Álvaro Valcarce

Time-Series JEPA for Predictive Remote Control Under Capacity-Limited Networks

Abanoub M. Girgis, Álvaro Valcarce, Mehdi Bennis

In remote control systems, transmitting large data volumes (e.g., images, video frames) from wireless sensors to remote controllers is challenging when uplink capacity is limited (e.g., RedCap devices or massive wireless sensor networks). Furthermore, controllers often need only information-rich representations of the …

fi, fr (code pays fourni par la source)

Human-centric decision-making in cell-less 6G networks

Emma Chiaramello, Carla Fabiana Chiasserini, Francesco Malandrino, Alessandro Nordio et autres

In next-generation networks, cells will be replaced by a collection of points-of-access (PoAs), with overlapping coverage areas and/or different technologies. Along with a promise for greater performance and flexibility, this creates further pressure on network management algorithms, which must make joint decisions …

it, se, fr (code pays fourni par la source)

Quantized Precoding Under ACLR Constraints with FIR-DACs for Downlink MU-MIMO

Nicolas Schlegel, Chadi Jabbour, Álvaro Valcarce, Eric Wantiez

Scaling massive multiuser multiple-input multipleoutput (MIMO) to larger antenna numbers constrains each chain in terms of power consumption and implementation. In this paper, the use of low resolution digital-to-analog converters (DACs) enabling these large scale arrays in downlink multiuser massive MIMO is …

fr (code pays fourni par la source)

D4.3–AI-based Techniques for Sustainable & Human-friendly RRM

Carla Fabiana Chiasserini, Claudio Casetti, Roberto Garello, Stefano Buzzi et autres

This document summarizes the achievements of the CENTRIC consortium during the two and a half years of project duration. In particular, it describes the research outcomes of Task 4.2 focused on developing AI-driven techniques for sustainable and human-centric radio resource management. Indeed, …

it, fi, fr, gb (code pays fourni par la source)

D4.3–AI-based Techniques for Sustainable & Human-friendly RRM

Carla Fabiana Chiasserini, Claudio Casetti, Roberto Garello, Stefano Buzzi et autres

This document summarizes the achievements of the CENTRIC consortium during the two and a half years of project duration. In particular, it describes the research outcomes of Task 4.2 focused on developing AI-driven techniques for sustainable and human-centric radio resource management. Indeed, …

it, fi, fr, gb (code pays fourni par la source)

LLM-Based Emulation of the Radio Resource Control Layer: Towards AI-Native RAN Protocols

Ziming Liu, Bryan Liu, Álvaro Valcarce, Xiaoli Chu

Integrating Large AI Models (LAMs) into 6G mobile networks is a key enabler of the AI-Native Air Interface (AI-AI), where protocol intelligence must scale beyond handcrafted logic. This paper presents, to our knowledge, the first standards-compliant emulation of the Radio Resource Control …

Cellular Network Design for UAV Corridors via Data-Driven High-Dimensional Bayesian Optimization

Mohamed Benzaghta, Giovanni Geraci, David López-Pérez, Álvaro Valcarce

We address the challenge of designing cellular networks for uncrewed aerial vehicles (UAVs) corridors through a novel data-driven approach. We assess multiple state-of-the-art high-dimensional Bayesian optimization (HD-BO) techniques to jointly optimize the cell antenna tilts and half-power beamwidth (HPBW). We find that …

es, fr (code pays fourni par la source)

Cellular Network Design for UAV Corridors via Data-driven High-dimensional Bayesian Optimization

Mohamed Benzaghta, Giovanni Geraci, David López‐Pérez, Álvaro Valcarce

We address the challenge of designing cellular networks for uncrewed aerial vehicles (UAVs) corridors through a novel data-driven approach. We assess multiple state-of-the-art high-dimensional Bayesian optimization (HD-BO) techniques to jointly optimize the cell antenna tilts and half-power beamwidth (HPBW). We find that …

Data-driven Optimization and Transfer Learning for Cellular Network Antenna Configurations

Mohamed Benzaghta, Giovanni Geraci, David López-Pérez, Álvaro Valcarce

We propose a data-driven approach for large-scale cellular network optimization, using a production cellular network in London as a case study and employing Sionna ray tracing for site-specific channel propagation modeling. We optimize base station antenna tilts and half-power beamwidths, resulting in …

Data-Driven Optimization and Transfer Learning for Cellular Network Antenna Configurations

Mohamed Benzaghta, Giovanni Geraci, David López-Pérez, Álvaro Valcarce

We propose a data-driven approach for large-scale cellular network optimization, using a production cellular network in London as a case study and employing Sionna ray tracing for site-specific channel propagation modeling. We optimize base station antenna tilts and half-power beamwidths, resulting in …

es, fr (code pays fourni par la source)

Intent-Aware DRL-Based NOMA Uplink Dynamic Scheduler for IIoT

Salwa Mostafa, Mateus P. Mota, Álvaro Valcarce, Mehdi Bennis

We investigate the problem of supporting Industrial Internet of Things user equipments (IIoT UEs) with specific intents (i.e., requested quality of service (QoS)) and random traffic arrivals. We propose a centralized dynamic scheduler for time-frequency resources based on deep reinforcement learning (DRL) …

fi, fr (code pays fourni par la source)

Quantized Precoding Under ACLR Constraints with FIR-DACs for Downlink MU-MIMO

Nicolas Schlegel, Chadi Jabbour, Álvaro Valcarce, Eric Wantiez

Scaling massive multiuser multiple-input multipleoutput (MIMO) to larger antenna numbers constrains each chain in terms of power consumption and implementation. In this paper, the use of low resolution digital-to-analog converters (DACs) enabling these large scale arrays in downlink multiuser massive MIMO is …

fr (code pays fourni par la source)