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Telecommunications for the Digital Transformation

About the Group

The Telecommunications for Digital Transformation focus group provides solutions to fundamental problems  in networks and systems that transport information and make it possible to design platforms that drive the digital industry of the future and technologies, such as IoT, Smart Cities, Intelligent Transport Systems (ITS), smart-grid, Big-Data, e-health, 5G to improve society’s quality of life in the 21st century.

The group generates innovative solutions with diverse applications that require knowledge of multiple technologies and disciplines through cross-cutting work in areas that include telemedicine, logistics in industrial engineering, computer-based learning, intelligent systems, robotics, integrated circuit design for telecommunications, embedded systems and optics, among others. With these contributions, the group supports the generation of competitive teams with an in-depth vision of scientific and technological interrelations, benefitting industry with the development of new scenarios based on a communication technology infrastructure that will drive digital transformation, thereby triggering change in society.

The group focuses on aspects such as information representation, signal generation and transmission, optimal management methods for communications resources, the study and characterization of phenomena in the transmission medium, and the design of new algorithms that make it possible to reduce the effects that hinder effective communication. It also conducts systems and communication network performance studies, which are a key component for industries that require communications services. Statistical models are used to obtain performance, while supporting the design of information processing algorithms and Big Data to enhance such performance.

One of the most dynamic technological segments is wireless communications, which has huge potential markets, such as mobile health, intelligent transport systems (ITS), sensor networks, IoT, and 5G, among others. Wireless communications are moving towards a new era of Big-Data, and understanding the vast amount of information that will be located in wireless networks will facilitate network design and optimization methods that will benefit the equipment manufacturing industry, especially within modern networks where traffic now focuses more on data than on voice.

The group also focuses on the design and optimization of future communications networks, incorporating new devices, architectures and protocols. Future networks promise to infiltrate the infrastructure of mobile operators to offer Gb/s transfer rates. Emphasis is placed on the generation and modulation of millimetric signals and their propagation in the hybrid channel, as well as on the design and use of nanodevices in optical communication systems. 

Research lines

  • Information Processing for Future Technologies
  • Big-Data and Wireless Communications
  • High Speed ​​Communications


César Vargas Rosales -

Core researchers

Alejandro Aragón Zavala
Gabriel Campuzano Treviño
Gerardo Antonio Castañón Avila
Leyre Azpilicueta Fernandez de las Heras
Mahdi Zareei
Rafaela Villalpando Hernández


Adjunct researchers

Armando Céspedes Mota
Emmanuel Torres Rios
Enrique González Guerrero
Fernando Peña Campos
Jesús Arturo Pérez Díaz
José Alejandro Galaviz Aguilar
Ramón Martín Rodríguez Dagnino
Raúl Peña Ortega


Top 5 of publications 2015-2019

- Evolution of Indoor Positioning Technologies: A Survey
Authors: Brena, R., García-Vázquez, J., Galván-Tejada, C., Muñoz-Rodriguez, D., Vargas-Rosales, C., & Fangmeyer, J.

- Cloud based Video-on-Demand service model ensuring quality of service and scalability
Authors: Barba-Jimenez, C., Ramirez-Velarde, R., Tchernykh, A., Rodríguez-Dagnino, R., Nolazco-Flores, J., & Perez-Cazares, R.

- Artificial neural network nonlinear equalizer for coherent optical OFDM
Authors: Jarajreh, M., Giacoumidis, E., Aldaya, I., Le, S., Tsokanos, A., Ghassemlooy, Z., & Doran, N.

- Fiber nonlinearity-induced penalty reduction in CO-OFDM by ANN-based nonlinear equalization
Authors: Giacoumidis, E., Le, S., Ghanbarisabagh, M., McCarthy, M., Aldaya, I., Mhatli, S., Jarajreh, M., Haigh, P., Doran, N., Ellis, A., & Eggleton, B.

- Optimization of the distribution and localization of wireless sensor networks based on differential evolution approach
Authors: Céspedes-Mota, A., Castañón, G., Martínez-Herrera, A., & Cárdenas-Barrón, L.