Comparative Study and Implementation of Efficient Bandwidth Utilization Technique for LoRaWAN

LoRaWAN (Long Range Wide Area Network) is one of the most widely adopted Low-Power Wide Area Network (LPWAN) technologies, enabling long-range, energy-efficient communication for Internet of Things (IoT) applications. A key mechanism in LoRaWAN is Adaptive Data Rate (ADR), which dynamically configures each end device’s Spreading Factor (SF) and transmission power (Tx Power) to balance energy consumption, coverage, and reliability. The efficient allocation of SFs is particularly critical, as it directly influences bandwidth utilization, throughput, latency, and packet collision rates. In this paper, we present a comparative study and implementation of three approaches for ADR-based bandwidth optimization schemes: Static ADR, Centralized ADR, and a proposed Decentralized ADR scheme. Python-based simulations are conducted under varying traffic conditions, incorporating realistic wireless channel models such as Free Space, Okumura-Hata, and Nakagami-m fading.Performance metrics including throughput, packet success rate, collision rate, and SF distribution are evaluated to provide a clear and comprehensive comparison of the different ADR approaches. The results demonstrate that the proposed Decentralized ADR significantly improves overall performance, achieving up to 18.6% higher throughput compared to the conventional Centralized ADR scheme. These findings highlight the importance of distributed decision-making in LoRaWAN and provide useful insights into scalable, adaptive, and efficient ADR designs for next-generation large-scale IoT deployments.