  In this paper, the generalized Nash equilibrium (GNE) seeking problem for
continuous games with coupled affine inequality constraints is investigated in
a partial-decision information scenario, where each player can only access its
neighbors' information through local communication although its cost function
possibly depends on all other players' strategies. To this end, a novel
decentralized primal-dual algorithm based on consensus and dual diffusion
methods is devised for seeking the variational GNE of the studied games. This
paper also provides theoretical analysis to show that the designed algorithm
converges linearly for the last-iterate, which, to our best knowledge, is the
first to propose a linearly convergent GNE seeking algorithm under coupled
affine inequality constraints. Finally, a numerical example is presented to
demonstrate the effectiveness of the obtained theoretical results.
