Oxidative Stress in Diabetes Mellitus: Is There a Role for Hypoglycemic Drugs and/or Antioxidants?

Abstract

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. The solution to the proposed game has each user formulating a best response to the worst-case interference. 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. The set of channel coefficients for which the robust-optimization equilibrium is unique and the iterative waterfilling algorithm converges shrinks as the channel uncertainty bound increases. We analyse the social properties of the equilibrium under varying channel uncertainty bounds for the two-user case. We prove an interesting phenomenon that increasing channel uncertainty can lead to a more efficient equilibrium, and hence, a better sum rate in certain multi-user communication systems.