Low-Complexity Feedback Data Compression for Closed-Loop Digital Predistortion

Arne Fischer-Buhner; Lauri Anttila; Vishnu Unnikrishnan; Manil Dev Gomony; Mikko Valkama

doi:10.1109/IMS37964.2023.10188025

Low-Complexity Feedback Data Compression for Closed-Loop Digital Predistortion

Arne Fischer-Buhner, Lauri Anttila, Vishnu Unnikrishnan, Manil Dev Gomony, Mikko Valkama

Sähkötekniikka

Tutkimustuotos: Konferenssiartikkeli › Tieteellinen › vertaisarvioitu

27 Lataukset (Pure)

Abstrakti

This paper proposes sample combining as a low-complex and effective feedback data compression technique that allows to significantly reduce the computational effort and buffering needs for parameter adaptation in a closed-loop digital predistortion (DPD) system. Compression is achieved by applying an integrate & dump operation to an undersampled feedback signal. The proposed method is experimentally validated for RF measurement based behavioral modeling as well as closed-loop DPD of a 3.5 GHz GaN Doherty PA, taking also quantization effects of the feedback path into account. Our results demonstrate that the proposed technique is as capable as state-of-the-art histogram-based sample selection, however, at a much lower complexity.

Alkuperäiskieli	Englanti
Otsikko	2023 IEEE/MTT-S International Microwave Symposium, IMS 2023
Kustantaja	IEEE
Sivut	795-798
Sivumäärä	4
ISBN (elektroninen)	9798350347647
DOI - pysyväislinkit	https://doi.org/10.1109/IMS37964.2023.10188025
Tila	Julkaistu - 2023
OKM-julkaisutyyppi	A4 Artikkeli konferenssijulkaisussa
Tapahtuma	IEEE/MTT-S International Microwave Symposium - San Diego, Yhdysvallat Kesto: 11 kesäk. 2023 → 16 kesäk. 2023

Julkaisusarja

Nimi	IEEE MTT-S International Microwave Symposium Digest
Vuosikerta	2023-June
ISSN (painettu)	0149-645X

Conference

Conference	IEEE/MTT-S International Microwave Symposium
Maa/Alue	Yhdysvallat
Kaupunki	San Diego
Ajanjakso	11/06/23 → 16/06/23

Rahoitus

V. CONCLUSION Sample combining for low-complexity feedback signal compression for DPD model adaptation was proposed in this paper. Despite the simplicity of the method, the presented experiments show that solid performances for PA behavioral modeling or closed-loop DPD can be reached with a significantly reduced data volume with the proposed method, while taking also a low-resolution quantization into account. The method was demonstrated to achieve similar performances as histogram-based sample selection, however with negligible added complexity. It is thus well suited for implementation. At the same time, the ADC rate and bit-width can be reduced, reducing the overall data load of the DPD system. ACKNOWLEDGMENT This project was funded by EU Horizon 2020 under the Marie Skłodowska-Curie grant agreement No. 860921, and by Academy of Finland under grants 319994, 338224, 332361. REFERENCES

Julkaisufoorumi-taso

Jufo-taso 1

!!ASJC Scopus subject areas

Radiation
Condensed Matter Physics
Electrical and Electronic Engineering

Pääsy asiakirjaan

10.1109/IMS37964.2023.10188025

Low-Complexity Feedback
This publication is copyrighted. You may download, display and print it for Your own personal use. Commercial use is prohibited.
Accepted author manuscript, 318 KBLisenssi: Unspecified

https://urn.fi/URN:NBN:fi:tuni-202309088062Lisenssi: Unspecified

Siteeraa tätä

Fischer-Buhner, A., Anttila, L., Unnikrishnan, V., Gomony, M. D., & Valkama, M. (2023). Low-Complexity Feedback Data Compression for Closed-Loop Digital Predistortion. teoksessa 2023 IEEE/MTT-S International Microwave Symposium, IMS 2023 (Sivut 795-798). (IEEE MTT-S International Microwave Symposium Digest; Vuosikerta 2023-June). IEEE. https://doi.org/10.1109/IMS37964.2023.10188025

@inproceedings{bf3cc47a8494491889e2d2b9e963f1bf,

title = "Low-Complexity Feedback Data Compression for Closed-Loop Digital Predistortion",

abstract = "This paper proposes sample combining as a low-complex and effective feedback data compression technique that allows to significantly reduce the computational effort and buffering needs for parameter adaptation in a closed-loop digital predistortion (DPD) system. Compression is achieved by applying an integrate & dump operation to an undersampled feedback signal. The proposed method is experimentally validated for RF measurement based behavioral modeling as well as closed-loop DPD of a 3.5 GHz GaN Doherty PA, taking also quantization effects of the feedback path into account. Our results demonstrate that the proposed technique is as capable as state-of-the-art histogram-based sample selection, however, at a much lower complexity.",

keywords = "Behavioral modeling, closed-loop adaptation, digital predistortion (DPD), low-complexity, power amplifier (PA)",

author = "Arne Fischer-Buhner and Lauri Anttila and Vishnu Unnikrishnan and Gomony, {Manil Dev} and Mikko Valkama",

note = "Funding Information: V. CONCLUSION Sample combining for low-complexity feedback signal compression for DPD model adaptation was proposed in this paper. Despite the simplicity of the method, the presented experiments show that solid performances for PA behavioral modeling or closed-loop DPD can be reached with a significantly reduced data volume with the proposed method, while taking also a low-resolution quantization into account. The method was demonstrated to achieve similar performances as histogram-based sample selection, however with negligible added complexity. It is thus well suited for implementation. At the same time, the ADC rate and bit-width can be reduced, reducing the overall data load of the DPD system. ACKNOWLEDGMENT This project was funded by EU Horizon 2020 under the Marie Sk{\l}odowska-Curie grant agreement No. 860921, and by Academy of Finland under grants 319994, 338224, 332361. REFERENCES Publisher Copyright: {\textcopyright} 2023 IEEE.; IEEE/MTT-S International Microwave Symposium ; Conference date: 11-06-2023 Through 16-06-2023",

year = "2023",

doi = "10.1109/IMS37964.2023.10188025",

language = "English",

series = "IEEE MTT-S International Microwave Symposium Digest",

publisher = "IEEE",

pages = "795--798",

booktitle = "2023 IEEE/MTT-S International Microwave Symposium, IMS 2023",

address = "United States",

}

Fischer-Buhner, A , Anttila, L , Unnikrishnan, V, Gomony, MD & Valkama, M 2023, Low-Complexity Feedback Data Compression for Closed-Loop Digital Predistortion. julkaisussa 2023 IEEE/MTT-S International Microwave Symposium, IMS 2023. IEEE MTT-S International Microwave Symposium Digest, Vuosikerta 2023-June, IEEE, Sivut 795-798, IEEE/MTT-S International Microwave Symposium, San Diego, Yhdysvallat, 11/06/23. https://doi.org/10.1109/IMS37964.2023.10188025

Low-Complexity Feedback Data Compression for Closed-Loop Digital Predistortion. / Fischer-Buhner, Arne ; Anttila, Lauri ; Unnikrishnan, Vishnu et al.
2023 IEEE/MTT-S International Microwave Symposium, IMS 2023. IEEE, 2023. s. 795-798 (IEEE MTT-S International Microwave Symposium Digest; Vuosikerta 2023-June).

Tutkimustuotos: Konferenssiartikkeli › Tieteellinen › vertaisarvioitu

TY - GEN

T1 - Low-Complexity Feedback Data Compression for Closed-Loop Digital Predistortion

AU - Fischer-Buhner, Arne

AU - Anttila, Lauri

AU - Unnikrishnan, Vishnu

AU - Gomony, Manil Dev

AU - Valkama, Mikko

N1 - Funding Information: V. CONCLUSION Sample combining for low-complexity feedback signal compression for DPD model adaptation was proposed in this paper. Despite the simplicity of the method, the presented experiments show that solid performances for PA behavioral modeling or closed-loop DPD can be reached with a significantly reduced data volume with the proposed method, while taking also a low-resolution quantization into account. The method was demonstrated to achieve similar performances as histogram-based sample selection, however with negligible added complexity. It is thus well suited for implementation. At the same time, the ADC rate and bit-width can be reduced, reducing the overall data load of the DPD system. ACKNOWLEDGMENT This project was funded by EU Horizon 2020 under the Marie Skłodowska-Curie grant agreement No. 860921, and by Academy of Finland under grants 319994, 338224, 332361. REFERENCES Publisher Copyright: © 2023 IEEE.

PY - 2023

Y1 - 2023

N2 - This paper proposes sample combining as a low-complex and effective feedback data compression technique that allows to significantly reduce the computational effort and buffering needs for parameter adaptation in a closed-loop digital predistortion (DPD) system. Compression is achieved by applying an integrate & dump operation to an undersampled feedback signal. The proposed method is experimentally validated for RF measurement based behavioral modeling as well as closed-loop DPD of a 3.5 GHz GaN Doherty PA, taking also quantization effects of the feedback path into account. Our results demonstrate that the proposed technique is as capable as state-of-the-art histogram-based sample selection, however, at a much lower complexity.

AB - This paper proposes sample combining as a low-complex and effective feedback data compression technique that allows to significantly reduce the computational effort and buffering needs for parameter adaptation in a closed-loop digital predistortion (DPD) system. Compression is achieved by applying an integrate & dump operation to an undersampled feedback signal. The proposed method is experimentally validated for RF measurement based behavioral modeling as well as closed-loop DPD of a 3.5 GHz GaN Doherty PA, taking also quantization effects of the feedback path into account. Our results demonstrate that the proposed technique is as capable as state-of-the-art histogram-based sample selection, however, at a much lower complexity.

KW - Behavioral modeling

KW - closed-loop adaptation

KW - digital predistortion (DPD)

KW - low-complexity

KW - power amplifier (PA)

U2 - 10.1109/IMS37964.2023.10188025

DO - 10.1109/IMS37964.2023.10188025

M3 - Conference contribution

AN - SCOPUS:85168545734

T3 - IEEE MTT-S International Microwave Symposium Digest

SP - 795

EP - 798

BT - 2023 IEEE/MTT-S International Microwave Symposium, IMS 2023

PB - IEEE

T2 - IEEE/MTT-S International Microwave Symposium

Y2 - 11 June 2023 through 16 June 2023

ER -

Low-Complexity Feedback Data Compression for Closed-Loop Digital Predistortion

Abstrakti

Julkaisusarja

Conference

Rahoitus

Julkaisufoorumi-taso

!!ASJC Scopus subject areas

Pääsy asiakirjaan

Sormenjälki

Siteeraa tätä