Research on Energy Efficiency Optimization of Indoor Network for Green Communication

In order to achieve green communication, this paper studied the energy efficiency optimization of indoor network based on the transmit power of home base stations. Firstly, a three-dimensional system model of dense deployment of home base stations is established, in which the physical location of the home base stations follows the Poisson Point Process (PPP). Secondly, a deep reinforcement learning algorithm is proposed to optimize the transmit power of the home base stations to improve the energy efficiency of the system. In addition, this paper compared deep reinforcement learning algorithm with Q learning algorithm and random allocation algorithm. Finally, the simulation results showed that our proposed algorithm has a fast convergence rate and is superior to the other two algorithms in energy efficiency optimization.