HYBRID-BOOSTED MODEL WITH AN APPROACH INSPIRED

This study introduces a hybrid-boosted ensemble model tailored for predicting energy utilization in 5G base stations. The methodology merges ridge regression for linear trend analysis, XGBoost to tackle

Power Consumption Modeling of 5G Multi-Carrier Base Stations:

We demonstrate that this model achieves good estimation performance, and it is able to capture the benefits of energy saving when dealing with the complexity of multi-carrier base stations architectures.

AI-based energy consumption modeling of 5G base stations: an

We design a Deep Neural Network (DNN) based energy consumption model. The designed DNN is then optimized through quantization process for reducing its size, inference time

Energy-efficiency schemes for base stations in 5G heterogeneous

EE solutions have been segregated into five primary categories: base station hardware components, sleep mode strategies, radio transmission mechanisms, network deployment and

Energy-efficiency schemes for base stations in 5G

In today''s 5G era, the energy efficiency (EE) of cellular base stations is crucial for sustainable communication. Recognizing this, Mobile Network Operators are actively prioritizing EE for both

Hybrid Control Strategy for 5G Base Station Virtual Battery

Grounded in the spatiotemporal traits of chemical energy storage and thermal energy storage, a virtual battery model for base stations is established and the scheduling potential of

On hybrid energy utilization for harvesting base station in 5G networks

In this paper, hybrid energy utilization was studied for the base station in a 5G network. To minimize AC power usage from the hybrid energy system and minimize solar energy waste, a

Energy-efficient indoor hybrid deployment strategy for 5G mobile small

Within this model, we leverage the flexibility of mobile small-cell base stations (MSBS) to seamlessly traverse service regions. We compute the transmission power and location of SBS and