Z. Zhou, P. Mertikopoulos, A. L. Moustakas, S. Mehdian, N. Bambos and P. W. Glynn. In GLOBECOM '17: Proceedings of the 2017 IEEE Global Telecommunications Conference, 2017.
We propose a simple, novel and distributed power control algorithm that efficiently incorporates past information and regulates power to achieve better stability. We provide an analytical framework that examines in depth the properties of the proposed algorithm, and we establish its convergence for both deterministic, time-invariant channels and stochastic, time-varying environments. In the former (deterministic) case, if the channel is feasible, the proposed dual averaging algorithm converges to the optimal power vector. More importantly, in the latter (stochastic) case, we show that if the channel is feasible on average, then the proposed dual averaging power control algorithm converges almost surely to a deterministic optimal power vector, even though existing power control algorithms (such as Foschini–Miljanic) may fail to converge (to a distribution) altogether. Finally, we provide a set of simulations that further demonstrate various interesting and desirable properties of the proposed algorithm.