Long-range Low-power Wireless Networks and Sampling Strategies in Electricity Metering
For smart city applications like electricity metering, this work provides a practical analysis of LoRa network performance and sampling strategies, though it is incremental in nature.
This paper evaluates LoRa-based wireless networks for smart electricity metering, showing that event-based sampling outperforms time-based sampling in reconstructing household consumption profiles, and analyzes how interference affects outage probability and bit-rate to determine gateway range for reliable signal reconstruction.
This paper studies a specific low-power wireless technology capable of reaching a long range, namely LoRa. Such a technology can be used by different applications in cities involving many transmitting devices while requiring loose communication constrains. We focus on electricity grids, where LoRa end-devices are smart-meters that send the average power demanded by their respective households during a given period. The successfully decoded data by the LoRa gateway are used by an aggregator to reconstruct the daily households' profiles. We show how the interference from concurrent transmissions from both LoRa and non-LoRa devices negatively affect the communication outage probability and the link effective bit-rate. Besides, we use actual electricity consumption data to compare time-based and event-based sampling strategies, showing the advantages of the latter. We then employ this analysis to assess the gateway range that achieves an average outage probability that leads to a signal reconstruction with a given requirement. We also discuss that, although the proposed analysis focuses on electricity metering, it can be easily extended to any other smart city application with similar requirements, like water metering or traffic monitoring.