Model-centric nonlinear equalizer for coherent long-haul fiber-optic communication systems

In long-haul DWDM or elastic subwavelength modulated systems with periodic dispersion compensation and amplification, all-optical communications give rise to severe physical impairments, due to fiber dispersion and nonlinearity, together with noise due to amplified spontaneous emission (ASE), that adversely affect system performance. Many signal processing techniques, including forward error correction, constrained coding, and predistortion/equalization, have been developed to mitigate these physical impairments and fully exploit the system capacity of long-haul DWDM systems. However, existing equalizers either only mitigate linear impairments or are too complex to be useful, such as backpropagation. This paper proposes a model-centric nonlinear equalizer for coherent systems based on a 2D discrete-time model of physical impairments in long-haul time and wavelength channel systems with periodic dispersion compensation and amplification using inverse Volterra theory. Different from backpropagation, which is hard to implement in hardware, this equalizer can function on the most basic discrete-time signal processing device. The nonlinear equalizer is effective in suppressing linear and nonlinear physical impairments in a long-haul fiber-optic communication system, particularly for high launched power levels where fiber nonlinearity dominates.