Filter Design for SOA-Assisted SS-WDM Systems Using Parallel Multicanonical Monte Carlo

Abstract

We address design and optimization of optical filters for spectrum-sliced wavelength division multiplexed (SS-WDM) systems employing saturated semiconductor optical amplifiers (SOAs) to suppress intensity noise. We study the impact of the shape of both slicing and channel selecting optical filters vis-a-vis two important impairments: the filtering effect and the crosstalk. The quantification of bit error rate (BER) is made possible by a parallel implementation of the multicanonical Monte Carlo algorithm. The intensity noise suppression by the SOA and signal degradation by subsequent optical filtering are studied both numerically and experimentally. We find optical filter shape and bandwidth that minimizes BER. By varying channel spacing and width, we estimate the achievable spectral efficiency when using both noise-cleaning SOA and forward error correction. We show that when constrained to use a symmetric architecture, i.e., identical filters for both slicing and channel selecting filters, there is a degradation in achievable spectral efficiency. We show that noise suppression is robust to variations in relative channel powers in multichannel systems. Our numerical simulations, vetted experimentally, provide accurate and quantitative results on optimized system performance.