Energy Efficiency Optimization for DAS Based on Neural Network

Abstract

Aiming at the huge energy consumption problem in the communication industry, this paper proposes an optimization algorithm of geometric topology of base station based on neural network to improve the system energy efficiency. The relative position between the base station and the user affects the path loss of signal propagation and the size of interference signal, thus affecting the spectral efficiency and energy efficiency of the system. In this paper, communication simulation experiments are conducted to obtain some location coordinates of randomly distributed BTS and their corresponding system energy efficiency values, which are put into the neural network for training. Finally, the network model of base station location and system energy efficiency is obtained, and the maximum value of system energy efficiency is solved. The experimental results show that the algorithm can improve the system energy efficiency by 10 times, which has achieved the desired goal.