54 citations · 112 across the 11 of their papers we have counts for
8 papers · 1 filter
Intent-Aware DRL-Based NOMA Uplink Dynamic Scheduler for IIoT
Salwa Mostafa, Mateus P. Mota, Alvaro Valcarce +1
We investigate the problem of supporting Industrial Internet of Things user equipment (IIoT UEs) with intent (i.e., requested quality of service (QoS)) and random traffic arrival.…
Emergent Communication Protocol Learning for Task Offloading in Industrial Internet of Things
Salwa Mostafa, Mateus P. Mota, Alvaro Valcarce +1
In this paper, we leverage a multi-agent reinforcement learning (MARL) framework to jointly learn a computation offloading decision and multichannel access policy with correspondin…
Designing Cellular Networks for UAV Corridors via Bayesian Optimization
Mohamed Benzaghta, Giovanni Geraci, David Lopez-Perez +1
As traditional cellular base stations (BSs) are optimized for 2D ground service, providing 3D connectivity to uncrewed aerial vehicles (UAVs) requires re-engineering of the existin…
Learning Random Access Schemes for Massive Machine-Type Communication with MARL
Muhammad Awais Jadoon, Adriano Pastore, Monica Navarro +1
In this paper, we explore various multi-agent reinforcement learning (MARL) techniques to design grant-free random access (RA) schemes for low-complexity, low-power battery operate…
Scalable Joint Learning of Wireless Multiple-Access Policies and their Signaling
Mateus P. Mota, Alvaro Valcarce, Jean-Marie Gorce
In this paper, we apply an multi-agent reinforcement learning (MARL) framework allowing the base station (BS) and the user equipments (UEs) to jointly learn a channel access policy…
The Emergence of Wireless MAC Protocols with Multi-Agent Reinforcement Learning
Mateus P. Mota, Alvaro Valcarce, Jean-Marie Gorce +1
In this paper, we propose a new framework, exploiting the multi-agent deep deterministic policy gradient (MADDPG) algorithm, to enable a base station (BS) and user equipment (UE) t…
Bayesian Optimization for Radio Resource Management: Open Loop Power Control
Lorenzo Maggi, Alvaro Valcarce Rial, Jakob Hoydis
We provide the reader with an accessible yet rigorous introduction to Bayesian optimisation with Gaussian processes (BOGP) for the purpose of solving a wide variety of radio resour…
Towards Joint Learning of Optimal MAC Signaling and Wireless Channel Access
Alvaro Valcarce, Jakob Hoydis
Communication protocols are the languages used by network nodes. Before a user equipment (UE) can exchange data with a base station (BS), it must first negotiate the conditions and…