Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: End-to-End Deep Learning of Long-Haul Coherent Optical Fiber
  Communications via Regular Perturbation Model   We present a novel end-to-end autoencoder-based learning for coherent optical
communications using a "parallelizable" perturbative channel model. We jointly
optimized constellation shaping and nonlinear pre-emphasis achieving mutual
information gain of 0.18 bits/sym./pol. simulating 64 GBd dual-polarization
single-channel transmission over 30x80 km G.652 SMF link with EDFAs.

29
The categories of this paper are: funct-an
14
The categories of this paper are: math-ph
5
The categories of this paper are: gr-qc
8
The categories of this paper are: hep-ex
20
The categories of this paper are: acc-phys
11
The categories of this paper are: hep-lat
23
The categories of this paper are: solv-int
31
The categories of this paper are: ao-sci
0
The categories of this paper are: hep-ph
37
The categories of this paper are: supr-con
7
The categories of this paper are: hep-th
24
The categories of this paper are: dg-ga
28
The categories of this paper are: alg-geom
4
The categories of this paper are: cond-mat
9
The categories of this paper are: nlin
16
The categories of this paper are: stat