Journal of Communication and Information Systems https://jcis.sbrt.org.br/jcis <p>The Journal of Communication and Information Systems (JCIS) features high-quality, peer-reviewed technical papers in several areas of communications and information systems. The JCIS is jointly sponsored by the Brazilian Telecommunications Society (SBrT) and the IEEE Communications Society (ComSoc). As from June 2020, Prof. Rausley Adriano Amaral de Souza from National Institute of Telecommunications (Inatel) and Prof. José Cândido Silveira Santos Filho from University of Campinas (UNICAMP) are the Editors-in-Chief of the JCIS.&nbsp;</p> <p>There are no article publication or submission charges. Previous editions of the JCIS can be accessed <a href="/index.php/JCIS/issue/archive" target="_blank" rel="noopener">here</a>.</p> <p>This is an open access journal which means that all content is freely available without charge to the user or his/her institution, permanently accessible online immediately upon assignment of the DOI. Users are allowed to read, download, copy, distribute, print, search, or link to the full texts of the articles, or use them for any other lawful purpose, without asking prior permission from the publisher or the author. This is in accordance with the BOAI definition of open access.</p> <p>ISSN: 1980-6604</p> Brazilian Telecommunications Society en-US Journal of Communication and Information Systems 1980-6604 <p><span>Authors who publish with this journal agree to the following terms:</span><br /><br /></p><ol type="a"><ol type="a"><li>Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a <a href="https://creativecommons.org/licenses/by/3.0/" target="_new">Creative Commons Attribution License</a> that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.</li></ol></ol><p> </p><ol type="a"><ol type="a"><li>Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.</li></ol></ol><p> </p><ol type="a"><ol type="a"><li>Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See <a href="http://opcit.eprints.org/oacitation-biblio.html" target="_new">The Effect of Open Access</a>).</li></ol></ol><p>___________</p> Improving Bluetooth Mesh Energy Efficiency Using Clustering https://jcis.sbrt.org.br/jcis/article/view/788 <p>This work proposes a Clustering Algorithm to improve the energy efficiency of Bluetooth Mesh networks. To further reduce the burden over the Cluster Heads, a Radio Duty Cycling algorithm that requires only a simple modification on the Bluetooth packet transmission logic is proposed. Computer simulations show that the radio duty cycling and clustering methods are effective in improving energy efficiency. It is observed that duty cycling provides a 78% improvement on the energy efficiency. In addittion, simulations show that the proposed clustering technique is effective in controlling the excessive message replication that is inherent in flooding operation, which in turn have a positive impact on packet delivery ratio and network scalability. Finally, it can be observed that the proposed clustering algorithm together with the proposed radio duty cycling algorithm can provide an improvement on the energy efficiency when compared to the baseline Bluetooth Mesh profile.</p> Joelton Deonei Gotz Ohara Kerusauskas Rayel Guilherme Luiz Moritz ##submission.copyrightStatement## https://creativecommons.org/licenses/by/4.0 2021-08-30 2021-08-30 36 1 156 165 10.14209/jcis.2021.17 Iterative Error Decimation for Syndrome-Based Neural Network Decoders https://jcis.sbrt.org.br/jcis/article/view/776 <p>In this letter, we introduce a new syndrome-based decoder where a deep neural network (DNN) estimates the error pattern from the reliability and syndrome of the received vector. The proposed algorithm works by iteratively selecting the most confident positions to be the error bits of the error pattern, updating the vector received when a new position of the error pattern is selected. Simulation results for the (63,45) and (63,36) BCH codes show that the proposed approach outperforms existing neural network decoders. In addition, the new decoder is flexible in that it can be applied on top of any existing syndrome-based DNN decoder without retraining.</p> Jorge Kysnney Santos Kamassury Danilo Silva ##submission.copyrightStatement## https://creativecommons.org/licenses/by/4.0 2021-08-27 2021-08-27 36 1 151 155 10.14209/jcis.2021.16 An Analog Filter Bank-based Circuit for Performing the Adaptive Impedance Matching in PLC Systems https://jcis.sbrt.org.br/jcis/article/view/768 <div class="page" title="Page 1"> <div class="layoutArea"> <div class="column"> <p>Aiming to bring attention to the necessity of dealing with the dynamics of access impedance in electric power systems, this paper introduces an adaptive impedance matching circuit that is based on an analog filter bank approach. In this sense, it describes a prototype that validates the proposed filter bank approach for improving impedance matching. Numerical results obtained with the detailed prototype operating in the frequency band between 2 and 500 MHz show that the proposed analog filter bank approach helps to improve impedance matching in power line communication (PLC) systems. Also, the numerical results show that the dynamics of impedance matching between two or more PLC transceivers is a difficult task to be accomplished because real-time coordination among them is necessary. Overall, it is shown that the proposed analog filter bank approach constitutes an interesting research direction for improving impedance matching between PLC transceivers and electric power systems.</p> </div> </div> </div> Luís Guilherme da Silva Costa Antônio Carlos Moreirão de Queiroz Vinícius Lagrota Rodrigues da Costa Moisés Vidal Ribeiro ##submission.copyrightStatement## https://creativecommons.org/licenses/by/4.0 2021-08-20 2021-08-20 36 1 133 150 10.14209/jcis.2021.15 Optimizing the Spectral Efficiency in mmWave Massive SU-MIMO Systems Using Hybrid Processing https://jcis.sbrt.org.br/jcis/article/view/786 <p>In this letter, a methodology to optimize the spectral efficiency in downlink massive single-user multiple-input multiple-output (SU-MIMO) millimeter-wave (mmWave) systems is proposed. Making use of a hierarchical strategy, four optimization sub-problems are formulated, whose solutions and derivations are strongly related to each other. This fact produces efficient coordination between the parties involved such that higher spectral efficiency is achieved. Therefore, the main feature of the proposed methodology relies on the coordination of the proposed RF and passband beamformer of both the transmitter and the receiver. This fact produced that the proposed hybrid processing surpasses the considered hybrid processings and even the considered fully-digital technique in the simulated scenarios.</p> Alvaro Javier Ortega ##submission.copyrightStatement## https://creativecommons.org/licenses/by/4.0 2021-07-25 2021-07-25 36 1 128 132 10.14209/jcis.2021.14 MUSA Grant-Free Access Framework and Blind Detection Receiver https://jcis.sbrt.org.br/jcis/article/view/771 <p>Recently, a non-orthogonal multiple access scheme called multi-user shared access (MUSA) was proposed to provide massive connection capability of low-complexity devices in the 5G networks. MUSA achieves higher spectral efficiency allowing independent devices to transmit data on the same physical layer time-frequency resources. Furthermore, MUSA introduces a grant-free transmission and a blind multi-user detection at the receiver, reducing the complexity on the transmit side. This approach is interesting for Internet of Things applications over mobile communication networks, where the devices have limited power and processing capacity. The references available in the literature about this multiple access scheme do not bring sufficient details about the MUSA multi-user detector. This limitation makes it difficult to evaluate the MUSA performance and to propose improvements for this new technique. The main goal of this paper is to provide a framework describing the entire communication chain using MUSA as multiple access. This paper also brings a proposal for a blind multi-user detection, where the information about the MUSA parameters and the channel state information are unknown at the receiver side. The performance of the MUSA multi-user detector is improved by a deep learning based processing that improves the quality of the channel estimation provided by a initial minimum mean square error estimator. The proposed deep neural network architecture employed to improve the channel estimation allows more users to share the same time-frequency resources for a given target block error rate, increasing the overall spectrum efficiency of the system.</p> Guilherme Pedro Aquino Tiago Cardoso Barbosa Marwa Chafii Luciano Leonel Mendes Abdul Karim Gizzini ##submission.copyrightStatement## https://creativecommons.org/licenses/by/4.0 2021-07-12 2021-07-12 36 1 119 127 10.14209/jcis.2021.13 Transient Analysis of the Bias-Compensated LMS Algorithm https://jcis.sbrt.org.br/jcis/article/view/762 <p>In most supervised adaptive filtering settings, only the additive noise of the reference signal is taken into account. However, in many practical situations the excitation data is also immersed in noise, which leads to a bias in the estimation procedure. In order to mitigate such issue, adaptive algorithms with bias compensation schemes have been proposed. This paper advances for the first time a stochastic model that predicts the average and mean-square learning behavior of the bias-compensated least mean squares algorithm in the transient region. Asymptotic predictions can also be obtained as a result of the devised analysis. Tracking capabilities and the impact of employing sub-optimal length adaptive filter are also considered, without restricting the input signal to be neither white nor Gaussian. Results indicate that the proposed analysis reveals accurate agreement with simulation results.</p> Rodrigo Marendaz Silva Pimenta Newton Norat Siqueira Mariane Rembold Petraglia Diego Barreto Haddad ##submission.copyrightStatement## https://creativecommons.org/licenses/by/4.0 2021-06-07 2021-06-07 36 1 114 118 10.14209/jcis.2021.12 Lightweight and Secure Publish-Subscribe System for Cloud-Connected Ultra Low Power IoT Devices https://jcis.sbrt.org.br/jcis/article/view/782 <p>The Internet of Things (IoT) enables the development of innovative applications in various domains such as healthcare, transportation, and Industry 4.0. The integration of the cloud platform's large processing and storage capacity with the ubiquitous sensing and actuation provided by the devices creates an IoT architecture that provides vast raw data. The IoT devices send the data to the cloud platform with the developed IoT applications, which can use publish-subscribe systems. However, messages with sensitive content require end-to-end security. Besides that, IoT devices may present processing, memory, payload, and energy restrictions. In this sense, messages in an IoT architecture need to achieve both energy-efficiency and secure message delivery. Thus, this article's main contribution refers to a system that standardizes the publish-subscribe topic and payload used by the cloud platform and the IoT devices. Our system also provides end-to-end security while surpassing the energy-efficiency to send data than the main related works in the literature regarding the use of publish-subscribe systems in IoT.</p> Norisvaldo Ferraz Junior Anderson A. A. Silva Adilson E. Guelfi Marcelo Teixeira de Azevedo Sergio Takeo Kofuji ##submission.copyrightStatement## https://creativecommons.org/licenses/by/4.0 2021-05-27 2021-05-27 36 1 100 113 10.14209/jcis.2021.11 Cascade of Linear Predictors for Deconvolution of Non-Stationary Channels in Sparse and Antisparse Scenarios https://jcis.sbrt.org.br/jcis/article/view/724 <p>This work deals with adaptive predictive deconvolution of non-stationary channels. In particular, we investigate the use of a cascade of linear predictors in the recovering of sparse and antisparse original signals. To do so, we first discuss the behavior of the Lp Prediction Error Filter (PEF), with p different of 2, showing that it has a superior ability to deal with non-minimum phase channels in comparison with the classical L2 PEF, although it still presents intrinsic limitations due to its direct linear structure. The cascade structure emerges as a possible solution to circumvent this issue. We apply the proposed cascade structure in the deconvolution of non-stationary channels, with minimum-, maximum- , mixed- and variable-phase response, and also noise scenarios. From the simulation results we observed that, besides the duality relation between the Lp norms, they present different algorithmic behavior: the L1 norm attains a fast convergence, enhancing the cascade tracking capacity, but is more sensible to noise. The L4 norm, on the other hand, is more robust to noise, but presents slower convergence and tracking capability.</p> Renan Brotto Kenji Nose-Filho Romis Attux João Marcos Travassos Romano ##submission.copyrightStatement## https://creativecommons.org/licenses/by/4.0 2021-05-10 2021-05-10 36 1 90 99 10.14209/jcis.2021.10 A Semi-Distributed Approach for Uplink Max-Min Energy Efficiency Optimization with Minimum User Satisfaction and Adjacency Constraints https://jcis.sbrt.org.br/jcis/article/view/777 <p>Maximizing energy efficiency is one of the pillars of modern networks. In this context, we consider in this letter a nonlinear max-min energy efficiency problem in the uplink of wireless networks. Due to the problem nonlinearity we resort to epigraph form so as to obtain an integer linear problem and to propose a centralized optimal solution for it using a branch-and-bound algorithm. Also because distributed solutions are useful to deal with high computational processing and scalability problems, we propose a low-complexity semi-distributed solution for the problem using a specific signaling scheme. Simulations show that the proposed semi-distributed solution performs closely to the centralized optimal scheme and outperforms state-of-the-art algorithms in terms of energy efficiency and outage rate.</p> Iran Mesquita Braga Jr. Francisco Rafael Marques Lima Tarcisio Ferreira Maciel Victor Farias Monteiro ##submission.copyrightStatement## https://creativecommons.org/licenses/by/4.0 2021-04-14 2021-04-14 36 1 85 89 10.14209/jcis.2021.9 Coupling Impact Between a Radial Antenna and Guided Modes on Twisted-Pair Systems Operating in Millimeter-Wave https://jcis.sbrt.org.br/jcis/article/view/754 <p>Recent research points out that transmission at terabits per second (Tbps) is feasible over copper cables if they were used as millimeter waveguides. The challenge is how to efficiently couple signals to the higher-order modes of twisted-pairs. This paper investigates the effectiveness of radial antennas on the coupling of near-terahertz signals to twisted-pairs. For that, the scattering parameter of the proposed antenna and the intensity of the electric field around the pairs are evaluated from numerical simulations. We also present the attenuation coefficients of four guided modes in a twisted-pair with typical constructive parameters and evaluate aggregate data rate results through Shannon's capacity. The results indicate the coupling efficiency may reach up to 71.62%, yielding an aggregate data rate over copper cables up to 0.17 Tbps at 10 m.</p> Brenda Sousa Daynara Dias Souza Gilvan Borges Roberto Rodrigues André Cavalcante João Costa ##submission.copyrightStatement## https://creativecommons.org/licenses/by/4.0 2021-03-08 2021-03-08 36 1 75 84 10.14209/jcis.2021.8