  In the recent past, many mobile/telecom operators have seen a continuously
growing demand for ubiquitous high-speed wireless access and an unprecedented
increase in connected wireless devices. As a result, we have seen explosive
growth in traffic volumes and a wide range of QoS requirements. The Fifth
generation (5G) heterogeneous cellular networks (HetNets) have been developed
by different mobile operators to achieve the growing mass data capacity and to
reconnoiter the energy efficiency guaranteed trade-off between throughput QoS
requirements and latency performance. However, existing energy efficiency
algorithms do not satisfy the throughput QoS requirements such as reduced
latency and packet loss, longer battery lifetime, reliability, and high data
rates with regards to the three components of energy consumption of the 5G
radio access network (RANs) that dominate the overall mobile communication
networks. In addition, real-time traffic types such as voice and video require
a high computational load at the terminal side which has an undesirable impact
on energy/battery lifetime which further affects the throughput QoS performance
such as reduced packet loss, longer battery lifetime, reliability, and high
data rates. As a result, this paper proposed an Intelligent Throughput-based
Sleep Control (ITSC) algorithm for throughput QoS and energy efficiency
enhancement in 5G dense HetNets. In the proposed ITSC algorithm, a deep neural
network (DNN) was used to determine the cell capacity ratio for the small base
stations (SBSs).
