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This paper develops a hierarchical iterative OSNR algorithm based on a game theory framework. A Nash game is formulated between channels with channel utility related to maximizing channel optical signal-to-noise ratio (OSNR). The OSNR game has coupled utilities and coupled constraints, such that total power is kept below the nonlinearity threshold. Solving directly this game requires coordination among all channels and is impractical in networks. A duality approach is used instead, based on the recent theoretical results in . This method offers a natural way to hierarchically decompose the coupled Nash game into a lower-level Nash game with no coupled constraints, and a higher-level link optimization problem for pricing parameters. The lower-level Nash game is analytically tractable, and its solution can be iteratively found via an algorithm decentralized with respect to channels. The price is adjusted at the network higher-level so that channels are induced to cooperate towards satisfying the coupled total power constraint.