deep Learning-Based Pilot Contamination Mitigation in Massive MIMO Systems. Preprints 2019, 2019080165 (doi: 10.20944/preprints201908.0165.v1).

Abstract

In this brief letter we report our initial results on the application of deep-learning to the massive MIMO channel estimation challenge. We show that it is possible to estimate wireless channels and that the possibility of mitigating pilot-contamination with deep-learning is possible given that the leaning model underwent an extensive training-phase and that it has been presented with a large number of different channel conditions.

Subject Areas

massive MIMO; pilot contamination; deep learning; machine learning

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