Reconfigurable Intelligent Surfaces

Designing and deploying reconfigurable intelligent surfaces to support wireless networks of the future

The future vision for 6G networks includes unlimited and near-instant connectivity. This vision revolves around space-air-ground integrated networks (SAGIN) and reconfigurable intelligent surfaces (RIS) are poised to facilitate this vision thanks to their potential to improve the coverage and capacity of wireless networks.

LATECE Domains

Socially useful technologies

LATECE Values

  • Transdisciplinarity
  • Accessibility
  • Knowledge transfer

Nature of the project

Wireless network engineering project

Official title of the project

Toward an efficient design and employment of reconfigurable intelligent surfaces in future wireless communication systems

The challenge

Finding practical and efficient methods and techniques to embed RIS technology into future SAGIN networks through efficient and advanced resource allocation algorithms rooted primarily in machine learning approaches.

The goal

Support Québec and Canada’s place in the fields of aerospace and information and communications technologies, attract talent to the province, contribute to innovation, and generate intellectual property.

Source:

D. Shahbaztabar, I. Trigui, W.-P. Zhu and W. Ajib, “Performance Analysis of RIS-Assisted Communication With Direct Link: A New Copula Application,” in IEEE Open Journal of the Communications Society, vol. 5, pp. 1740-1752, 2024

Target audiences

  • Local experts in the field of IT (Québec, Canada)
  • Telecommunications field (global)
  • General public

Start up

April 2023

Target end date

April 2027

Status

Validation and implementation stages

Leader

Wessam Ajib, PhD

Other LATECE members

Gunes Karabulut Kurt

Other collaborators

Wei-Ping Zhu, Concordia University

LATECE student collaborators

  • Minh Dat Nguyen, Postdoc
  • Cirine Chaieb, PhD(c)
  • Ahmed Kasaeyan, PhD(c)
  • Ndieye Fatou Diop, MSc(c)
  • Leila Marandi, MSc(c)

Keywords

Wireless networks, resource allocation, reconfigurable intelligent surfaces, machine learning, energy efficiency

Partners and Funders

  • Fonds de recherche du Québec – Nature et technologies (FRQNT)

Funding

$150,000