Abstract
An important issue in the cellular industry is the rising energy cost and carbon footprint due to the rapid expansion of the cellular infrastructure. Greening cellular networks has thus attracted attention. Among the promising green cellular network techniques, the renewable energy-powered cellular network has drawn increasing attention as a critical element towards reducing carbon emissions due to massive energy consumption in the base stations deployed in cellular networks. Game theory is a branch of mathematics that is used to evaluate and optimize systems with multiple players with conflicting objectives and has been successfully used to solve various problems in cellular networks. In this paper, we model the green energy utilization and power consumption optimization problem of a green cellular network as a pilot power selection strategic game and propose a novel distributed algorithm based on a strategic learning method. The simulation results indicate that the proposed algorithm achieves correlated equilibrium of the pilot power selection game, resulting in optimum green energy utilization and power consumption reduction.
Highlights
With the rapid increase in the world’s energy demand, the reduction of greenhouse gas (GHG) emissions to combat global warming has become one of the most important issues in today’s society
We can observe that Intelligent Cell brEathing (ICE) successfully minimizes the maximum energy depleting rate (EDR) values and balances the green energy consumption among the base stations (BSs) compared to other schemes
As seen in the figure, ICE and the proposed scheme achieve lower user outage compared to SSF when the number of users is less than 550, above which SSF achieves better performance due to insufficient green energy allocation to satisfy all users in the system
Summary
With the rapid increase in the world’s energy demand, the reduction of greenhouse gas (GHG) emissions to combat global warming has become one of the most important issues in today’s society. We formulate the green energy utilization and power consumption optimization problem as a strategic game and propose a simple distributed algorithm that solves the strategic game based on the regret matching procedure to enhance energy efficiency. The proposed algorithm achieves an equilibrium solution to the pilot power selection game, resulting in optimum green energy utilization and power consumption reduction. To maximize the green energy utilization and minimize the total energy consumption based on the green network model described above, the BSs are designed to optimize the cell coverage area through dynamic pilot power selection. We propose to model the pilot power selection problem as a strategic game such that 1) BSs are rewarded for choosing strategies that increase green energy utilization and 2) BSs are penalized for choosing strategies that increase system power consumption. Are the components of the strategic game: 1. Set of players: M is the set of players corresponding to the BSs with the goal of maximizing its utility
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