Efficient statistical QoT-aware resource allocation in EONs over the C+L-band: a multi-period and low-margin perspective

Abstract

Recently, multi-band elastic optical networks (MB-EONs) have been considered a viable solution to increase the transmission bandwidth in optical networks. To improve spectral efficiency and reduce the blocking ratio, the general signal-to-noise ratio (GSNR) as a quality-of-transmission (QoT) metric must be accurately calculated in the routing, modulation level, and spectrum assignment algorithms used in elastic optical networks (EONs). The interference prediction methods commonly used for single-band EONs are not efficient in the case of MB-EONs because of the inter-channel stimulated Raman scattering impact and their wide spectrum. In this paper, we propose a statistical method to predict the interference noise in C+L-band EONs considering multi-period planning. The proposed algorithm, which utilizes the predicted total number of channels (PTNC) on each link for given requests, is a low-margin, fast, and cost-effective method. Additionally, the proposed PTNC algorithm can also be used for single-period planning. Our simulation results indicate that the proposed PTNC algorithm combines the advantages of both studied benchmark algorithms. It has a low complexity order and execution time that are comparable to those of the fully loaded algorithm, which is currently employed by the network operators. However, this benchmark does not achieve the best spectral efficiency. Furthermore, the PTNC method and the other benchmark that determines margin through an exhaustive search, referred to as margin exhaustive search (MES), achieve remarkable spectral efficiency and residual capacity with fewer transceivers, resulting in lower capital expenditure requirements. Nevertheless, the MES algorithm may not be practical due to the requirement of reconfiguring established lightpaths and its high complexity order, particularly in multi-period planning.