Dynamic base station planning with power adaptation for green wireless cellular networks

Energy-efficient green solutions are not only beneficial for the environment but also help to reduce the energy expenditure of the investors. Since base stations (BSs) of wireless cellular access networks are deployed to accommodate the peak-time traffic, they are underutilized most of the time. In this work, we try to save energy by both turning BSs on/off and adaptively adjusting their transmission power according to the current traffic conditions. To achieve that goal, we formulate a novel nonlinear programming model for the green dynamic BS planning (GDBP) problem to find the best possible topology which minimizes the energy consumption of the network while satisfying a certain grade of service (GoS). We derive a greedy heuristic called FastWISE to solve the formulated problem and compare our results with the results of a noncommercial optimization tool and numerous Monte Carlo experiments. It is shown that our GDBP scheme adaptively adjusts the network topology to the current traffic load and saves significant amount of energy without violating the GoS constraints, such as the probability of blocking and the coverage ratio.