Network Energy Saving Optimization in Advanced Mobile Networks

In the fifth generation (<tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$\mathbf{5 G}$</tex>) mobile networks, the growing energy consumption of base stations (BS) has made network energy saving (NES) an increasingly important issue. This paper proposed optimized schemes, including the BSoriented NES (B-NES), the user equipment (UE)-oriented NES (U-NES), and the hybird NES (H-NES), for the NES function (NESF) to make the BS energy-saving decision. The first two schemes employ heuristic algorithms, while the last scheme adopts the Harris Hawks Optimization (HHO) or Whale Optimization Algorithm (WOA), based on an evolutionary approach. With the proposed schemes, each UE periodically measures the received signal reference power (RSRP) of both the serving and neighboring BSs and reports candidate BSs with an RSRP at least as high as that of the serving BS to the NESF. Additionally, each BS periodically reports its current and predicted traffic load to the NESF. The information is utilized by the NESF to optimize network energy efficiency by determining the transition of each BS between energy saving and active states, while maintaining the quality of service of UEs. Simulation results show that the H-NES scheme achieves the best energy efficiency, however its computational complexity is the highest. In contrast, the UNES scheme, which has the lowest computational complexity, outperforms the B-NES scheme and performance lower than that of the H-NES scheme. In conclusion, the proposed schemes not only enable energy-efficient networks but also exhibit adaptability for deployment in the sixth-generation (6G) mobile networks.