Uplink Transmission Probability Functions for LoRa-Based Direct-to-Satellite IoT: A Case Study

IEEE Trans. Aerosp. Electron. Syst.

et al. 2022

Self Cite

In this paper we introduce and design sparse constellations for Direct-to-Satellite Internet of Things (DtS-IoT). DtS-IoT does not require a ground infrastructure, because the devices are directly connected to Low Earth Orbit satellites acting as orbiting gateways. The key idea of sparse constellations is to significantly reduce the number of in-orbit DtS-IoT satellites by (i) a proper dimensioning of the delivery delay anyway present in resource-constrained IoT services, and (ii) an optimal positioning of the orbiting gateways. First, we analyze LoRa/LoRaWAN and NB-IoT standards and derive realistic constraints on the maximum gap time between two consecutive passing-by satellites. Then, we introduce and optimize an algorithm to design quasioptimal topologies for sparse IoT constellations. Finally, we apply our design to both global and regional coverage and we analyze the trade-off between latency, number of orbit planes and total number of satellites. Results show that sparse constellations can provide world-wide IoT coverage with only 12.5% and 22.5% of the satellites required by traditional dense constellations considering 3-hour and 2-hour gaps. Also, we show that regionspecific coverage of Africa and Europe can be achieved with only 4 and 3 satellites for LoRa/LoRaWAN and NB-IoT, respectively.

Section: A Sparse Lora/lorawan Constellationsmentioning

confidence: 99%

Sparse Satellite Constellation Design for Global and Regional Direct-to-Satellite IoT Services

Capez

Henn

IEEE Trans. Aerosp. Electron. Syst.

et al. 2022

Self Cite

“…More sophisticated and general routing approaches (e.g., Dijkstra or topology-aware Contact-Graph Routing [21]) can be easily added in the future thanks to our modular design. c) Beacon-based radio: As discussed by Vogelgesang et al [22], beacons can play an important role in announcing satellite presence and synchronizing end devices on the ground. In LORAWAN, this can be achieved leveraging the Class B mode of communication where the gateway periodically sends a beacon to synchronize the clock of enddevices and the reception windows for downlink slots.…”

Section: A Features A) Orbital Mechanicsmentioning

confidence: 99%

Simulating LoRa-Based Direct-to-Satellite IoT Networks with FLoRaSaT

2022 IEEE 23rd International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM)

Madoery

Mehdi

et al. 2022

Self Cite

Direct-to-Satellite-IoT (DTS-IOT) is a promising approach for data transfer to/from IoT devices in remote areas where deploying terrestrial infrastructure is not appealing or feasible. In this context, Low-Earth Orbit (LEO) satellites can serve as passing-by IoT gateways to which devices can offload buffered data to. However, transmission distance and orbital dynamics, combined with highly constrained devices on the ground makes DTS-IOT a very challenging problem. In fact, existing IoT medium access control protocols, negotiations schemes, etc. need to be revised and/or extended to scale up to these challenging conditions. The intricate time-dynamic aspects of DTS-IOT networks require of adequate simulation environments to assess the expected performance of enabling technologies. To make up for the lack of such tools, we present a novel eventdriven open-source end-to-end simulation tool coined FLORASAT. The simulator leverages Omnet++ and includes a benchmarking DTS-IOT scenario comprising 16 cross-linked LEO satellites and 1500 IoT nodes on the surface. Satellites and devices are connected using the standard LoRaWAN Low-Power Wide Area (LPWAN) protocol (Class A and B). FLORASAT allows the easy implementation and study of DTS-IOT radio access and core network protocols, and we take advantage of this flexibility to investigate expected network metrics and non-intuitive phenomena emerging from the resulting multi-gateway setup.

“…In this context, media access control (MAC) protocols for DtS-IoT are of paramount importance in massive deployments [10]. Furthermore, the network size under the footprint of the nanosatellite is a priori unknown, but an accurate network size estimation can be exploited by MAC protocols to optimize the shared uplink channel resources [11], [12].…”

Section: Introductionmentioning

confidence: 99%

“…Indeed, estimating a node population's size is a major factor for achieving scalability and energy efficiency on certain access control protocols [12], [13]. Additionally, knowing the number of devices to be served by a CubeSat guarantees the quality of service for their applications.…”

Section: Introductionmentioning

confidence: 99%

Network Size Estimation for Direct-to-Satellite IoT

Ilabaca

Montejo‐Sánchez²,

IEEE Internet Things J.

et al. 2023

The worldwide adoption of the Internet of things (IoT) depends on the massive deployment of sensor nodes and timely data collection. However, installing the required ground infrastructure in remote or inaccessible areas can be economically unattractive or unfeasible. Cost-effective nanosatellites deployed in low Earth orbits (LEO) are emerging as an alternative solution: on-board IoT gateways provide access to remote IoT devices, according to direct-to-satellite IoT (DtS-IoT) architectures. One of the main challenges of DtS-IoT is to devise communication protocols that scale to thousands of highly constrained devices served by likewise constrained orbiting gateways. In this paper, we tackle this issue by first estimating the (varying) size of the device set underneath the (mobile) nanosatellite footprint. Then, we demonstrate applicability of the estimation when used to intelligently throttle DtS-IoT access protocols. Since recent works have shown that MAC protocols improve the throughput and energy efficiency of a DtS-IoT network when a network size estimation is available, we present here a novel and computationally-efficient network size estimator in DtS-IoT: our optimistic collision information (OCI) based estimator. We evaluate OCI's effectiveness with extensive simulations of DtS-IoT scenarios. Results show that when using network size estimations, the scalability of a frame slotted Aloha-based DtS-IoT network is boosted 8-fold, serving up to 4 × 10 3 devices, without energy efficiency penalties. We also show the effectiveness of the OCI mechanism given realistic detection ratios and demonstrate its low computational cost implementation, making it a strong candidate for network estimation in DtS-IoT.