Energy-Source-Aware Cost Optimization for Green Cellular Networks with Strong Stability

Last decade witnessed the explosive growth in mobile devices and their traffic demand, and thereby the significant increase in the energy cost of the cellular service providers. One major component of the service providers' operational expenditure comes from the operation of cellular base stations using grid power or diesel generators when grid power is absent, which also causes adverse environmental impact due to enormous carbon footprint. Therefore, from the service providers' perspective, how to effectively reduce the energy cost of base stations while satisfying cellular users' soaring traffic demands has become an imperative and challenging problem. In this paper, we investigate the minimization of the long-term time-averaged expected energy cost of cellular service providers while guaranteeing the strong stability of the network. In particular, we first formulate the problem by jointly considering flow routing, link scheduling, and energy (i.e., renewable energy resource, energy storage unit, and so on) constraints. Since the formulated problem is a time-coupling stochastic mixed-integer nonlinear programming problem, which is prohibitively expensive to solve, we reformulate the problem by employing Lyapunov optimization theory. A decomposition-based algorithm is developed to solve the problem and the network strong stability is proven. We then derive and prove both the lower and the upper bounds on the optimal result of the original problem. Simulation results demonstrate the tightness of the obtained bounds and the efficacy of the proposed scheme.