Semi‐dynamic Markov approximation‐based base station sleep with user association for heterogeneous networks

Abstract

AbstractEnergy efficiency (EE) in the communication industry is the general trend of green communication development, and the base station sleep (BSS) strategy is crucial to improving EE. However, how to maximize the cell's EE and optimize the performance of users in the sleeping area after the BSS is a challenging problem. The sub‐6GHz and millimeter‐wave (mmWave) integrated networks are considered in this paper. The users’ backhaul of the cell is jointly provided by the sub‐6 GHz band and the mmWave band. User reaccess algorithm based on multiple parameters access criterion is adopted when their severed base stations (BSs) are shut down. The authors also consider a resource allocation algorithm based on the semi‐dynamic Markov approximation (MA) algorithm, which is proposed to quickly allocate sub‐channels to reaccessed users and ensure the maximum throughput. The simulation results show that the proposed algorithm can improve the EE of the heterogeneous network and promptly meet the users’ needs when some BSs are shut down.