Search Results for author: Boris Bellalta

Found 11 papers, 4 papers with code

A Federated Reinforcement Learning Framework for Link Activation in Multi-link Wi-Fi Networks

no code implementations28 Apr 2023 Rashid Ali, Boris Bellalta

However, given the limited number of available channels, the use of multiple links by a group of contending Basic Service Sets (BSSs) can result in higher interference and channel contention, thus potentially leading to lower performance and reliability.

Fairness reinforcement-learning +1

Federated Spatial Reuse Optimization in Next-Generation Decentralized IEEE 802.11 WLANs

no code implementations20 Mar 2022 Francesc Wilhelmi, Jernej Hribar, Selim F. Yilmaz, Emre Ozfatura, Kerem Ozfatura, Ozlem Yildiz, Deniz Gündüz, Hao Chen, Xiaoying Ye, Lizhao You, Yulin Shao, Paolo Dini, Boris Bellalta

As wireless standards evolve, more complex functionalities are introduced to address the increasing requirements in terms of throughput, latency, security, and efficiency.

Federated Learning

Machine Learning for Performance Prediction of Channel Bonding in Next-Generation IEEE 802.11 WLANs

no code implementations29 May 2021 Francesc Wilhelmi, David Góez, Paola Soto, Ramon Vallés, Mohammad Alfaifi, Abdulrahman Algunayah, Jorge Martin-Pérez, Luigi Girletti, Rajasekar Mohan, K Venkat Ramnan, Boris Bellalta

With the advent of Artificial Intelligence (AI)-empowered communications, industry, academia, and standardization organizations are progressing on the definition of mechanisms and procedures to address the increasing complexity of future 5G and beyond communications.

BIG-bench Machine Learning

Intelligent Reflecting Surfaces at Terahertz Bands: Channel Modeling and Analysis

no code implementations28 Mar 2021 Konstantinos Dovelos, Stylianos D. Assimonis, Hien Quoc Ngo, Boris Bellalta, Michail Matthaiou

An intelligent reflecting surface (IRS) at terahertz (THz) bands is expected to have a massive number of reflecting elements to compensate for the severe propagation losses.

Concurrent Decentralized Channel Allocation and Access Point Selection using Multi-Armed Bandits in multi BSS WLANs

no code implementations5 Jun 2020 Álvaro López-Raventós, Boris Bellalta

Finding a suitable network configuration able to maximize the performance of enterprise WLANs is a challenging task given the complex dependencies between APs and stations.

Multi-Armed Bandits Thompson Sampling

Usage of Network Simulators in Machine-Learning-Assisted 5G/6G Networks

2 code implementations17 May 2020 Francesc Wilhelmi, Marc Carrascosa, Cristina Cano, Anders Jonsson, Vishnu Ram, Boris Bellalta

Without any doubt, Machine Learning (ML) will be an important driver of future communications due to its foreseen performance when applied to complex problems.

BIG-bench Machine Learning

Spatial Reuse in IEEE 802.11ax WLANs

2 code implementations9 Jul 2019 Francesc Wilhelmi, Sergio Barrachina Muñoz, Cristina Cano, Ioannis Selinis, Boris Bellalta

In particular, the main objective of the SR operation is to maximize the utilization of the medium by increasing the number of parallel transmissions.

Networking and Internet Architecture

On the Performance of the Spatial Reuse Operation in IEEE 802.11ax WLANs

1 code implementation19 Jun 2019 Francesc Wilhelmi, Sergio Barrachina-Muñoz, Boris Bellalta

The Spatial Reuse (SR) operation included in the IEEE 802. 11ax-2020 (11ax) amendment aims at increasing the number of parallel transmissions in an Overlapping Basic Service Set (OBSS).

Networking and Internet Architecture

Implications of Decentralized Q-learning Resource Allocation in Wireless Networks

1 code implementation30 May 2017 Francesc Wilhelmi, Boris Bellalta, Cristina Cano, Anders Jonsson

Reinforcement Learning is gaining attention by the wireless networking community due to its potential to learn good-performing configurations only from the observed results.


Adapting Sampling Interval of Sensor Networks Using On-Line Reinforcement Learning

no code implementations7 Jun 2016 Gabriel Martins Dias, Maddalena Nurchis, Boris Bellalta

The time between two successive measurements is a critical parameter to set during the WSN configuration because it can impact the WSN's lifetime, the wireless medium contention and the quality of the reported data.

reinforcement-learning Reinforcement Learning (RL)

Predicting Occupancy Trends in Barcelona's Bicycle Service Stations Using Open Data

no code implementations14 May 2015 Gabriel Martins Dias, Boris Bellalta, Simon Oechsner

That is, users might avoid stations at times when they could not return a bicycle that they have rented before, or when they would not find a bike to rent.

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