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Wireless radio link design to improve near-shore ...

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This letter proposes a multi-gateway designation framework to design real-time wireless sensor networks (WSNs) improving traffic schedulability, i.e., meeting the traffic time constraints. To this end, we resort to Spectral Clustering un-supervised learning that allows defining arbitrary k disjoint clusters without knowledge of the nodes physical position. In each cluster we use a centrality metric from social sciences to designate one gateway. This novel combination is applied to a time-synchronized channel-hopping (TSCH) WSN under earliest-deadline-first (EDF) scheduling and shortest-path routing. Simulation results under varying configurations show that our framework is able to produce WSN designs that greatly reduce the worst-case network demand. In a situation with 5gateways, 99% schedulability can be achieved with 3.5 times more real-time flows than in a random benchmark.

Low-power wide-area networks are extending beyond the conventional terrestrial domain. Coastal zones, rivers, wetlands, among others, are nowadays common deployment settings for Internet-of-Things nodes where communication technologies such as LoRa are becoming popular. In this article, we investigate large-scale fading dynamics of LoRa line-of-sight links deployed over an estuary with characteristic intertidal zones, considering both shore-to-shore and shore-to-vessel communications. We propose a novel methodology for path loss prediction which captures i) spatial, ii) temporal and iii) physical features of the RF signal interaction with the environmental dynamics, integrating those features into the two-ray propagation model. To this purpose, we resort to precise hydrodynamic modeling of the estuary, including the specific terrain profile (bathymetry) at the reflection point. These aspects are key to accounting for a reflecting surface of varying altitude and permittivity as a function of the tide. Experimental measurements using LoRa devices operating in the 868~MHz band show major trends on the received signal power in agreement with the methodology's predictions.