Deep Receiver Design for Multi-carrier Waveforms Using CNNs

Yasin Yildirim, Sedat Ozer, Hakan Ali Cirpan

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

2 Citations (Scopus)

Abstract

In this paper, a deep learning based receiver is proposed for a collection of multi-carrier wave-forms including both current and next-generation wireless communication systems. In particular, we propose to use a convolutional neural network (CNN) for jointly detection and demodulation of the received signal at the receiver in wireless environments. We compare our proposed architecture to the classical methods and demonstrate that our proposed CNN-based architecture can perform better on different multi-carrier forms including OFDM and GFDM in various simulations. Furthermore, we compare the total number of required parameters for each network for memory requirements.

Original languageEnglish
Title of host publication2020 43rd International Conference on Telecommunications and Signal Processing, TSP 2020
EditorsNorbert Herencsar
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages31-36
Number of pages6
ISBN (Electronic)9781728163765
DOIs
Publication statusPublished - Jul 2020
Event43rd International Conference on Telecommunications and Signal Processing, TSP 2020 - Milan, Italy
Duration: 7 Jul 20209 Jul 2020

Publication series

Name2020 43rd International Conference on Telecommunications and Signal Processing, TSP 2020

Conference

Conference43rd International Conference on Telecommunications and Signal Processing, TSP 2020
Country/TerritoryItaly
CityMilan
Period7/07/209/07/20

Bibliographical note

Publisher Copyright:
© 2020 IEEE.

Funding

This work was partially supported by TUBITAK’s 2232: International Fellowship for Outstanding Researchers program (Project No: 118C356), however, that support does not necessarily mean that TUBITAK also supports all the content and comments made in this paper.

FundersFunder number
TUBITAK118C356

    Keywords

    • CNN
    • Deep Learning
    • Deep Receiver Design
    • GFDM
    • Multi-carrier Wave-forms
    • OFDM

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