Abstract
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.
PDF Article
More Like This
Cited By
You do not have subscription access to this journal. Cited by links are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.
Contact your librarian or system administrator
or
Login to access Optica Member Subscription