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Dive into the research topics where Iván A. Pérez-Álvarez is active.

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Featured researches published by Iván A. Pérez-Álvarez.


Sensors | 2017

Underwater Electromagnetic Sensor Networks—Part I: Link Characterization

Gara Quintana-Díaz; Pablo Mena-Rodríguez; Iván A. Pérez-Álvarez; Eugenio Jiménez; Blas-Pablo Dorta-Naranjo; Santiago Zazo; Marina Pérez; Eduardo Quevedo; Laura Cardona; J. Hernández

Underwater Wireless Sensor Networks (UWSNs) using electromagnetic (EM) technology in marine shallow waters are examined, not just for environmental monitoring but for further interesting applications. Particularly, the use of EM waves is reconsidered in shallow waters due to the benefits offered in this context, where acoustic and optical technologies have serious disadvantages. Sea water scenario is a harsh environment for radiocommunications, and there is no standard model for the underwater EM channel. The high conductivity of sea water, the effect of seabed and the surface make the behaviour of the channel hard to predict. This justifies the need of link characterization as the first step to approach the development of EM underwater sensor networks. To obtain a reliable link model, measurements and simulations are required. The measuring setup for this purpose is explained and described, as well as the procedures used. Several antennas have been designed and tested in low frequency bands. Agreement between attenuation measurements and simulations at different distances was analysed and made possible the validation of simulation setups and the design of different communications layers of the system. This leads to the second step of this work, where data and routing protocols for the sensor network are examined.


Sensors | 2016

Underwater Electromagnetic Sensor Networks, Part II: Localization and Network Simulations

Javier Zazo; Sergio Valcarcel Macua; Santiago Zazo; Marina Pérez; Iván A. Pérez-Álvarez; Eugenio Jiménez; Laura Cardona; Joaquín Hernández Brito; Eduardo Quevedo

In the first part of the paper, we modeled and characterized the underwater radio channel in shallow waters. In the second part, we analyze the application requirements for an underwater wireless sensor network (U-WSN) operating in the same environment and perform detailed simulations. We consider two localization applications, namely self-localization and navigation aid, and propose algorithms that work well under the specific constraints associated with U-WSN, namely low connectivity, low data rates and high packet loss probability. We propose an algorithm where the sensor nodes collaboratively estimate their unknown positions in the network using a low number of anchor nodes and distance measurements from the underwater channel. Once the network has been self-located, we consider a node estimating its position for underwater navigation communicating with neighboring nodes. We also propose a communication system and simulate the whole electromagnetic U-WSN in the Castalia simulator to evaluate the network performance, including propagation impairments (e.g., noise, interference), radio parameters (e.g., modulation scheme, bandwidth, transmit power), hardware limitations (e.g., clock drift, transmission buffer) and complete MAC and routing protocols. We also explain the changes that have to be done to Castalia in order to perform the simulations. In addition, we propose a parametric model of the communication channel that matches well with the results from the first part of this paper. Finally, we provide simulation results for some illustrative scenarios.


IEEE Transactions on Cognitive Communications and Networking | 2015

Hybrid UCB-HMM: A Machine Learning Strategy for Cognitive Radio in HF Band

Laura Melián-Gutiérrez; Navikkumar Modi; Christophe Moy; Faouzi Bader; Iván A. Pérez-Álvarez; Santiago Zazo

Multiple users transmit in the HF band with worldwide coverage but collide with other HF users. New techniques based on cognitive radio principles are discussed to reduce the inefficient use of this band. In this paper, we show the feasibility of the Upper Confidence Bound (UCB) algorithm, based on reinforcement learning, for an opportunistic access to the HF band. The exploration vs. exploitation dilemma is evaluated in single-channel and multi-channel UCB algorithms in order to obtain their best performance in the HF environment. Furthermore, we propose a new hybrid system, which combines two types of machine learning techniques based on reinforcement learning and learning with Hidden Markov Models. This system can be understood as a metacognitive engine that automatically adapts its data transmission strategy according to HF environments behaviour to efficiently use spectrum holes. The proposed hybrid UCB-HMM system increases the duration of data transmissions slots when conditions are favourable, and is also able to reduce the required signalling transmissions between transmitter and receiver to inform which channels have been selected for data transmission. This reduction can be as high as 61% with respect to the signalling required by multi-channel UCB.


Wireless Personal Communications | 2017

Compressive Narrowband Interference Detection for Wideband Cognitive HF Front-Ends

Laura Melián-Gutiérrez; Adrian Garcia-Rodriguez; Iván A. Pérez-Álvarez; Santiago Zazo

An adaptive interference detector based on compressive sensing is introduced in this paper. The proposed detector is part of a narrowband interference mitigation system for wideband cognitive HF front-ends that self-adapts its configuration hinging on the behaviour of the automatic gain control. The use of a compressive sensing architecture allows us to significantly reduce the cost of the additional hardware required to perform the detection of harmful narrowband interfering signals. The proposed detector has been verified with real wideband HF signals and the results show that the adopted approach is a suitable alternative to detect a number of narrowband interfering signals without prior knowledge of their frequency location.


ursi atlantic radio science conference | 2015

DSA with reinforcement learning in the HF band

Laura Melián-Gutiérrez; Navikkumar Modi; Christophe Moy; Iván A. Pérez-Álvarez; Faouzi Bader; Santiago Zazo

Using the ionosphere as a passive reflector allows trans-horizon communications in the HF band, which covers the radiofrequency spectrum from 3 to 30 MHz. This band is mainly used for military communications, but also for aeronautical, maritime, and amateur communications. Besides its propagation changeability, the limitation of the HF band is the existence of multiple uncontrolled collisions between users. Even if HF stations use the Automatic Link Establishment protocol (MIL-STD-188-141B), they select their transmission channel according to its internal ranking based only on the channel propagation characteristics. Therefore, we propose to add some adaptability and cognition into the exploitation of the HF band as a good solution to diminish the inefficient use of the band.


military communications conference | 2007

Multi-Carrier Techniques Performance on Ionospheric Channel for Delay-Sensitive Applications

J. Lopez-Perez; S. Zazo-Bello; Iván A. Pérez-Álvarez; Ivana Raos; E. Mendieta-Otero

Multi-carrier modulations are widely employed in HF communications, and particularly OFDM, mainly because their ease of generation by means of DFT and also their appealing properties that can turn a selective fading channel into a set of flat channels. In order to cope with deep nulls in the channel traditional approach has been the use of channel coding and interleaving, thus causing an increase in communication delay. For delay-sensitive applications, spreading schemes over OFDM, such as OFDM-CDM can be applied. If CSI is known at transmitter, system performance can be improved by BER-optimum power loading and channel matrix SVD decomposition of OFDM-CDM signal. These techniques are well suited to delay-sensitive applications as they incur in no further delays.


Physical Communication | 2013

HF spectrum activity prediction model based on HMM for cognitive radio applications

Laura Melián-Gutiérrez; Santiago Zazo; J.L. Blanco-Murillo; Iván A. Pérez-Álvarez; Adrian Garcia-Rodriguez; B. Pérez-Díaz


HF Radio Systems and Techniques, 2003. Ninth International Conference on (Conf. Publ. No. 493) | 2003

Interactive digital voice over HF

Iván A. Pérez-Álvarez; I. Raos; S. Zazo; E. Mendieta-Otero; H. Santana-Sosa; J.M. Paez-Borrallo


Ionospheric radio Systems and Techniques, 2009. (IRST 2009). The Institution of Engineering and Technology 11th International Conference on | 2009

Real link of a high data rate OFDM modem: Description and performance

Iván A. Pérez-Álvarez; J. Lopez-Perez; Santiago Zazo; Ivana Raos; B. Perez-Diaz; E. Jimenez-Yguacel


international conference on communications | 2015

Upper Confidence Bound learning approach for real HF measurements

Laura Melián-Gutiérrez; Navikkumar Modi; Christophe Moy; Iván A. Pérez-Álvarez; Faouzi Bader; Santiago Zazo

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Dive into the Iván A. Pérez-Álvarez's collaboration.

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Santiago Zazo

Technical University of Madrid

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J. Lopez-Perez

University of Las Palmas de Gran Canaria

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Laura Melián-Gutiérrez

University of Las Palmas de Gran Canaria

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Marina Pérez

Technical University of Madrid

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B. Perez-Diaz

University of Las Palmas de Gran Canaria

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Eduardo Quevedo

Oceanic Platform of the Canary Islands

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Ivana Raos

Technical University of Madrid

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E. Jimenez-Yguacel

University of Las Palmas de Gran Canaria

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Javier Zazo

Technical University of Madrid

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Sergio Valcarcel Macua

Technical University of Madrid

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