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Optimizing LoRaWAN Gateway Placement in Urban Environments: A Hybrid PSO-DE Algorithm Validated via HTZ Simulations
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With rapid advancements in the Internet of Things (IoT), Low-Power Wide-Area Networks (LPWANs) play a crucial role in expanding IoT’s capabilities while using minimal energy. Among the various LPWAN technologies, LoRaWAN (Long-Range Wide-Area Network) is particularly notable for its capacity to enable long-range, low-rate communications with low power needs. This study investigates how to optimize the placement of LoRaWAN gateways by using a combination of Particle Swarm Optimization (PSO) and Differential Evolution (DE). The approach is validated through simulations driven by HTZ to evaluate network performance in urban settings. Centered around the area of the Politehnica University of Bucharest, this research examines how different gateway placements on various floors of a building affect network coverage and packet loss. The experiment employs Adeunis Field Test Devices (FTDs) and Dragino LG308-EC25 gateways, systematically testing two spreading factors, SF7 and SF12, to assess their effectiveness in terms of signal quality and reliability. An innovative optimization algorithm, GateOpt PSODE, is introduced, which combines PSO and DE to optimize gateway placements based on real-time network performance metrics, like the Received Signal Strength Indicator (RSSI), the Signal-to-Noise Ratio (SNR), and packet loss. The findings reveal that strategically positioning gateways, especially on higher floors, significantly improves communication reliability and network efficiency, providing a solid framework for deploying LoRaWAN networks in intricate urban environments.
Title: Optimizing LoRaWAN Gateway Placement in Urban Environments: A Hybrid PSO-DE Algorithm Validated via HTZ Simulations
Description:
With rapid advancements in the Internet of Things (IoT), Low-Power Wide-Area Networks (LPWANs) play a crucial role in expanding IoT’s capabilities while using minimal energy.
Among the various LPWAN technologies, LoRaWAN (Long-Range Wide-Area Network) is particularly notable for its capacity to enable long-range, low-rate communications with low power needs.
This study investigates how to optimize the placement of LoRaWAN gateways by using a combination of Particle Swarm Optimization (PSO) and Differential Evolution (DE).
The approach is validated through simulations driven by HTZ to evaluate network performance in urban settings.
Centered around the area of the Politehnica University of Bucharest, this research examines how different gateway placements on various floors of a building affect network coverage and packet loss.
The experiment employs Adeunis Field Test Devices (FTDs) and Dragino LG308-EC25 gateways, systematically testing two spreading factors, SF7 and SF12, to assess their effectiveness in terms of signal quality and reliability.
An innovative optimization algorithm, GateOpt PSODE, is introduced, which combines PSO and DE to optimize gateway placements based on real-time network performance metrics, like the Received Signal Strength Indicator (RSSI), the Signal-to-Noise Ratio (SNR), and packet loss.
The findings reveal that strategically positioning gateways, especially on higher floors, significantly improves communication reliability and network efficiency, providing a solid framework for deploying LoRaWAN networks in intricate urban environments.
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