258 research outputs found
Analysis of LoRaWAN Uplink with Multiple Demodulating Paths and Capture Effect
Low power wide area networks (LPWANs), such as the ones based on the LoRaWAN
protocol, are seen as enablers of large number of IoT applications and
services. In this work, we assess the scalability of LoRaWAN by analyzing the
frame success probability (FSP) of a LoRa frame while taking into account the
capture effect and the number of parallel demodulation paths of the receiving
gateway. We have based our model on the commonly used {SX1301 gateway chipset},
which is capable of demodulating {up to} eight frames simultaneously; however,
the results of the model can be generalized to architectures with arbitrary
number of demodulation paths. We have also introduced and investigated {three}
policies for Spreading Factor (SF) allocation. Each policy is evaluated in
terms of coverage {probability}, {FSP}, and {throughput}. The overall
conclusion is that the presence of multiple demodulation paths introduces a
significant change in the analysis and performance of the LoRa random access
schemes
5G NB-IoT via Low Density LEO Constellations
5G NB-IoT is seen as a key technology for providing truly ubiquitous, global 5G coverage (1.000.000 devices/km2) for machine type communications in the internet of things. A non-terrestrial network (NTN) variant of NB-IoT is being standardized in the 3GPP, which along with inexpensive and non-complex chip-sets enables the production of competitively priced IoT devices with truly global coverage. NB-IoT allows for narrowband single carrier transmissions in the uplink, which improves the uplink link-budget by as much as 16.8 dB over the 180 [kHz] downlink. This allows for a long range sufficient for ground to low earth orbit (LEO) communication without the need for complex and expensive antennas in the IoT devices. In this paper the feasibility of 5G NB-IoT in the context of low-density constellations of small-satellites carrying base-stations in LEO is analyzed and required adaptations to NB-IoT are discussed
Machine Learning Methods for Monitoring of Quasi-Periodic Traffic in Massive IoT Networks
One of the central problems in massive Internet of Things (IoT) deployments
is the monitoring of the status of a massive number of links. The problem is
aggravated by the irregularity of the traffic transmitted over the link, as the
traffic intermittency can be disguised as a link failure and vice versa. In
this work we present a traffic model for IoT devices running quasi-periodic
applications and we present both supervised and unsupervised machine learning
methods for monitoring the network performance of IoT deployments with
quasi-periodic reporting, such as smart-metering, environmental monitoring and
agricultural monitoring. The unsupervised methods are based on the Lomb-Scargle
periodogram, an approach developed by astronomers for estimating the spectral
density of unevenly sampled time series
A Modelling and Experimental Framework for Battery Lifetime Estimation in NB-IoT and LTE-M
To enable large-scale Internet of Things (IoT) deployment, Low-power
wide-area networking (LPWAN) has attracted a lot of research attention with the
design objectives of low-power consumption, wide-area coverage, and low cost.
In particular, long battery lifetime is central to these technologies since
many of the IoT devices will be deployed in hard-toaccess locations. Prediction
of the battery lifetime depends on the accurate modelling of power consumption.
This paper presents detailed power consumption models for two cellular IoT
technologies: Narrowband Internet of Things (NB-IoT) and Long Term Evolution
for Machines (LTE-M). A comprehensive power consumption model based on User
Equipment (UE) states and procedures for device battery lifetime estimation is
presented. An IoT device power measurement testbed has been setup and the
proposed model has been validated via measurements with different coverage
scenarios and traffic configurations, achieving the modelling inaccuracy within
5%. The resulting estimated battery lifetime is promising, showing that the
10-year battery lifetime requirement specified by 3GPP can be met with proper
configuration of traffic profile, transmission, and network parameters.Comment: submitted to IEEE Internet of Things Journal, 12 pages, 10 figure
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