activity
20192022
most citedWi-Fi Rate Adaptation using a Simple Deep Reinforcement Learning Approach

2 citations · 2 across the 4 of their papers we have counts for

collaborators

7 papers

cs.NI20222 cited

Wi-Fi Rate Adaptation using a Simple Deep Reinforcement Learning Approach

Ruben Queiros, Eduardo Nuno Almeida, Helder Fontes +2

The increasing complexity of recent Wi-Fi amendments is making optimal Rate Adaptation (RA) a challenge. The use of classic algorithms or heuristic models to address RA is becoming…

cs.NI2020

A Fast Gateway Placement Algorithm for Flying Networks

Gonçalo Santos, João Martins, André Coelho +3

The ability to operate anywhere, anytime, as well as their capability to hover and carry cargo on board make Unmanned Aerial Vehicles (UAVs) suitable platforms to act as Flying Gat…

cs.NI2020

On the Reproduction of Real Wireless Channel Occupancy in ns-3

Renato Cruz, Helder Fontes, José Ruela +2

In wireless networking R&D we typically depend on simulation and experimentation to evaluate and validate new networking solutions. While simulations allow full control over the sc…

cs.NI2019

A Routing Metric for Inter-flow Interference-aware Flying Multi-hop Networks

André Coelho, Eduardo Nuno Almeida, José Ruela +2

The growing demand for broadband communications anytime, anywhere has paved the way to the usage of Unmanned Aerial Vehicles (UAVs) for providing Internet access in areas without n…

cs.NI2019

Traffic-aware Gateway Placement for High-capacity Flying Networks

André Coelho, Helder Fontes, Rui Campos +1

The ability to operate virtually anywhere and carry payload makes Unmanned Aerial Vehicles (UAVs) perfect platforms to carry communications nodes, including Wi-Fi Access Points (AP…

cs.NI2019

A Token-Based MAC Solution for WiLD Point-To-Multipoint Links

Carlos Leocadio, Tiago Oliveira, Pedro Silva +2

The inefficiency of the fundamental access method of the IEEEE 802.11 standard is a well-known problem in scenarios where multiple long range and faulty links compete for the share…