Efficiency of rate-maximization game under bounded channel uncertainty

The problem of competitive rate-maximization is an important signal-processing problem for power-constrained multi-user systems. It involves solving the power control problem for mutually interfering users operating across multiple frequencies. We introduced robust rate-maximization game for systems with bounded channel uncertainty. In this paper, we analyse the effect of uncertainty on the global efficiency of the robust rate-maximization game. For a two-user scenario with large number of frequencies, we show that the robust-optimization equilibrium tends to move towards FDMA solution as the uncertainty bound increases and thus increases the sum-rate for interference-constrained systems where FDMA is Pareto-optimal. These results are verified through simulations.