Browsing by Author "Chen, Tzu-Yang"

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Increasing LoRaWAN Application-Layer Message Delivery Success Rates
(2018-01-01)
Wang, Shie-Yuan
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Chen, Tzu-Yang
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資訊工程學系
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Department of Computer Science
The LoRaWAN network is proposed for IoT applications and has the advantages of long range transmission and low power consumption. However, it suffers from very low data throughputs and long transmission duty cycle delays. In our real on-campus LoRaWAN deployment that has been lasting for one year, we found that even though we placed LoRaWAN end devices (nodes) at a short distance such as less than 700 meters from a LoRaWAN gateway, the packet loss rates at some locations are still too high to be acceptable. In this paper, we propose two approaches to overcome this high packet loss rate problem. We modified the IoT application running on nodes to let a node retransmit its lost data in multiple packets and help transmit its neighboring node's data. Our experimental results show that our approaches can effectively increase the application-layer message delivery success rate of LoRaWAN.
Performance of LoRa-based IoT Applications on Campus
(2017-01-01)
Wang, Shie-Yuan
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Chen, Yo-Ru
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Chen, Tzu-Yang
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Chang, Chia-Hung
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Cheng, Yu-Hsiang
To promote smart campus, National Chiao Tung University is deploying several location-based IoT applications based on wireless communications technologies including LoRa and NB-IoT. The applications are indoor/outdoor environment conditions monitoring (such as PM2.5, temperature, and humidity), emergency buttons, and so on. This paper uses PM2.5 measurement application as an example to present the performance of LoRa when it is used on campus. We investigated the LoRa transmission performance from LoRa end-devices to the LoRa gateway. We show how packet losses were affected by the distance between the end-device and the gateway, the transmit power, the payload length, the antenna angle, the time of day, and the weather conditions. The pattern of LoRa packet losses were also measured and we found that in our long-term PM2.5 monitoring application, more than 99% of LoRa packet losses occurred with three or less consecutive packet losses.