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Flexible optical networks (FONs) are being adopted to accommodate theincreasingly heterogeneous traffic in today's Internet. However, in presence ofhigh traffic load, not all offered traffic can be satisfied at all time. Ascarried traffic load brings revenues to operators, traffic blocking due tolimited spectrum resource leads to revenue losses. In this study, given a setof traffic requests to be provisioned, we consider the problem of maximizingoperator's revenue, subject to limited spectrum resource and physical layerimpairments (PLIs), namely amplified spontaneous emission noise (ASE),self-channel interference (SCI), cross-channel interference (XCI), and nodecrosstalk. In FONs, adaptive modulation, multiple FEC, and the tuning of powerspectrum density (PSD) can be effectively employed to mitigate the impact ofPLIs. Hence, in our study, we propose a universal bandwidth-related impairmentevaluation model based on channel bandwidth, which allows a performanceanalysis for different PSD, FEC and modulations. Leveraging this PLI model anda piecewise linear fitting function, we succeed to formulate the revenuemaximization problem as a mixed integer linear program. Then, to solve theproblem on larger network instances, a fast two-phase heuristic algorithm isalso proposed, which is shown to be near-optimal for revenue maximization.Through simulations, we demonstrate that using adaptive modulation enables tosignificantly increase revenues in the scenario of high signal-to-noise ratio(SNR), where the revenue can even be doubled for high traffic load, while usingmultiple FECs is more profitable for scenarios with low SNR.

Maximizing Revenue with Adaptive Modulation and Multiple FECs in Flexible Optical Networks