Design of a Lora-Based IoT Network using Enhance Clustering Protocols.

LoRa is an IoT (Internet of Things) enabling technology which is particularly suitable for low data rateapplications. The technology can achieve extended network coverage while operating in unlicensed ISM bandand falls into the category of Low Power Wide Area Networks (LPWANs) technologies. Currently, LoRa WANnetworks face challenges related to Collision rates, packet delivery, and efficient management of static andmobile nodes. Existing methods based on ALOHA have limitations that hinder the effectiveness inaccommodating the diverse requirements of Lora networks. In this study, A LoRa IOT network with bothstatic and mobile nodes is modelled in MATLAB Environment. Static-Based Time Slot (SBTS) and Energy-Aware Dynamic User Clustering (EADUC) clustering approaches are implemented for Clustering andimplemented using ALOHA and TDMA medium Access mechanisms. The implementation assesses how theseprotocols impact key network metrics like Signal-to-Interference Ratio (SIR), Packet Delivery Ratio (PDR) andCollision rate (CR). Result from the analysis underscores the clear performance superiority of the SBTS-TDMAprotocol in LoRa networks. SBTS-TDMA achieved the highest Signal-to-Interference Ratio (SIR) at 10.97 dB,significantly outperforming EADUC-TDMA, EADUC-ALOHA, and SBTS-ALOHA, which enhances interferencemanagement. It also excelled in Packet Delivery Ratio (PDR), reaching 78.84%, demonstrating greaterreliability in data transmission than other protocols. Additionally, with a Collision Rate of just 0.00045, SBTS-TDMA outperformed EADUC-TDMA, EADUC-ALOHA, and SBTS-ALOHA, reinforcing its efficiency andreliability for data integrity in LoRa networks.