Deep Belief Networks With Novel Dynamic Bandwidth Allocation (NoDBA) to Improve the Reconfigurable Fronthaul's Energy and Transmission Efficiency

ABSTRACT The increasing demand for high‐speed, low‐latency communication has led to significant advancements in hybrid optical‐wireless access networks. Among these, time and wavelength division multiplexing passive optical networks (TWDM‐PONs) have received considerable attention for their high capacity and efficiency. In this study, a reconfigurable fronthaul for cloud radio access networks (C‐RANs) is developed using deep belief networks (DBNs) and a novel dynamic bandwidth allocation (NoDBA) algorithm. The primary objective is to design a low‐latency, high‐efficiency mobile fronthaul that optimally manages bandwidth allocation while ensuring seamless connectivity. The proposed DBN‐NoDBA model, integrated with the XGS‐PON standard, is evaluated through simulations, demonstrating superior performance compared with existing XGS‐PON algorithms for handling mobile fronthaul and backhaul traffic. Additionally, a fast‐converging genetic algorithm is introduced to enhance energy efficiency by dynamically activating and deactivating fronthaul units based on real‐time traffic variations. The results confirm that DBN‐NoDBA effectively reduces latency, optimizes bandwidth utilization, and significantly develops energy savings, making it a promising solution for next‐generation 5G and beyond optical‐wireless networks.