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Periodicity-Enabled Size Reduction of Symbol Based Predistortion for High-Order QAM

We experimentally demonstrate a novel size reduction approach for symbol-based look-up table (LUT) digital predistortion (DPD) of the transmitter impairments taking advantage of the periodicity in the pattern-dependent distortions. Compared to other reduced-size LUT schemes, the proposed method can significantly lessen the storage memory requirements with negligible performance penalty for high-order modulation formats. To further alleviate the storage memory restriction, a twice reduced-size LUT scheme is proposed to provide further size reduction. Importantly, given a targeted memory length, we verify the importance of averaging over sufficient occurrences of the patterns to obtain a well-performing LUT. Moreover, it is necessary to evaluate the performance of LUT-based DPD using random data. Finally, we demonstrate a neural network (NN) based nonlinear predistortion technique, which achieves nearly identical performance to the full-size LUT for all employed constellations and is robust against a change of modulation format. The proposed techniques are verified in a back-to-back transmission experiment of 20 Gbaud 64-QAM, 256-QAM, and 1024-QAM signals considering 3 and 5 symbol memory. The performance of the LUT-based DPD is further validated in a noise loading experiment.

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Informasi Detail

Judul Seri

JOURNAL OF LIGHTWAVE TECHNOLOGY; Vol.40 No.18 September 15 2022

No. Panggil

-

Penerbit

: .,

Deskripsi Fisik

p. 6168-6178

Bahasa

English

ISBN/ISSN

-

Klasifikasi

NONE

Tipe Isi

-

Tipe Media

-

Tipe Pembawa

-

Edisi

-

Subjek

SIGNAL PROCESSING
NEURAL NETWORK
LOOK-UP TABLE
PREDISTORTION
TRANSMITTER NONLINEARITY COMPENSATION

Info Detail Spesifik

DOI: 10.1109/JLT.2022.3191464

Pernyataan Tanggungjawab

Zonglong He, Jinxiang Song, Kovendhan Vijayan, Christian Hager, Alexandre Graell i Amat, Henk Wymeersch, Peter A. Andrekson, Magnus Karlsson, Jochen Schroder

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