Non-data-aided joint bit-rate and modulation format identification for next-generation heterogeneous optical networks

A novel and cost-effective technique for simultaneous bit-rate and modulation format identification (BR-MFI) in next-generation heterogeneous optical networks is proposed. This technique utilizes an artificial neural network (ANN) in conjunction with asynchronous delay-tap plots (ADTPs) to enable low-cost joint BR-MFI at the receivers as well as at the intermediate network nodes without requiring any prior information from the transmitters. The results of numerical simulations demonstrate successful identification of several commonly-used bit-rates and modulation formats with estimation accuracies in excess of 99.7%. The effectiveness of proposed technique under different channel conditions i.e. optical signal-to-noise ratio (OSNR) in the range of 14-28 dB, chromatic dispersion (CD) in the range of -500 to 500 ps/nm and differential group delay (DGD) in the range of 0-10 ps, is investigated and it has been shown that the proposed technique is robust against all these impairments.