Name of the Speaker: Sameer Ahmad Mir (EE19D418)
Guide: Dr. Deepa Venkitesh
Venue/Online meeting link: meet.google.com/euu-rfvb-gar
Date/Time: 28th July, 2022, 12:00 noon
With ever-increasing network traffic with an exponential growth rate of up to 60% per year, based on the application segment and geographical location, the next generation fiber-optic networks must focus on the spectrally efficient ways of providing high-capacity transport infrastructure for both long-haul and short-haul systems (<100 km). One of the methods to scale the capacity is by employing higher cardinality of modulation, thereby encoding more bits in a symbol, coupled with using a higher symbol rate of transmission. However, on scaling the modulation order, the allowed phase perturbation to be still within the error-free detection, a.k.a phase margin, reduces. Thus the performance becomes detrimental to small non-idealities or phase fluctuations in the system due to laser phase noise and transceiver IQ imbalance. Therefore, we need advanced digital signal processing (DSP)algorithms to correct these impairments.
In this talk, we present a novel DSP algorithm to correct for the laser phase noise, even in the presence of transmitter IQ imbalance, by intelligently adapting the decision boundaries. We show the improvement in performance by evaluating the algorithm for up to 32 GBd PM-16QAM (256 Gbps) modulation and show that it has less computational complexity than the conventional DSP algorithm. We also present a novel Geometric parameter extraction-based algorithm for receiver IQ imbalance correction. This pilot-free algorithm only uses less than 5% symbols from the received frame to estimate the statistical parameters, which are then used to correct the imbalanced data. We show the efficacy of this algorithm in simulations and through experiments for up to 80 GBd PM-16QAM (640 Gbps) signal.