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Game theory is a useful and powerful tool for performance analysis and optimization of wireless mesh networks (WMNs). Based on incompletely cooperative game theory, a mesh router can estimate the game state (e.g., the number of competing nodes), and broadcast this information to its clients. Then all the clients play a cooperative game based on the estimated game state, and achieve the optimal equilibrium strategy. For each client to implement the game independently as it cannot get the game state accurately or timely sometimes, particle swarm optimization is introduced into the game, and a game-theoretic particle swarm optimization scheme (G-PSO) for WMNs is presented in this paper. Simulation results show that G-PSO can increase system throughput and decrease delay, jitter and packet-loss-rate.