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In this paper, a novel joint symbol ratemodulation format identification (SR-MFI) and optical signal-to-noise ratio (OSNR) estimation scheme using the low-bandwidth coherent detecting and random forest (RF)based ensemble learning is proposed for intermediate nodes in the flexible dense wavelength division multiplexing (F-DWDM) networks. By leveraging low-bandwidth coherent detecting with small bulk wavelength scanning, no chromatic dispersion compensation and low-complexity RF, the proposed scheme could serve as a reduced-complexity and cost-effective option to realize joint SR-MFI and OSNR estimation at intermediate nodes in F-DWDM networks. To verify the feasibility of the proposed scheme, the comprehensive simulations of 8/16 GBaud polarization division multiplexing (PDM)-4/16/32/64 quadrature amplitude modulation (QAM) systems are conducted. The simulation results show that the identification accuracy of SR-MFI reaches 100% and the mean absolute error of OSNR estimation is within 1 dB. Moreover, the proposed monitoring scheme is verified by 8/16 GBaud PDM-4/16/32QAM coherent transmission experiments.

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A frequency domain (FD) 4×2 multi-input and multi-output (MIMO) equalizer based on radially directed equalizer is proposed to compensate receiver in-phase/quadrature (IQ) imbalances of M-ary quadrature amplitude modulation signals. This algorithm has a significantly lower complexity compared with a conventional time-domain 4×2 MIMO equalizer. Furthermore, each of imperfection estimations is derived from the converged discrete frequency response of the FD 4×2 MIMO equalizer. The simulation and experimental results indicated that the receiver (Rx) IQ imbalances were fully compensated by the proposed equalizer and precisely estimated by estimators, even for long-haul transmission with Rx IQ imbalances varying over a wide range.

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