End-to-End Learning of Constellation Shaping for Optical Fiber Communication Systems

End-to-end learning based on autoencoder can realize robust constellation shaping for optical fiber communications. The existing schemes use the symbol-wise autoencoder (SAE) or bit-wise autoencoder (BAE) to realize the constellation shaping. The SAE mainly focus on the performance of mutual information (MI), this neglects the decoding loss so that the generalized mutual information (GMI) or the post forward error correction (FEC) bit error rate (BER) has almost no performance gain in bit-wise metric systems. In this paper, we propose a probabilistic shaping (PS) based on BAE with a modified loss function, where the mean square error and source entropy are used to construct the loss function. We compare the GMI and post-FEC performance of the PS and also geometric shaping (GS) based on SAE or BAE by numerical simulations and experiments. In simulations, we transmit 64-QAM signal with GS or PS over 100-km SSFM. The simulation results show that the GS or PS based on BAE can achieve 0.13-bits/sym or beyond 0.2-bits/sym GMI gain. In experiment, the GS based on BAE obtains 0.11-bits/sym GMI gain and 0.7-dB launch optical power gain after belief propagation decoding. The PS with source entropy of 5.5-bits/sym and 5.2-bits/sym outperforms uniform 64-QAM by 0.25-bits/sym and 0.3-bits/sym, respectively

Efficient biosynthesis of (R)-mandelic acid from styrene oxide by an adaptive evolutionary Gluconobacter oxydans STA

Abstract Background (R)-mandelic acid (R-MA) is a highly valuable hydroxyl acid in the pharmaceutical industry. However, biosynthesis of optically pure R-MA remains significant challenges, including the lack of suitable catalysts and high toxicity to host strains. Adaptive laboratory evolution (ALE) was a promising and powerful strategy to obtain specially evolved strains. Results Herein, we report a new cell factory of the Gluconobacter oxydans to biocatalytic styrene oxide into R-MA by utilizing the G. oxydans endogenous efficiently incomplete oxidization and the epoxide hydrolase (SpEH) heterologous expressed in G. oxydans. With a new screened strong endogenous promoter P 12780 , the production of R-MA was improved to 10.26 g/L compared to 7.36 g/L of using P lac . As R-MA showed great inhibition for the reaction and toxicity to cell growth, adaptive laboratory evolution (ALE) strategy was introduced to improve the cellular R-MA tolerance. The adapted strain that can tolerate 6 g/L R-MA was isolated (named G. oxydans STA), while the wild-type strain cannot grow under this stress. The conversion rate was increased from 0.366 g/L/h of wild type to 0.703 g/L/h by the recombinant STA, and the final R-MA titer reached 14.06 g/L. Whole-genome sequencing revealed multiple gene-mutations in STA, in combination with transcriptome analysis under R-MA stress condition, we identified five critical genes that were associated with R-MA tolerance, among which AcrA overexpression could further improve R-MA titer to 15.70 g/L, the highest titer reported from bulk styrene oxide substrate. Conclusions The microbial engineering with systematic combination of static regulation, ALE, and transcriptome analysis strategy provides valuable solutions for high-efficient chemical biosynthesis, and our evolved G. oxydans would be better to serve as a chassis cell for hydroxyl acid production