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In the recent past, many mobile/telecom operators have seen a continuouslygrowing demand for ubiquitous high-speed wireless access and an unprecedentedincrease in connected wireless devices. As a result, we have seen explosivegrowth in traffic volumes and a wide range of QoS requirements. The Fifthgeneration (5G) heterogeneous cellular networks (HetNets) have been developedby different mobile operators to achieve the growing mass data capacity and toreconnoiter the energy efficiency guaranteed trade-off between throughput QoSrequirements and latency performance. However, existing energy efficiencyalgorithms do not satisfy the throughput QoS requirements such as reducedlatency and packet loss, longer battery lifetime, reliability, and high datarates with regards to the three components of energy consumption of the 5Gradio access network (RANs) that dominate the overall mobile communicationnetworks. In addition, real-time traffic types such as voice and video requirea high computational load at the terminal side which has an undesirable impacton energy/battery lifetime which further affects the throughput QoS performancesuch as reduced packet loss, longer battery lifetime, reliability, and highdata rates. As a result, this paper proposed an Intelligent Throughput-basedSleep Control (ITSC) algorithm for throughput QoS and energy efficiencyenhancement in 5G dense HetNets. In the proposed ITSC algorithm, a deep neuralnetwork (DNN) was used to determine the cell capacity ratio for the small basestations (SBSs).

Intelligent Throughput-based Sleep Control Algorithm for the 5G Dense Heterogeneous Cellular Networks