Surveillance of few-mode fiber-communication channels with a single hidden layer neural network

Abstract

Multi- and few-mode fibers (FMFs) promise to enhance the capacity of optical communication networks by orders of magnitude. The key for this evolution was the strong advancement of computational approaches that allowed inherent complex light transmission to be surpassed, learned, or controlled, reined in by modal crosstalk and mode-dependent losses. However, complex light transmission through FMFs can be learned by a single hidden layer neural network (NN). The emerging developments in NNs additionally allow the implementation of novel concepts for security enhancements in optical communication. Once the transmission characteristics of FMFs are learned, it is possible to survey the incoming and outgoing light fields via monitoring channels during data transmission. If an eavesdropper tries to gain unauthorized access to the FMF, its transmission properties are impaired through sensitive modal crosstalk. This process is registered by the NN and thus the eavesdropper is revealed. With our solution, the security of optical communication can be improved.