Details
| Originalsprache | Englisch |
|---|---|
| Titel des Sammelwerks | 2018 15th International Symposium on Wireless Communication Systems (ISWCS) |
| Herausgeber (Verlag) | VDE Verlag GmbH |
| Seitenumfang | 6 |
| ISBN (elektronisch) | 9781538650059 |
| ISBN (Print) | 9781538650066 |
| Publikationsstatus | Veröffentlicht - 15 Okt. 2018 |
| Veranstaltung | 15th International Symposium on Wireless Communication Systems, ISWCS 2018 - Lisbon, Portugal Dauer: 28 Aug. 2018 → 31 Aug. 2018 |
Publikationsreihe
| Name | Proceedings of the International Symposium on Wireless Communication Systems |
|---|---|
| ISSN (Print) | 2154-0217 |
| ISSN (elektronisch) | 2154-0225 |
Abstract
One of the key issues of Digital Radio Mondiale (DRM) is green broadcasting. For wide area coverage, the use of high-power transmitters is essential. However, the applied transmission technology based on Orthogonal Frequency Division Multiplexing (OFDM) results in non-linearities in the emitted signal, low power efficiency, and high costs of transmitters. Digital predistortion is a promising scheme for power amplifier (PA) linearization. This paper presents an efficient approach to estimate the parameters of a digital predistorter based on adaptive filtering with direct learning architecture (DLA). A well-known algorithm for identifying and tracking the timevarying parameters of an unknown system is the recursive least squares (RLS) method with exponential/directional forgetting. In this paper, the efficiency of both exponential/directional forgetting techniques is investigated for different degrees of PA nonlinearities. On this basis, a new hybrid technique based on statistical properties of the PA input signal is proposed. The evaluation results show that for both scenarios, the statistic-based forgetting technique not only provides better accuracy but also is more robust against high PA nonlinearities.
ASJC Scopus Sachgebiete
- Informatik (insg.)
- Computernetzwerke und -kommunikation
- Ingenieurwesen (insg.)
- Elektrotechnik und Elektronik
- Sozialwissenschaften (insg.)
- Kommunikation
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2018 15th International Symposium on Wireless Communication Systems (ISWCS). VDE Verlag GmbH, 2018. (Proceedings of the International Symposium on Wireless Communication Systems).
Publikation: Beitrag in Buch/Bericht/Sammelwerk/Konferenzband › Aufsatz in Konferenzband › Forschung › Peer-Review
}
TY - GEN
T1 - Use of Statistical Signal Properties for Adaptive Predistortion of High Power Amplifiers
AU - Moghaddamnia, Sanam
AU - Fuhrwerk, Martin
AU - Peissig, Jurgen
N1 - Publisher Copyright: © 2018 IEEE. Copyright: Copyright 2018 Elsevier B.V., All rights reserved.
PY - 2018/10/15
Y1 - 2018/10/15
N2 - One of the key issues of Digital Radio Mondiale (DRM) is green broadcasting. For wide area coverage, the use of high-power transmitters is essential. However, the applied transmission technology based on Orthogonal Frequency Division Multiplexing (OFDM) results in non-linearities in the emitted signal, low power efficiency, and high costs of transmitters. Digital predistortion is a promising scheme for power amplifier (PA) linearization. This paper presents an efficient approach to estimate the parameters of a digital predistorter based on adaptive filtering with direct learning architecture (DLA). A well-known algorithm for identifying and tracking the timevarying parameters of an unknown system is the recursive least squares (RLS) method with exponential/directional forgetting. In this paper, the efficiency of both exponential/directional forgetting techniques is investigated for different degrees of PA nonlinearities. On this basis, a new hybrid technique based on statistical properties of the PA input signal is proposed. The evaluation results show that for both scenarios, the statistic-based forgetting technique not only provides better accuracy but also is more robust against high PA nonlinearities.
AB - One of the key issues of Digital Radio Mondiale (DRM) is green broadcasting. For wide area coverage, the use of high-power transmitters is essential. However, the applied transmission technology based on Orthogonal Frequency Division Multiplexing (OFDM) results in non-linearities in the emitted signal, low power efficiency, and high costs of transmitters. Digital predistortion is a promising scheme for power amplifier (PA) linearization. This paper presents an efficient approach to estimate the parameters of a digital predistorter based on adaptive filtering with direct learning architecture (DLA). A well-known algorithm for identifying and tracking the timevarying parameters of an unknown system is the recursive least squares (RLS) method with exponential/directional forgetting. In this paper, the efficiency of both exponential/directional forgetting techniques is investigated for different degrees of PA nonlinearities. On this basis, a new hybrid technique based on statistical properties of the PA input signal is proposed. The evaluation results show that for both scenarios, the statistic-based forgetting technique not only provides better accuracy but also is more robust against high PA nonlinearities.
KW - Adaptive linearization
KW - Digital broadcasting
KW - Digital predistortion
KW - Drm+
KW - Nonlinear power amplification
UR - http://www.scopus.com/inward/record.url?scp=85056702654&partnerID=8YFLogxK
U2 - 10.1109/ISWCS.2018.8491222
DO - 10.1109/ISWCS.2018.8491222
M3 - Conference contribution
AN - SCOPUS:85056702654
SN - 9781538650066
T3 - Proceedings of the International Symposium on Wireless Communication Systems
BT - 2018 15th International Symposium on Wireless Communication Systems (ISWCS)
PB - VDE Verlag GmbH
T2 - 15th International Symposium on Wireless Communication Systems, ISWCS 2018
Y2 - 28 August 2018 through 31 August 2018
ER -