  We consider the problem of decentralized power allocation for competitive
rate-maximization in a frequency-selective Gaussian interference channel under
bounded channel uncertainty. We formulate a distribution-free robust framework
for the rate-maximization game. We present the robust-optimization equilibrium
for this game and derive sufficient conditions for its existence and
uniqueness. We show that an iterative waterfilling algorithm converges to this
equilibrium under certain sufficient conditions. We analyse the social
properties of the equilibrium under varying channel uncertainty bounds for the
two-user case. We also observe an interesting phenomenon that the equilibrium
moves towards a frequency-division multiple access solution for any set of
channel coefficients under increasing channel uncertainty bounds. We further
prove that increasing channel uncertainty can lead to a more efficient
equilibrium, and hence, a better sum rate in certain two-user communication
systems. Finally, we confirm, through simulations, this improvement in
equilibrium efficiency is also observed in systems with a higher number of
users.
