Energy-Efficient Adaptive Sensing in Low Power Wide Area Networks
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Low Power Wide Area Networks (LPWAN) is attracting attention from both research communities and the industry due to its low energy, long-range radio communication. Expectations of the capabilities of the LPWAN technologies, with LoRaWAN and NB-IoT being the two most prominent, are high. Standards organizations, such as the 3GPP, promise end-device battery life of more than ten years. However, little research has focused on investigating how this is achievable. This thesis provides a study on the energy characteristics of LPWAN end-devices, focusing on the prominent factors leading to increased energy consumption. The research further investigates the potential implications of applying Adaptive Sensing techniques to the system. From experiments with a Pycom Fipy LoRaWAN device, we show that energy consumption when transmitting uplink packets consists of two parts: an increasing linear factor related to increasing the packet payload size, plus a fixed cost independent of payload. Introducing accumulation of packets, or adaptive sensing, the fixed cost yields a potential reduction in end-device energy consumption of up to 9000 %, compared to using a fixed-rate transmission scheme. The results of the study also show that when adaptive sensing manages to reduce half of the transmitted packets, a seven-month increase in battery life is possible when using a 2400 mAh battery. This increase implies a 65 % extended battery life, even when sending only maximum payload packets.