Quality of Transmission Aware Optical Networking Using Enhanced Gaussian Noise Model
Artikel i vetenskaplig tidskrift, 2019
We present a new joint routing, wavelength, and power allocation method for optical network planning. The introduced gradient-based convex optimization approach has a lower computational complexity, compared to common linear programming techniques, suitable for both static as well as time-critical dynamic network planning with fast convergence requirement. The proposed scheme takes physical-layer impairments into account, using the enhanced Gaussian noise nonlinear model. In contrast to methods exploiting the theoretical full link spectrum utilization assumption (fully occupied fiber-optic C-hand spectrum), we focus on maximizing the network achievable rate and minimum signal-to-noise ratio (SNR) margin of networks with partial spectrum utilization in their links, relevant to the majority of empirical metro network scenarios. According to numerical results, the network achievable rate can be improved around 17% by performing power optimization over the individual launch power of network lightpaths compared to optimizing a single flat (equal) launch power for all the lightpaths. Moreover, the minimum SNR margin of the simulated network is improved by about 23 dB. Finally, it is observed that maximizing the network minimum SNR margin needs the launch power of each lightpath to be proportional to the total nonlinear interference noise efficiency influencing the lightpath.
routing and wavelength assignment
enhanced Gaussian noise model
optical network optimization