Online algorithms for energy cost minimization in cellular networks

Dynamic base station activation and transmission power control are the key mechanisms to reduce energy consumption in cellular networks. In this work, we consider employing these methods for the purpose of minimizing long-term energy cost in cellular networks. Based on the two-timescale Lyapunov optimization technique, we formulate an online control problem to ensure achieving minimal energy cost while stabilizing use queues. While the control problem can be solved in a centralized manner, we limit our attention to distributed solutions which are highly attractive in the design of next generation mobile networks. Due to the combinatorial nature of the problem and the complex relation of achievable rates to interfering signals, the problem is non-convex. Consequently, conventional duality methods cannot be employed to achieve the distributed solution. Thus, we design a distributed solution for the problem based on Gibbs sampling method. The proposed algorithm can be implemented in a fully distributed manner, does not depend on the convexity or continuity of the energy cost functions, and guarantees solution optimality. Numerical results are provided to demonstrate the behavior of the solution in some example network scenarios.