Performance of turbulence-impaired dense OAM constellations for data modulation

Abstract

The increase of data rate and bandwidth efficiency of free-space optical communication links may be supported by the use of dense orbital angular momentum (OAM) states, carrying several information bits per transmission. Using machine-learning decoding, the performance of 32-OAM and 64-OAM signal constellations –designed using 4-state superpositions– are studied using numerical propagation models. Using two candidate architectures for detection –Shack-Hartmann and Mode Sorter– we evaluate the performance of the modulation in a simulated optical atmospheric channel by means of the detection accuracy.