Energy and Throughput Optimization in NB-IoT Networks

Autorentext

Mr DIOMANDE LASSANA, a qualified nurse, is a participant in the third cohort of the Republic of Côte d'Ivoire's intermediate-level epidemiology training program (FETP). He currently works for the Guémon regional health department, where he is in charge of regional epidemiological surveillance.

Klappentext

This study aims to enhance energy efficiency and network throughput in Narrowband IoT (NB-IoT) and Narrowband Cognitive Radio IoT (NB-CR-IoT) networks. A novel three-hop communication strategy is proposed, employing a double auction mechanism to optimize relay selection and extend the battery life of cell-edge NB-IoT users (CENUs). The approach is supported by the EENU-MWM algorithm, which ensures efficient and fair user matching. With the rapid proliferation of IoT devices, critical challenges such as spectrum congestion and hardware limitations for continuous sensing have emerged. To address these issues, the study introduces optimized sensing parameters and relay node selection strategies within NB-CR-IoT and Narrowband Cognitive Radio Internet of Medical Things (NB-CR-IoMT) frameworks. These enhancements improve overall data throughput while reducing transmission power consumption.