An Energy-Aware Zone Routing Protocol Scheme Utilizing LSTM-RNN for 5G Wireless Backhaul Network

• Published in: 2023 International Conference of Computer Science and Information Technology (ICOSNIKOM) pp. 1 - 6
• Main Authors: Sirait, Fadli, Mulyono, Dani, Akhmad Wahyu, Marsal, Arif, Rofiq, Muhammad Ainur
• Format: Conference Proceeding
• Language: English
• Published: IEEE 10.11.2023
• Subjects: Energy consumption; LSTM-RNN; Routing; Routing protocols; Throughput; Training; Wireless communication; Wireless mesh networks; Zone Radius; ZRP
• DOI: 10.1109/ICoSNIKOM60230.2023.10364444

In this study, we introduce an energy aware zone routing protocol for fifth-generation wireless system, aiming to significantly enhance network performance. LSTM-RNN was utilized for enabling the zone routing protocol (ZRP) in dynamically adjusting the zone radius value according to the network's environmental conditions. This adjustment is achieved by customizing the routing zone for each node guided by performance metrics including routing overhead, energy consumption, throughput, and user usage. The input metrics were employed as a dataset, which was divided into 500 data points for training and 100 data point for testing. The proposed method was assessed in two scenarios. The first scenario involved a static node environment, while the second scenario involved a mobility node environment. These assessments were carried out in an unlicensed spectrum for wireless backhaul networks that employ wireless mesh networks (WMNs) as their network infrastructure, aligning with the 5G New Radio, as specified in 3GPP Release 16. Findings from the proposed method were analyzed in comparison to the conventional ZRP's outcome in both scenarios. Moreover, it is evident that the energy consumption during the implementation of the introduced method is notably less than that associated with the conventional approach. This observation holds true for both static and mobile node scenarios.