Bayesian game-theoretic modeling of transmit power determination in a self-organizing CDMA wireless network

A static Bayesian game-theoretic model is applied to the problem of transmit power determination in the uplink of a self-organizing CDMA wireless network. Nodes are assumed to be uniformly distributed and to have knowledge of the common a priori path loss distribution, which is derived using standard assumptions. Using a classical existence result, the resulting Bayesian game is shown to have a pure strategy ε-Bayesian Nash equilibrium. Simulation studies identify pure strategy Bayesian Nash equilibria for a discretized version of the game, and comparisons to centralized and single-agent optimization approaches are made. Results for a representative case reveal a 16-27% expected throughput improvement for the game-theoretic approach over a distributed single-agent optimization and yet only a 9-15% reduction in expected throughput from the optimal centralized transmit power allocation. The approach presented may help to extend the applicability of game-theoretic analyses for emerging, self-organizing wireless networks by properly accounting for network uncertainties.