scholarly journals Collision prediction for a low power wide area network using deep learning methods

2020 ◽  
Vol 22 (3) ◽  
pp. 205-214 ◽  
Author(s):  
Shengmin Cui ◽  
Inwhee Joe
2019 ◽  
Vol 11 (3) ◽  
pp. 57 ◽  
Author(s):  
Lorenzo Vangelista ◽  
Marco Centenaro

The low-power wide-area network (LPWAN) paradigm is gradually gaining market acceptance. In particular, three prominent LPWAN technologies are emerging at the moment: LoRaWAN™ and SigFox™, which operate on unlicensed frequency bands, and NB-IoT, operating on licensed frequency bands. This paper deals with LoRaWAN™, and has the aim of describing a particularly interesting feature provided by the latest LoRaWAN™ specification—often neglected in the literature—i.e., the roaming capability between different operators of LoRaWAN™ networks, across the same country or even different countries. Recalling that LoRaWAN™ devices do not have a subscriber identification module (SIM) like cellular network terminals, at a first glance the implementation of roaming in LoRaWAN™ networks could seem intricate. The contribution of this paper consists in explaining the principles behind the implementation of a global LoRaWAN network, with particular focus on how to cope with the lack of the SIM in the architecture and how to realize roaming.


Author(s):  
Paulo Renato Câmera da Silva ◽  
Herman Augusto Lepikson ◽  
Marcus Vinícius Ivo da Silva ◽  
Rafael Barbosa Mendes

2020 ◽  
Vol 19 (11) ◽  
pp. 1876-1880
Author(s):  
Grzegorz Bogdan ◽  
Konrad Godziszewski ◽  
Yevhen Yashchyshyn

Sensors ◽  
2020 ◽  
Vol 20 (4) ◽  
pp. 1008 ◽  
Author(s):  
Seungku Kim ◽  
Heonkook Lee ◽  
Sungho Jeon

When the low power wide area network (LPWAN) was developed for the internet of things (IoT), it attracted significant attention. LoRa, which is one of the LPWAN technologies, provides low-power and long-range wireless communication using a frequency band under 1 GHz. A long-range wide area network (LoRaWAN) provides a simple star topology network that is not scalable; it supports multi-data rates by adjusting the spreading factor, code rate, and bandwidth. This paper proposes an adaptive spreading factor selection scheme for corresponding spreading factors (SFs) between a transmitter and receiver. The scheme enables the maximum throughput and minimum network cost, using cheap single channel LoRa modules. It provides iterative SF inspection and an SF selection algorithm that allows each link to communicate at independent data rates. We implemented a multi-hop LoRa network and evaluated the performance of experiments in various network topologies. The adaptive spreading factor selection (ASFS) scheme showed outstanding end-to-end throughput, peaking at three times the performance of standalone modems. We expect the ASFS scheme will be a suitable technology for applications requiring high throughput on a multi-hop network.


2017 ◽  
Vol 13 (3) ◽  
pp. 155014771769941 ◽  
Author(s):  
Juha Petäjäjärvi ◽  
Konstantin Mikhaylov ◽  
Marko Pettissalo ◽  
Janne Janhunen ◽  
Jari Iinatti

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