One-Bit Quantized Channel Prediction with Neural Networks

Nurettin Turan, Michael Koller, Wolfgang Utschick

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

We study the problem of predicting channel coefficients from one-bit quantized observations in an environment of a moving user who sends pilots to a base station. To start with, we propose a prediction algorithm which consists of two stages. The first stage aims at reconstructing the high-resolution (pre-quantization) receive signal. The second stage then predicts channel coefficients from this reconstructed signal. A drawback of this algorithm is that certain second moments of the channel statistics are required. In case of high-resolution (no quantization) observations, a recently introduced neural network based approach was able to predict channels even without the use of second order statistics. A low-SNR formulation of the proposed two stage algorithm motivates us to employ the neural network based method also in the case of one-bit quantization. Numerical simulations demonstrate the validity of this approach. We observe that the obtained channel predictor can compete with the algorithm that makes use of the second order statistics.

Original languageEnglish
Title of host publication2021 IEEE 32nd Annual International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages604-609
Number of pages6
ISBN (Electronic)9781728175867
DOIs
StatePublished - 13 Sep 2021
Event32nd IEEE Annual International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC 2021 - Virtual, Helsinki, Finland
Duration: 13 Sep 202116 Sep 2021

Publication series

NameIEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC
Volume2021-September

Conference

Conference32nd IEEE Annual International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC 2021
Country/TerritoryFinland
CityVirtual, Helsinki
Period13/09/2116/09/21

Keywords

  • channel prediction
  • neural networks
  • one-bit quantization
  • time-variant channel state information

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