Fiber neural networks for the intelligent optical fiber communications

TL;DR

This paper introduces fiber neural networks that leverage optical fiber transmission for efficient, power-saving signal processing in future intelligent optical communication systems, demonstrating their effectiveness in modulation format recognition.

Contribution

It develops fiber neural networks integrated with optical signal processing, enabling direct optical domain computation and advancing beyond 5G communication signal processing.

Findings

Enhanced processing efficiency and reduced power consumption.

Successful modulation format recognition without conversion to electronic signals.

Potential for future optical communication systems.

Abstract

Optical neural networks have long cast attention nowadays. Like other optical structured neural networks, fiber neural networks which utilize the mechanism of light transmission to compute can take great advantages in both computing efficiency and power cost. Though the potential ability of optical fiber was demonstrated via the establishing of fiber neural networks, it will be of great significance of combining both fiber transmission and computing functions so as to cater the needs of future beyond 5G intelligent communication signal processing. Thus, in this letter, the fiber neural networks and their related optical signal processing methods will be both developed. In this way, information derived from the transmitted signals can be directly processed in the optical domain rather than being converted to the electronic domain. As a result, both prominent gains in processing efficiency and power cost can be further obtained. The fidelity of the whole structure and related methods is demonstrated by the task of modulation format recognition which plays important role in fiber optical communications without losing the generality.