Papers by Ailton Oliveira
5G and beyond 5G (B5G) wireless networks will have considerable impacts in different areas, inclu... more 5G and beyond 5G (B5G) wireless networks will have considerable impacts in different areas, including the usage of unmanned aerial vehicles (UAVs). In this context, it is important to investigate how UAVs can interact with 5G/B5G networks [1]. To develop significant investigations involving UAVs and 5G/B55G networks it is important to have substantial amounts of data, however, it is exceedingly difficult to collect real measurements using UAVs connected to 5G systems [2]. A simulation framework called “Communication networks, Artificial intelligence and computer VIsion with 3D computergenerAted imageRy (CAVIAR)” was developed to simulate with realism the interaction between UAVs and 5G/B5G networks [3].
Some 6G use cases include augmented reality and high-fidelity holograms, with this information fl... more Some 6G use cases include augmented reality and high-fidelity holograms, with this information flowing through the network. Hence, it is expected that 6G systems can feed machine learning algorithms with such context information to optimize communication performance. This paper focuses on the simulation of 6G MIMO systems that rely on a 3-D representation of the environment as captured by cameras and eventually other sensors. We present new and improved Raymobtime datasets, which consist of paired MIMO channels and multimodal data. We also discuss tradeoffs between speed and accuracy when generating channels via ray-tracing. We finally provide results of beam selection and channel estimation to assess the impact of the improvements in the ray-tracing simulation methodology.
2021 IEEE Statistical Signal Processing Workshop (SSP), 2021
Some 6G use cases include augmented reality and highfidelity holograms, with this information flo... more Some 6G use cases include augmented reality and highfidelity holograms, with this information flowing through the network. Hence, it is expected that 6G systems can feed machine learning algorithms with such context information to optimize communication performance. This paper focuses on the simulation of 6G MIMO systems that rely on a 3-D representation of the environment as captured by cameras and eventually other sensors. We present new and improved Raymobtime datasets, which consist of paired MIMO channels and multimodal data. We also discuss tradeoffs between speed and accuracy when generating channels via ray-tracing. We finally provide results of beam selection and channel estimation to assess the impact of the improvements in the ray-tracing simulation methodology.
ITU Journal on Future and Evolving Technologies, 2021
Digital representations of the real world are being used in many applications, such as augmented ... more Digital representations of the real world are being used in many applications, such as augmented reality. 6G systems will not only support use cases that rely on virtual worlds but also benefit from their rich contextual information to improve performance and reduce communication overhead. This paper focuses on the simulation of 6G systems that rely on a 3D representation of the environment, as captured by cameras and other sensors. We present new strategies for obtaining paired MIMO channels and multimodal data. We also discuss trade-offs between speed and accuracy when generating channels via ray tracing. We finally provide beam selection simulation results to assess the proposed methodology.
Anais do XII Computer on the Beach - COTB '21, 2021
Unmanned aerial vehicles (UAVs) are being used in many applications,such as surveillance and prod... more Unmanned aerial vehicles (UAVs) are being used in many applications,such as surveillance and product delivery. Currently, manyUAVs are controlled by WiFi or proprietary radio technologies.However, it is envisioned that 5G and beyond 5G (B5G) networkscan connect the UAVs and increase the overall security due to improvedcontrol by operators and governments. Soon, UAVs willalso be used as mobile radio base stations to extend reach or improvethe network capacity. All this motivates intense research on5G technologies for supporting UAV-based applications. However,there are currently few simulation tools for testing and investigatingtelecommunication systems that involve UAV solutions. Forinstance, modern 5G networks use multiple antennas that enablebeamforming. A realistic simulation, in this case, requires not onlysupport for beamforming but also for realistic UAV trajectories,which impact the communication channel evolution over time. Toevaluate scenarios with connected UAVs, this pape...
Anais de XXXVIII Simpósio Brasileiro de Telecomunicações e Processamento de Sinais, 2020
Gathering channel data to test telecommunication systems is an essential step to guarantee the qu... more Gathering channel data to test telecommunication systems is an essential step to guarantee the quality of the product. However, it can be a slow process and demand a considerable amount of effort and investment since it is costly to make field measurements of mmWaves. Having a ready dataset at disposal make things way faster and cheaper, allowing a developer to focus on more specific tasks. This paper presents an entire multimodal dataset with different kinds of information like channel communication, urban traffic and obstacles position, got from two realistic computer simulations made in two different city models: Beijing and Rosslyn. It also includes detailed information on how each data is stored.
Anais de XXXVII Simpósio Brasileiro de Telecomunicações e Processamento de Sinais, 2019
Millimeter waves is one of 5G networks strategies to achieve high bit rates. Measurement campaign... more Millimeter waves is one of 5G networks strategies to achieve high bit rates. Measurement campaigns with these signals are difficult and require expensive equipment. In order to generate realistic data this paper refines a methodology for "virtual" measurements of 5G channels, which combines a simulation of urban mobility with a ray-tracing simulator. The urban mobility simulator is responsible for controlling mobility, positioning pedestrians and vehicles throughout each scene while the ray-tracing simulator is repeatedly invoked, simulating the interactions between receivers and transmitters. The orchestration among both simulators is done using a Python software. To check how the realism can influence the computational cost, it was made a numerical analyse between the number of faces and the simulation time.
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Papers by Ailton Oliveira