Dynamic energy-efficient resource allocation in cognitive heterogeneous wireless networks with the smart grid

Rapidly rising energy costs and increasingly rigid environmental standards have led to an emerging trend of addressing the “energy efficiency” aspect of wireless cellular networks. In cellular networks, base stations (BSs) are power-hungry elements and absorbing them in the smart grid can significantly increase power efficiency. However, this important perspective has been ignored in the energy-efficiency research on cellular networks. In this paper, heterogeneous networks, cognitive radios, and the smart grid are jointly studied to improve energy efficiency. Multiple retailers in the smart grid provide real-time electricity prices to the heterogeneous network, and the macrocell base station (MBS) and femtocell base stations (FBSs) perform energy-efficient power allocation. To mitigate interference and guarantee quality of service (QoS), an interference price is proposed to allow the MBS to protect itself by charging the femtocell users.We formulate the decision problems of electricity price, energy-efficient power allocation and interference price as a three-level Stackelberg game. We use a homogeneous Bertrand game to model price decisions made by the retailers. A backward induction method is used to analyze the proposed game. Simulation results show that our proposed scheme can significantly reduce operational expenditure and CO₂ emissions.