Accelerated Over-The-Air Neural Receiver Training Using Self-Contrastive Learning

Corey D. Cooke; Nicholas C. Neel; Hayden T. Waddle; Doug A. Mann; Tyler W. McCormick

doi:10.1109/ICMLCN64995.2025.11140337

Accelerated Over-The-Air Neural Receiver Training Using Self-Contrastive Learning

Corey D. Cooke, Nicholas C. Neel, Hayden T. Waddle, Doug A. Mann, Tyler W. McCormick

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Self-contrastive learning (SCL), a self-supervised learning method, has been shown to improve image and signal classifier accuracies and reduce the training time for neural communications receivers. In particular, prior work has shown that SCL applied as a pre-training step can improve simulated performance of OFDM in 3GPP TDL channel models by reducing the training time of the downstream classification task (demodulation and demapping). In this work a practical implementation demonstrating SCL pre-training using software defined radios (SDRs) is proposed.

Original language	English
Title of host publication	2025 IEEE International Conference on Machine Learning for Communication and Networking, ICMLCN 2025
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9798331520427
DOIs	https://doi.org/10.1109/ICMLCN64995.2025.11140337
State	Published - 2025
Event	2nd IEEE International Conference on Machine Learning for Communication and Networking, ICMLCN 2025 - Barcelona, Spain Duration: May 26 2025 → May 29 2025

Publication series

Name	2025 IEEE International Conference on Machine Learning for Communication and Networking, ICMLCN 2025

Conference

Conference	2nd IEEE International Conference on Machine Learning for Communication and Networking, ICMLCN 2025
Country/Territory	Spain
City	Barcelona
Period	05/26/25 → 05/29/25

Funding

This manuscript has been authored, in part, by UT-Battelle, LLC under Contract No. DE-AC05-000R22725 with the U.S. Department of Energy. The US government retains and the publisher, by accepting the article for publication, acknowledges that the US government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this manuscript, or allow others to do so, for US government purposes. DOE will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (http://energy.gov/downloads/doe-public-access-plan)

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10.1109/ICMLCN64995.2025.11140337

Cite this

Cooke, C. D., Neel, N. C., Waddle, H. T., Mann, D. A., & McCormick, T. W. (2025). Accelerated Over-The-Air Neural Receiver Training Using Self-Contrastive Learning. In 2025 IEEE International Conference on Machine Learning for Communication and Networking, ICMLCN 2025 (2025 IEEE International Conference on Machine Learning for Communication and Networking, ICMLCN 2025). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICMLCN64995.2025.11140337

Cooke, Corey D. ; Neel, Nicholas C. ; Waddle, Hayden T. et al. / Accelerated Over-The-Air Neural Receiver Training Using Self-Contrastive Learning. 2025 IEEE International Conference on Machine Learning for Communication and Networking, ICMLCN 2025. Institute of Electrical and Electronics Engineers Inc., 2025. (2025 IEEE International Conference on Machine Learning for Communication and Networking, ICMLCN 2025).

@inproceedings{09fa65384e1142baae73f79adaf66c7a,

title = "Accelerated Over-The-Air Neural Receiver Training Using Self-Contrastive Learning",

abstract = "Self-contrastive learning (SCL), a self-supervised learning method, has been shown to improve image and signal classifier accuracies and reduce the training time for neural communications receivers. In particular, prior work has shown that SCL applied as a pre-training step can improve simulated performance of OFDM in 3GPP TDL channel models by reducing the training time of the downstream classification task (demodulation and demapping). In this work a practical implementation demonstrating SCL pre-training using software defined radios (SDRs) is proposed.",

author = "Cooke, \{Corey D.\} and Neel, \{Nicholas C.\} and Waddle, \{Hayden T.\} and Mann, \{Doug A.\} and McCormick, \{Tyler W.\}",

note = "Publisher Copyright: {\textcopyright} 2025 IEEE.; 2nd IEEE International Conference on Machine Learning for Communication and Networking, ICMLCN 2025 ; Conference date: 26-05-2025 Through 29-05-2025",

year = "2025",

doi = "10.1109/ICMLCN64995.2025.11140337",

language = "English",

series = "2025 IEEE International Conference on Machine Learning for Communication and Networking, ICMLCN 2025",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

booktitle = "2025 IEEE International Conference on Machine Learning for Communication and Networking, ICMLCN 2025",

}

Cooke, CD, Neel, NC, Waddle, HT, Mann, DA & McCormick, TW 2025, Accelerated Over-The-Air Neural Receiver Training Using Self-Contrastive Learning. in 2025 IEEE International Conference on Machine Learning for Communication and Networking, ICMLCN 2025. 2025 IEEE International Conference on Machine Learning for Communication and Networking, ICMLCN 2025, Institute of Electrical and Electronics Engineers Inc., 2nd IEEE International Conference on Machine Learning for Communication and Networking, ICMLCN 2025, Barcelona, Spain, 05/26/25. https://doi.org/10.1109/ICMLCN64995.2025.11140337

Accelerated Over-The-Air Neural Receiver Training Using Self-Contrastive Learning. / Cooke, Corey D.; Neel, Nicholas C.; Waddle, Hayden T. et al.
2025 IEEE International Conference on Machine Learning for Communication and Networking, ICMLCN 2025. Institute of Electrical and Electronics Engineers Inc., 2025. (2025 IEEE International Conference on Machine Learning for Communication and Networking, ICMLCN 2025).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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T1 - Accelerated Over-The-Air Neural Receiver Training Using Self-Contrastive Learning

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AU - Neel, Nicholas C.

AU - Waddle, Hayden T.

AU - Mann, Doug A.

AU - McCormick, Tyler W.

PY - 2025

Y1 - 2025

N2 - Self-contrastive learning (SCL), a self-supervised learning method, has been shown to improve image and signal classifier accuracies and reduce the training time for neural communications receivers. In particular, prior work has shown that SCL applied as a pre-training step can improve simulated performance of OFDM in 3GPP TDL channel models by reducing the training time of the downstream classification task (demodulation and demapping). In this work a practical implementation demonstrating SCL pre-training using software defined radios (SDRs) is proposed.

AB - Self-contrastive learning (SCL), a self-supervised learning method, has been shown to improve image and signal classifier accuracies and reduce the training time for neural communications receivers. In particular, prior work has shown that SCL applied as a pre-training step can improve simulated performance of OFDM in 3GPP TDL channel models by reducing the training time of the downstream classification task (demodulation and demapping). In this work a practical implementation demonstrating SCL pre-training using software defined radios (SDRs) is proposed.

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U2 - 10.1109/ICMLCN64995.2025.11140337

DO - 10.1109/ICMLCN64995.2025.11140337

M3 - Conference contribution

AN - SCOPUS:105016778226

T3 - 2025 IEEE International Conference on Machine Learning for Communication and Networking, ICMLCN 2025

BT - 2025 IEEE International Conference on Machine Learning for Communication and Networking, ICMLCN 2025

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2nd IEEE International Conference on Machine Learning for Communication and Networking, ICMLCN 2025

Y2 - 26 May 2025 through 29 May 2025

ER -

Cooke CD, Neel NC, Waddle HT, Mann DA , McCormick TW. Accelerated Over-The-Air Neural Receiver Training Using Self-Contrastive Learning. In 2025 IEEE International Conference on Machine Learning for Communication and Networking, ICMLCN 2025. Institute of Electrical and Electronics Engineers Inc. 2025. (2025 IEEE International Conference on Machine Learning for Communication and Networking, ICMLCN 2025). doi: 10.1109/ICMLCN64995.2025.11140337

Accelerated Over-The-Air Neural Receiver Training Using Self-Contrastive Learning

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