The Extended SLM Combined Autoencoder of the PAPR Reduction Scheme in DCO-OFDM Systems

End-to-end learning in optical communication systems is a promising technique to solve difficult communication problems, especially for peak to average power ratio (PAPR) reduction in orthogonal frequency division multiplexing (OFDM) systems. The less complex, highly adaptive hardware and advantages...

Full description

Saved in:
Bibliographic Details
Published in:Applied sciences 2019, Vol.9 (5), p.852
Main Authors: Hao, Lili, Wang, Dongyi, Tao, Yang, Cheng, Wenyong, Li, Jing, Liu, Zehan
Format: Article
Language:English
Subjects:
Adaptive systems
Algorithms
autoencoder
Bit error rate
Communication
Communications systems
Constellations
Deep learning
Distribution functions
end-to-end learning
Fourier transforms
Mapping
Methods
Neural networks
Optical communication
Optical wireless
Orthogonal Frequency Division Multiplexing
peak-to-average power ratio
Photonics
Subcarriers
Wireless networks
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:End-to-end learning in optical communication systems is a promising technique to solve difficult communication problems, especially for peak to average power ratio (PAPR) reduction in orthogonal frequency division multiplexing (OFDM) systems. The less complex, highly adaptive hardware and advantages in the analysis of unknown or complex channels make deep learning a valid tool to improve system performance. In this paper, we propose an autoencoder network combined with extended selected mapping methods (ESLM-AE) to reduce the PAPR for the DC-biased optical OFDM system and to minimize the bit error rate (BER). The constellation mapping/de-mapping of the transmitted symbols and the phase factor of each subcarrier are acquired and optimized adaptively by training the autoencoder with a combined loss function. In the loss function, both the PAPR and BER performance are taken into account. The simulation results show that a significant PAPR reduction of more than 10 dB has been achieved by using the ESLM-AE scheme in terms of the complementary cumulative distribution function. Furthermore, the proposed scheme exhibits better BER performance compared to the standard PAPR reduction methods.
ISSN:2076-3417
2076-3417
DOI:10.3390/app9050852