Implementation of Large Field-of-View Detection for UWOC Systems Based on a Diffractive Deep Neural Network

Abstract

The link alignment in underwater wireless optical communication (UWOC) systems is a knotty problem. The diffractive deep neural network (D2NN) has shown great potential in accomplishing tasks all optically these years. In this paper, a 6-layer D2NN is proposed to alleviate the link alignment difficulties in UWOC systems. Simulation results demonstrate that the proposed method can focus incident light with tilt angles from 0° to 60° into a 6.25% area of the detection plane with an average focusing efficiency of 93.15%. Extra simulations further reveal that more layers lead to a sustained performance improvement before reaching a bottleneck, and the D2NN can achieve large field angle focusing within a certain focusing area. The proposed receiver design, which can be highly integrated with detectors, holds promise to realize reliable link establishment in UWOC systems in the future.

Keywords

• Diffractive deep neural network
• underwater wireless optical communication
• optical computing