Abstract

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-band 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 2.3 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.

© 2018 IEEE

Quality of Transmission Estimation in WDM and Elastic Optical Networks Accounting for Space–Spectrum Dependencies

I. Sartzetakis, K. Christodoulopoulos, C. P. Tsekrekos, D. Syvridis, and E. Varvarigos
J. Opt. Commun. Netw. 8(9) 676-688 (2016)

Quality-aware resource provisioning for multiband elastic optical networks: a deep-learning-assisted approach

Rana Kumar Jana, Bijoy Chand Chatterjee, Abhishek Pratap Singh, Anand Srivastava, Biswanath Mukherjee, Andrew Lord, and Abhijit Mitra
J. Opt. Commun. Netw. 14(11) 882-893 (2022)

Resource Allocation for Elastic Optical Networks Using Geometric Optimization

Mohammad Hadi and Mohammad Reza Pakravan
J. Opt. Commun. Netw. 9(10) 889-899 (2017)

QoT estimation using EGN-assisted machine learning for multi-period network planning

Jasper Müller, Sai Kireet Patri, Tobias Fehenberger, Helmut Griesser, Jörg-Peter Elbers, and Carmen Mas-Machuca
J. Opt. Commun. Netw. 14(12) 1010-1019 (2022)

Performance improvements by dynamic amplifier reconfigurations for C + L-band optical networks in the presence of stimulated Raman scattering

Zhuili Huang, Liang Dou, Jingchi Cheng, Chongjin Xie, Chao Lu, and Alan Pak Tao Lau
J. Opt. Commun. Netw. 15(6) 344-356 (2023)