Closed-Form Joint Symbol and Channel Estimation in Hybrid-RIS-aided Communication Systems

Amarilton Lopes Magalhaes, Gilderlan Tavares de Araújo, Fazal-E- Asim, André de Almeida

DOI: 10.14209/sbrt.2024.1571036907

Keywords: RIS HRIS channel estimation tensor modeling

Abstract

In this work, we explore a hybrid reconfigurable intelligent surface in which the metasurface elements can sense a portion of the incoming signal while reflecting the remainder. We consider a single-user multiple-input multiple-output system whose channel between user terminal (UT) and HRIS experiences short-term changes due to UT mobility. Capitalizing on a tensor modeling approach, we propose a closed-form semi-blind receiver for the HRIS controller to estimate channels and symbols jointly without relying solely on training sequences. Simulation results have shown the robustness of our proposed closed-form semi-blind receiver in capturing all variations of the UT-HRIS channels while estimating data.

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Desempenho de Antenas Bowtie de Microfita com Diversas Estruturas DGS: Uma Análise para Aplicações em Wi-Fi 6 (IEEE802.11.AX), Redes 5G e Radar nas Bandas de 4 e 5 GHz

Fernanda Silva, Suely Silva Oliveira, Elioenay Jaiane Dias Goncalves

DOI: 10.14209/sbrt.2024.1571036908

Keywords: DGS Wifi 6 IEEE802.11.AX

Abstract

Este artigo apresenta o projeto e a análise de uma antena Bowtie com estrutura de Defeitos de Aterramento (DGS) para operação na faixa de frequência de 4 a 5 GHz, com foco na sua aplicação em redes sem fio de próxima geração, como o Wi-Fi 6 (IEEE802.11ax), com dimensões de 30 x 30 mm. O objetivo principal é verificar o desempenho de uma antena Bowtie utilizando diferentes formatos de DGS. Assim, a integração de antenas eficientes e adaptáveis desempenha um papel crucial na garantia da qualidade e do desempenho, especialmente em ambientes densos de usuários e dispositivos

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Improving Acoustic Echo Cancellation by Exploiting Prior Knowledge of RIR Energy Decay

Pedro de Carvalho Cayres Pinto, Roberto Campos, Mariane R Petraglia

DOI: 10.14209/sbrt.2024.1571036912

Keywords: Adaptive filters Acoustic echo cancellation Normalized least-mean-squares algorithm Affine Projection Algorithm

Abstract

Acoustic echo cancellation (AEC) through adaptive filters requires a large number of coefficients to establish good communication in reverberant environments. In order to increase the convergence rate of the adaptive algorithm, in this paper we explore the exponential decay rate of the room impulse response (RIR) by introducing an additional constraint, based on the energy relationship between blocks of coefficients, to the optimization problem. The performances of the proposed algorithms are investigated in different scenarios and compared with the performance of traditional algorithms employed in the AEC application. We also examine the influence of the algorithms' parameters in the convergence rate and final solution.

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DQAT: An Online Machine Learning Framework for Real-Time Data Quality Assurance in IoT

Marcos Lima Romero, Ricardo Suyama

DOI: 10.14209/sbrt.2024.1571036913

Keywords: Data Quality Machine Learning IoT Data Stream

Abstract

The Internet of Things (IoT) revolutionizes agriculture, but the quality of the generated data often hinders reliable decision-making. This study introduces the Data Quality Assurance Tool (DQAT), an open-source, event-driven framework tailored for real-time data assessment in IoT systems. DQAT's modular architecture enables seamless integration with existing applications and facilitates end-to-end scenario simulations. Utilizing online machine learning algorithms like Half-Space Trees and Support Vector Machines, DQAT detects anomalies in streaming data, outperforming traditional batch methods. Evaluation with agricultural datasets demonstrates DQAT's ability to monitor critical data quality dimensions, including accuracy, completeness, timeliness, and availability. This research directly contributes to enhancing the trustworthiness and utility of data for informed decision-making in the IoT sector.

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Protótipo de sistema de pasteurização de leite de búfala com controle e monitoramento via rede Wi-Fi

Andre Rafael Souza Biazotto, Diego K. N. Silva, Kamylle Vitória de Andrade Carneiro, Leslye Castro Eras, Maria Eduarda Araujo Massa

DOI: 10.14209/sbrt.2024.1571036916

Keywords: IoT bubalinocultura leiteira pasteurização MQTT

Abstract

This article describes the design of a Wi-Fi control and monitoring system for pasteurizing buffalo milk, aimed at small producers in the Amazon region, known for having the highest concentration of buffaloes in Brazil, providing them with an affordable solution. The system will be used specifically to sterilize and stabilize the milk until it is suitable for consumption and has greater durability and quality. In the work, various measurements and studies were carried out to support the use of Wi-Fi and the Internet of Things.

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Um Estudo Preliminar sobre Detecção de Pessoas a partir de Power-Line Communication (DP2LC)

Thiago Carneiro, Lisandro Lovisolo, Michel Pompeu Tcheou

DOI: 10.14209/sbrt.2024.1571036917

Keywords: PLC Detection HomePlug Presence

Abstract

Este estudo tem como objetivo avaliar o comportamento de portadoras OFDM em transmissões de dados utilizando PLCs e sua interação com corpos presentes no ambiente. Essa interação pode ser empregada como indicador para detectar pessoas em ambientes internos, de forma passiva sem um papel ativo do alvo. A infraestrutura de estudo foi idealizada e montada dentro de uma sala de aula. A análise das medições permite concluir que a detecção passiva da presença é possível. Além disso, os resultados preliminares apontam para a possibilidade de obter uma estimativa da posição do ocupante da sala.

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Intelligent People Flow Monitoring System in Indoor Environments Using YOLO and Cameras

Valdinei Rodrigues da Conceição, Aline Sena De Souza, Luiz Eduardo Nonato Dos Santos, Paulo Vinicius Rios Dos Anjos, Ryan Reis Oliveira, Glauco Estácio Gonçalves

DOI: 10.14209/sbrt.2024.1571037005

Keywords: Computer Vision YOLO Traffic analysis MQTT

Abstract

Monitoring people flow in indoor environments can help in the improvement of marketing strategies, the optimization of services, and is essential for access control and security in public places. This work addresses the implementation of an intelligent people monitoring system in commercial establishments. Using YOLO technology, the system aims to identify and count individuals in security camera footage. The proposed solution enables real-time detection and data transmission to an MQTT topic, easing the analysis of foot traffic in the monitored areas.

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Avaliação de funções-custo na super-resolução de imagens para jogos eletrônicos

Felippe Durán V. G. Santos, Renato Candido, Magno T. M. Silva

DOI: 10.14209/sbrt.2024.1571037068

Keywords: Super-resolução de imagens aprendizado profundo redes neurais convolucionais jogos eletrônicos

Abstract

A reconstrução de imagens em super-resolução tem sido de interesse em diversas áreas, como imagens médicas, vigilância, jogos eletrônicos, entre outras. Neste trabalho, são avaliadas diferentes funções-custo no contexto de super-resolução de imagens para jogos eletrônicos. Para isso, utiliza-se uma versão simplificada do modelo de [1], que faz uso de múltiplos quadros, seus respectivos mapas de profundidade e vetores de movimento. Além das funções-custo tradicionais como o erro quadrático médio, o erro absoluto médio e a obtida do índice de similaridade estrutural, avaliam-se a perceptual loss e a G-loss. Resultados experimentais mostram que a escolha de diferentes camadas da perceptual loss tem influência positiva no desempenho e que a combinação dessas funções-custo com ela pode resultar em detalhes que melhoram a percepção qualitativa das imagens.

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Digital Inclusion in Amazon with Starlink Backhauling and Mobile Telephony

Ryan Reis Oliveira, Aldebaro Klautau, Ilan S Correa, Leonardo Ramalho

DOI: 10.14209/sbrt.2024.1571037073

Keywords: Community Networks Open Source EPC Satellite Backhaul Digital Inclusion

Abstract

This work presents a cost-effective solution for extending internet access to underserved communities in the Amazon and other isolated regions. By deploying private LTE networks using open-source software, such as MagmaCore, a core network solution, and leveraging satellite backhaul connectivity, we address the limitations of WiFi based community networks. Our approach offers wider coverage, scalability, and quality of service, making it an attractive option for rural connectivity. Through the integration of open-source software and satellite technology, we demonstrate a scalable and affordable strategy for bridging the digital divide in remote areas.

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Um Novo Método de Fatoração Não Negativa em Modelos Bilineares: Aplicação em Separação de Fontes Espectrais

Alejandra J Inga Quezada, Yannick Deville, Leonardo Tomazeli Duarte

DOI: 10.14209/sbrt.2024.1571037391

Keywords:

Abstract

In hyperspectral remote sensing, sensors collect data that contain mixed pixels, which have mixed spectra of more than one pure material (endmembers). Recovering the spectra of these endmembers can be formulated as a blind source separation problem, for which non-negative matrix factorization (NMF) techniques have been used extensively. Non-linear extensions of NMF have been shown to be capable of dealing with non-linear aspects in certain spectral mixing processes (imaging urban areas). This article proposes a new non-negative factorization method for bilinear mixture models. Our proposal considers a projection operator that allows non-negativity to be maintained while preserving as much information as possible. Numerical experiments with two sets of synthetic hyperspectral data indicate that the proposal performs better than other methods in the literature.

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