On the machine learning–based smart beamforming for wireless virtualization with large‐scale MIMO system

Abstract

Abstract In this paper, we study a machine learning enabled smart beam scheduling approach for wireless virtualization in large‐scale multiple‐input–multiple‐output (MIMO) system. Large‐scale MIMO is regarded as an emerging technology to enhance data rate of future wireless networks and the wireless virtualization is regarded as an efficient paradigm to enhance the radio frequency (RF) spectrum utilization by subleasing RF slices of wireless infrastructure providers to mobile virtual network operators (MVNOs). We leverage machine learning approach for scheduling the beams in large‐scale MIMO where RF slices with the help of subsets of antennas are subleased for MVNOs. Performance of the proposed approach is evaluated using simulation results. The results show that the proposed approach outperforms the state of the art approach.