Error vector magnitude based parameter estimation for digital filter back-propagation mitigating SOA distortions in
Optics Express
|October 10, 2013
Summary
We present a simple, low-overhead method for digital filter back-propagation (DFBP) using coarse parameter estimation to reduce semiconductor optical amplifier (SOA) nonlinearity in coherent communications, achieving negligible performance penalty.
Area of Science:
- Optical Communications
- Nonlinear Optics
- Signal Processing
Background:
- Semiconductor optical amplifiers (SOAs) are crucial for extending transmission distances in coherent communication systems.
- SOA nonlinearity introduces signal distortions, degrading system performance.
- Digital filter back-propagation (DFBP) is a digital signal processing technique used to compensate for nonlinear impairments.
Purpose of the Study:
- To introduce a simplified, low-overhead parameter estimation method for DFBP.
- To mitigate nonlinearity in coherent communication systems caused by SOAs.
- To evaluate the performance of DFBP with coarse parameter estimation against fine parameter estimation.
Main Methods:
- Developed a coarse parameter estimation method for DFBP using Error Vector Magnitude (EVM) as a performance metric.
- Experimentally investigated the performance using two commercial SOAs as booster amplifiers.
- Tested the method with 16-Quadrature Amplitude Modulation (16-QAM) signals at 22 Gbaud over 80 km fiber propagation.
Main Results:
- The proposed coarse parameter estimation for DFBP achieved negligible bit error rate (BER) penalty compared to fine parameter estimation.
- Optimized SOA bias currents for improved performance were identified.
- Efficient compensation of SOA-induced nonlinearity was demonstrated for both SOA types.
Conclusions:
- Coarse parameter estimation for DFBP offers an efficient and low-overhead solution for mitigating SOA nonlinearity.
- The method is effective for high-order modulation formats like 16-QAM in long-haul coherent systems.
- This approach simplifies DFBP implementation without significant performance compromise.
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