TFG: Design and Implementation of an NBIoT Communication System

The development of IoT product has generated multiple needs in the field of information and communication technologies. Among them, the challenge of creating technological products capable of functioning independently of the power grid arises, leading to a line of development in telecommunications that, instead of maximizing the transmission capabilities of a system, seeks to minimize its power consumption.

This TFG is developed within the ESTAR project, an autonomous IoT product meant for monitoring multiple environments. More specifically, it focuses on ESTAR_COMMS, the module which will be in charge of connecting the device to an external server.

In order to provide wireless communications with the lowest energy cost, an analysis of different components is given, concluding with the SARA-R510S-01B. The SARA has access to NBIoT radio technology from the LPWANs that allows for low speed, low payload, sporadic and Ultra-Low-Power transmissions.

In the thesis, the following results are presented:

  • A functional communication design and PCB prototype that uses the SARA-R510S-01B module, with an analysis of all design stages.
  • A first approach to the software design, in addition to a summary of the main AT commands that will be used to control the SARA.
  • The first energy consumption tests with the KeysightB2901A.

Conferencia en la Academia de las Ciencias y las Artes Militares

El pasado 1 de febrero nuestro compañero Octavio Nieto-Taladriz impartió la conferencia en la Academia de las Ciencias y las Artes Militares (ACAMI) titulada “Prueba de concepto: Munición cooperativa, aspectos tecnológicos”.

Breve extracto:

Una de las principales labores de la Universidad es la de generar nuevas ideas y conceptos y en el caso específico de las tecnológicas, como la del conferenciante, ver cómo llegar a prototipos o productos mínimos viables (MVP). En este caso se presentará como idea la creación de una “red social” de munición autónoma en la que sus elementos colaboren para lograr uno o varios objetivos comunes.

Para ello se partirá de dispositivos de munición básica convencional y sobre ella se incorporarán elementos que permiten la creación de un modelo de “red social”, todo ello bajo un punto de vista tecnológico y de industrialización. La parte de estrategias de colaboración, doctrina, ética y legalidad quedarán para un futuro evento de la ACAMI.

La grabación de la misma está disponible en el siguiente link:

Gated Recurrent Unit Neural Networks for Automatic Modulation Classification With Resource-Constrained End-Devices

The article “Gated Recurrent Unit Neural Networks for Automatic Modulation Classification With Resource-Constrained End-Devices” by our lab member Ramiro Utrilla has just been published in the IEEE Access, a high-impact open-access journal.

This work has been carried out in collaboration with researchers from the CONNECT – Centre for Future Networks and Communications in Dublin (Ireland), where Ramiro carried out a research stay of 3 months.

In this article, they focus on the Automatic Modulation Classification (AMC). AMC is essential to carry out multiple CR techniques, such as dynamic spectrum access, link adaptation and interference detection, aimed at improving communications throughput and reliability and, in turn, spectral efficiency. In recent years, multiple Deep Learning (DL) techniques have been proposed to address the AMC problem. These DL techniques have demonstrated better generalization, scalability and robustness capabilities compared to previous solutions. However, most of these techniques require high processing and storage capabilities that limit their applicability to energy- and computation-constrained end-devices.

In this work, they propose a new gated recurrent unit neural network solution for AMC that has been specifically designed for resource-constrained IoT devices.

The proposed GRU network model for AMC.

They trained and tested their solution with over-the-air measurements of real radio signals, which were acquired with the MIGOU platform.

Dataset generation scenario set up.

Comparison of signals recorded at (a) 1 and (b) 6 meters. The signals in the bottom row are the normalized version of those in the top row.

Their results show that the proposed solution has a memory footprint of 73.5 kBytes, 51.74% less than the reference model, and achieves a classification accuracy of 92.4%.

Increasing the training set can lead to improvements in the performance of a model without increasing its complexity. These improvements allow developers to reduce the complexity of the model and, therefore, the device resources it requires. However, longer training processes can lead to fitting and gradient problems. These tradeoffs should be explored when developing neural network-based solutions for resource-constrained end-devices.

A Methodology for Choosing Time Synchronization Strategies for Wireless IoT Networks

This summer we have published a new article about time synchronization for wireless sensor networks, applied to the field of IoT, in Sensors Open Access Journal. This journal has these statistics:

  • 2018 Impact Factor: 3.031
  • 5-year Impact Factor: 3.302
  • JCR category rank: 15/61 (Q1) in ‘Instruments & Instrumentation’

This article belongs to the Special Issue Topology Control and Protocols in Sensor Network and IoT Applications.

This article has a direct relationship with the thesis of our colleague Francisco Tirado-Andrés. This thesis investigates a methodology, and associated tools, to make it easier for all researchers to choose time synchronization protocols for specific WSNs.

For more information about this article please visit MDPI webpage.

TFM: Development of a protocol for the wireless communication of monitoring data for real- time representation

With the development of the IoT, the number of devices of different nature and size
that are distributed throughout the environment has increased enormously, generating data
continuously. These data can often be processed where we generate them. However
sometimes we can not have enough computing power to do it or we want to access them
remotely to see the correct functioning of a system or for example to store them in a
With this background it makes necessary to develop an electronic system that can be
conected in an easy way to the place where we are generating the information and transport it
to our central node. For our particular case, we aspire to establish a real time stream in order
to represent the data in a graphic, in order to give to the user a proper view of the
performance of his sensor node.
We have developed a WIFI gateway that allows this automation that we have
explained. We have used the Zentri AMW 106, an ultralow consumption WIFI module who fits
perfect in our requirements. We can attach via serial (using UART) to our electronic system to
the module where we generate the data and creating a TCP-IP client send to our server
We have also made an effort in develop an user friendly application in the server side.

This application has the ability of representing the data we are sending in real time and at the
same time to store in a file having a register. This register can be accessed to consult the
values obtained in a certain time.