Research Areas

It is the ability of computer systems to perform tasks that normally require human intelligence. This involves using machine learning algorithms and models for data analysis, decision-making, pattern recognition, and problem-solving. AI applications include speech recognition, computer vision, natural language processing, automation, and much more, permeating various sectors, such as telecommunications, agriculture, healthcare, finance, technology, and manufacturing.

Radio resource allocation refers to the efficient management and distribution of resources, such as bandwidth, power, beams, etc., for different wireless communication services, such as mobile networks and Wi-Fi. This process is crucial to avoid interference and ensure the effective use of the electromagnetic spectrum, optimizing signal transmission and reception capacity.

Advances in RF devices, driven by the exploration of unique electromagnetic phenomena in artificial materials known as metamaterials, have enhanced their capabilities. These materials are meticulously designed and manufactured, incorporating resonators with dimensions smaller than the operating wavelength, which is in line with homogenization theory. In our research, we investigate a wide range of applications for metamaterials, from (bio)sensors to antennas, covering the electromagnetic spectrum from the visible regime, with wavelengths on the order of nanometers, to waves with lengths on the order of centimeters. These innovative concepts are fundamental to overcoming various limitations that enable the use of mobile communications technology in different types of applications.

RIS or intelligent metasurfaces are a particular case of metamaterials in which a metamaterial is considered planar (2D), with a thickness much thinner than the working wavelength. For this particular case, metasurfaces are considered whose unit cells can be controllable to dynamically adjust the phase and amplitude of the reflected or transmitted waves. In this line of research, we have different fronts, one of them being the design and prototyping of metasurfaces, which is done using different physical principles for manipulating wavefronts. We also consider the use of different materials for application in wearable devices. Another front of research in this line is using AI and ML techniques to optimize signal propagation, minimize interference, and improve spectral efficiency. All of this is achieved by adjusting wave phases and amplitudes to direct signals in a personalized way, improving connectivity in challenging environments, and increasing the efficiency of the radio spectrum. This technology has demonstrated promising applications in 5G networks and beyond.

Flexible metasurfaces not only enable the manipulation of wavefronts in challenging environments but also have the potential to be integrated as wearable devices. A unique feature of this application is the use of properly adjusted resonance frequencies of metasurfaces for continuous and real-time monitoring of various vital signs, transforming them into an innovative type of sensor. In our laboratory, we address this application in all its stages, from design to manufacturing and implementation of this new technology.

WET is a technology based on radio frequency (RF) signals that allows charging a massive number of Internet of Things devices without the need for wires. Therefore, WET eliminates the need to change batteries, reduces financial and environmental costs, and extends the device's useful life. Additionally, WET enables innovative use cases such as completely battery-free operation and eliminating physical ports, enabling waterproof/dustproof designs, reducing form factor and electrical shock hazards, and reducing e-waste. Therefore, WET is considered a key technology for 5G networks and beyond.

A channel model is a mathematical representation of the possible effects of a communication channel through which wireless signals in different formats are propagated. The channel model can represent different phenomena, such as short-term fading, long-term fading, path loss, and mobility as the signals travel through the wireless medium. To support the current 5G specifications and the future 6G networks, propagation channel models in which the telecommunication systems will operate have been used to assess the required performances. Thus, channel models that fit well to practical applications and represent many propagation phenomena are welcomed when evaluating mobile access technologies.

The concept of a fluid antenna system (FAS) was proposed as a solution to overcome the performance of multiple-input multiple-output systems, and its implementation has been investigated since then. Researchers worldwide envisage using FAS for 6G as it leverages the spatial diversity in the small space of user equipment so that a single-antenna FAS can outperform the traditional maximal ratio combining. Research focused on investigating the performance of FAS under different channel models is still in its infancy but is progressing rapidly.