Optical Coupler Network Modeling and Parameter Estimation Based on a Generalized Tucker Train Decomposition

Abstract

Tensor models have been used extensively in signal processing applications to design different types of communication systems. This paper proposes, for the first time, the use of tensor models for optical communications. The signals of an optical dual-core coupler network are modeled as a multiway array (tensor), which satisfies a generalized Tucker train decomposition. This tensor model is then used to develop an estimation algorithm that enables the network parameters to be estimated from the input and output signals. The performance of this algorithm was evaluated by means of computer simulations, in terms of NMSE of the estimated parameters and convergence speed. For the tested configurations, good levels of NMSE with fast convergence were obtained, demonstrating the effectiveness of the proposed method as a promising tool for studying and designing optical devices, with a wide range of applications in the context of lightwave systems.

Keywords

• Alternating least squares
• multidimensional signal processing
• multilinear algebra
• optical arrays
• optical directional coupler
• optical fiber devices