ESR 11


Eloise de Carvalho Rodrigues


Eloise received her Diploma of Computer Engineering from the Federal University of Ceara – UFC (Sobral, Brazil) in 2019, where she carried out applied research in wireless communication, especially in Radio Resource Allocation for 4G and 5G mobile communication networks. From Aug. 2017 to Sep. 2018, she held an academic mobility scholarship funded by the Brazilian government, in the frame of the BRAFITEC program, at Telecom SudParis – TSP (Evry, France), where she studied Emerging Services and Networks. As a Research Intern at Nokia Bell Labs (Paris-Saclay, France) from Feb. 2018 to Aug. 2018, she contributed to the final physical proof of concept of a low cost, low power consumption optical add/drop system and a WDM backplane in the framework of the French national project N -GREEN (New-Generation of Routers for Energy Efficient Networks). In June 2019, she joined Nokia Bell Labs (Dublin, Ireland – Paris, France) and Pompeu Fabra University – UPF (Barcelona, Spain) as a Marie-Curie Early Stage Researcher, and her Ph.D. research work focuses on wireless networks for autonomous robots. Her research interests include wireless networks, radio resource allocation, optimisation, machine learning, and related topics.

Research updates – Period 1

The research key target is to design novel radio resource management techniques for enabling high-demand machine-type applications, focusing on Industry 4.0 scenarios. These techniques will enhance the latency and reliability performance of the wireless communications system and will allow the command and control of energy-autonomous portable access points mainly by optimizing mechanisms that may potentially cause issues to low-latency applications.

A way to achieve low-latency and reliability is through cost-effective reuse of wireless network infrastructure and spectrum, either by optimizing existing communication protocols, e.g., taking advantage of widely developed infrastructures and standards, or even designing new ones, e.g., using artificial intelligence to learn optimized communication protocols. In line with this, my research has been focusing on techniques to improve latency in systems operating in the unlicensed spectrum—notably using Wi-Fi. Some challenges of operating in the unlicensed spectrum, such the mandatory listen before talk (LBT), can be addressed by increasing spatial reuse (SR). The first part of the studied provided an extensive analysis of the benefits of enabling the Parameterized Spatial Reuse (PSR) feature in 802.11ax WLANs in terms of reduced latency, concluding that PSR can offer up to a 3.8x reduction in the worst-case latencies for delay-sensitive stations with respect to an 802.11ax system without PSR. Moreover, our study demonstrates that, for low-latency communications, providing the network with PSR capabilities may be an appealing alternative to the deployment of more costly multi-antenna APs.




Alvaro Valcarce Rial,

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