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.
They trained and tested their solution with over-the-air measurements of real radio signals, which were acquired with the MIGOU platform.
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%.
The main objective of this Special Issue is to provide a common space for WSNs researchers to share their high quality research and outcomes, and disseminate them to the rest of the world. The topics include novel designs, developments, and management of smart systems with a focus on new applications. In addition to these, notable advancements in the performance of WSN are welcome.
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.
Como ya os comentamos hace unos días la visita de nuestro compañero Hacene Fouchal fue muy productiva. Una de las actividades que realizamos fue un artículo para el congreso Globecom’16 y por el gran trabajo realizado, el artículo ha sido aceptado.
El artículo propone un nuevo sistema de seguridad para redes de sensores inalámbricas (WSNs) que asegura la autenticación de los nodos aunque no tengan acceso a una autoridad de certificados. EL congreso se celebrará del 4 al 8 de Diciembre en Washington. Esperemos que sea una gran experiencia para Hacene.
Road traffic accidents are one of the main causes of death and disability worldwide. Workers responsible for maintaining and repairing roadways are especially prone to suffer these events, given their exceptional exposure to traffic. Since these actuations usually coexist with regular traffic, an errant driver can easily intrude the work area and provoke a collision. Some authors have proposed mechanisms aimed at detecting breaches in the work zone perimeter and alerting workers, which are collectively called intrusion alarm systems. However, they have several limitations and have not yet fulfilled the necessities of these scenarios. In this paper, we propose a new intrusion alarm system based on a Wireless Sensor Network (WSN). Our system is comprised of two main elements: vehicle detectors that form a virtual barrier and detect perimeter breaches by means of an ultrasonic beam and individual warning devices that transmit alerts to the workers. All these elements have a wireless communication interface and form a network that covers the whole work area. This network is in charge of transmitting and routing the alarms and coordinates the behavior of the system. We have tested our solution under real conditions with satisfactory results.