Del-Puerto-Flores, J. Alberto
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Preferred name
Del-Puerto-Flores, J. Alberto
Official Name
Del Puerto Flores, José Alberto
Alternative Name
jpuerto
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ORCID
Scopus Author ID
57206905278
Researcher ID
AAR-1386-2020

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Publication

Precoding for RIS-Assisted Multi-User MIMO-DQSM Transmission Systems

2023 , Castillo-Soria, Francisco R. , Del-Puerto-Flores, J. Alberto , Azurdia-Meza, Cesar A. , Kumaravelu, Vinoth Babu , Simón, Jorge , Gutiérrez, Carlos A.

This paper presents two precoding techniques for a reconfigurable intelligent surface (RIS)-assisted multi-user (MU) multiple-input multiple-output (MIMO) double quadrature spatial modulation (DQSM) downlink transmission system. Instead of being applied at the remote RIS, the phase shift vector is applied at the base station (BS) by using a double precoding stage. Results show that the proposed RIS-MU-MIMO-DQSM system has gains of up to 17 dB in terms of bit error rate (BER) and a reduction in detection complexity of 51% when compared with the conventional MU-MIMO system based on quadrature amplitude modulation (QAM). Compared with a similar system based on amplify and forward (AF) relay-assisted technique, the proposed system has a gain of up to 18 dB in terms of BER under the same conditions and parameters.

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Machine Learning Strategies for Reconfigurable Intelligent Surface-Assisted Communication Systems—A Review

2024 , Ibarra Hernández, Roilhi F. , Castillo Soria, Francisco R. , Gutiérrez, Carlos Andres , García Barrientos, Abel , Vázquez Toledo, Luis Alberto , Del-Puerto-Flores, J. Alberto

Machine learning (ML) algorithms have been widely used to improve the performance of telecommunications systems, including reconfigurable intelligent surface (RIS)-assisted wireless communication systems. The RIS can be considered a key part of the backbone of sixth-generation (6G) communication mainly due to its electromagnetic properties for controlling the propagation of the signals in the wireless channel. The ML-optimized (RIS)-assisted wireless communication systems can be an effective alternative to mitigate the degradation suffered by the signal in the wireless channel, providing significant advantages in the system’s performance. However, the variety of approaches, system configurations, and channel conditions make it difficult to determine the best technique or group of techniques for effectively implementing an optimal solution. This paper presents a comprehensive review of the reported frameworks in the literature that apply ML and RISs to improve the overall performance of the wireless communication system. This paper compares the ML strategies that can be used to address the RIS-assisted system design. The systems are classified according to the ML method, the databases used, the implementation complexity, and the reported performance gains. Finally, we shed light on the challenges and opportunities in designing and implementing future RIS-assisted wireless communication systems based on ML strategies.

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Publication

Carrier Diversity Incorporation to Low-Complexity Near-ML Detection for Multicarrier Systems over V2V Radio Channel

2021 , Del-Puerto-Flores, J. Alberto , Fernando Peña-Campos , Ramón Parra-Michel , Del-Valle-Soto, Carolina

Inter-carrier interference (ICI) in vehicle to vehicle (V2V) orthogonal frequency division multiplexing (OFDM) systems is a common problem that makes the process of detecting data a demanding task. Mitigation of the ICI in V2V systems has been addressed with linear and non-linear iterative receivers in the past; however, the former requires a high number of iterations to achieve good performance, while the latter does not exploit the channel’s frequency diversity. In this paper, a transmission and reception scheme for low complexity data detection in doubly selective highly time varying channels is proposed. The technique couples the discrete Fourier transform spreading with non-linear detection in order to collect the available channel frequency diversity and successfully achieving performance close to the optimal maximum likelihood (ML) detector. When compared with the iterative LMMSE detection, the proposed system achieves a higher performance in terms of bit error rate (BER), reducing the computational cost by a third-part when using 48 subcarriers, while in an OFDM system with 512 subcarriers, the computational cost is reduced by two orders of magnitude.

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A Low-Cost Digital Vital Signs Capturer for Older Adults: Design, Development, and Implementation

2021 , Valdivia, Leonardo , Del-Valle-Soto, Carolina , Del-Puerto-Flores, J. Alberto , Gómez Aceves, Kalid , Arrobo, Sebastian

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Implications for Serious Game Design: Quantification of Cognitive Stimulation in Virtual Reality Puzzle Games through MSC and SpEn EEG Analysis

2024 , Gomez Romero Borquez, Jesus Alberto , Del-Valle-Soto, Carolina , Del-Puerto-Flores, J. Alberto , Castillo-Soria, Francisco R. , Maciel-Barboza F.M.

This paper investigates the cognitive stimulation experienced by players engaging in virtual reality (VR) puzzle games through the analysis of electroencephalography (EEG) data. The study employs magnitude-square coherence (MSC) and spectral entropy (SpEn) metrics to quantify neural activity patterns associated with problem-solving processes during gameplay. Results reveal unique coherence and entropy profiles across different VR gaming tasks, with Tetris gameplay eliciting heightened coherence and entropy values compared to other games. Specifically, Tetris demonstrates increased coherence between frontal and temporal brain regions, indicative of enhanced visuospatial processing and decision making. These findings underscore the importance of considering both spectral coherence and entropy when assessing the cognitive effects of video game tasks on brain activity. Insights from this study may inform the design of serious VR games aimed at promoting cognitive development and problem-solving skills in players.

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Performance Metric Analysis for a Jamming Detection Mechanism under Collaborative and Cooperative Schemes in Industrial Wireless Sensor Networks

2021 , Alejandro Cortés-Leal , Del-Valle-Soto, Carolina , Cesar Cardenas , Valdivia, Leonardo , Del-Puerto-Flores, J. Alberto

The emergence of Industry 4.0 technologies, such as the Internet of Things (IoT) and Wireless Sensor Networks (WSN), has prompted a reconsideration of methodologies for network security as well as reducing operation and maintenance costs, especially at the physical layer, where the energy consumption plays an important role. This article demonstrates through simulations and experiments that, while the cooperative scheme is more efficient when a WSN is at normal operating conditions, the collaborative scheme offers more enhanced protection against the aggressiveness of jamming in the performance metrics, thus making it safer, reducing operation and maintenance costs and laying the foundations for jamming mitigation. This document additionally offers an algorithm to detect jamming in real time. Firstly, it examines the characteristics and damages caused by the type of aggressor. Secondly, it reflects on the natural immunity of the WSN (which depends on its node density and a cooperative or collaborative configuration). Finally, it considers the performance metrics, especially those that impact energy consumption during transmission.

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Neurogaming in Virtual Reality: A Review of Video Game Genres and Cognitive Impact

2024 , Gomez Romero Borquez, Jesus Alberto , Del-Valle-Soto, Carolina , Del-Puerto-Flores, J. Alberto , Ramon A. Briseño , José Varela-Aldás

This work marks a significant advancement in the field of cognitive science and gaming technology. It offers an in-depth analysis of the effects of various video game genres on brainwave patterns and concentration levels in virtual reality (VR) settings. The study is groundbreaking in its approach, employing electroencephalograms (EEGs) to explore the neural correlates of gaming, thus bridging the gap between technology, psychology, and neuroscience. This review enriches the dialogue on the potential of video games as a therapeutic tool in mental health. The study’s findings illuminate the capacity of different game genres to elicit varied brainwave responses, paving the way for tailored video game therapies. This review contributes meaningfully to the state of the art by offering empirical insights into the interaction between gaming environments and brain activity, highlighting the potential applications in therapeutic settings, cognitive training, and educational tools. The findings are especially relevant for developing VR gaming content and therapeutic games, enhancing the understanding of cognitive processes, and aiding in mental healthcare strategies.

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Publication

Channel Characterization and SC-FDM Modulation for PLC in High-Voltage Power Lines

2022 , Del-Puerto-Flores, J. Alberto , José Luis Naredo , Fernando Peña-Campos , Del-Valle-Soto, Carolina , Valdivia, Leonardo , Ramón Parra-Michel

Digital communication over power lines is an active field of research and most studies in this field focus on low-voltage (LV) and medium-voltage (MV) power systems. Nevertheless, as power companies are starting to provide communication services and as smart-grid technologies are being incorporated into power networks, high-voltage (HV) power-line communication has become attractive. The main constraint of conventional HV power-line carrier (PLC) systems is their unfeasibility for being migrated to wideband channels, even with a high signal-to-noise ratio (SNR). In this scenario, none of the current linear/non-linear equalizers used in single carrier schemes achieve the complete compensation of the highly dispersive conditions, which limits their operation to 4 kHz channels. In this paper, a new PLC-channel model is introduced for transmission lines incorporating the effects of the coupling equipment. In addition, the use of the single-carrier frequency-division modulation (SC-FDM) is proposed as a solution to operate PLC systems in a wide bandwidth, achieving transmission speeds above those of the conventional PLC system. The results presented in this paper demonstrate the superior performance of the SC-FDM-PLC over conventional PLC systems, obtaining a higher transmission capacity in 10 to 30 times.

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Maximal Ratio Combining Detection in OFDM Systems with Virtual Carriers Over V2V Channels

2023 , Del-Puerto-Flores, J. Alberto , Francisco R. Castillo-Soria , J. Vázquez-Castillo , R. R. Palacio Cinco

This paper examines the performance of orthogonal frequency division multiplexing (OFDM) systems for vehicle-to-vehicle (V2V) communication channels. More specifically, a doubly selective channel under high intercarrier interference (ICI) is considered. Current solutions involve complex detection and/or reduced spectral efficiency receivers. This paper proposes the use of virtual carriers (VC) in an OFDM system with a low-complexity maximal ratio combining (MRC) detector to improve the bit error rate (BER) performance. The results show that VC provides diversity in received data, resulting in a ≥5 dB gain compared to previous OFDM systems with conventional linear/nonlinear detectors used as a reference. The detector presented in this paper has linear complexity, making it a suitable solution for real-time V2V communication systems.

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Performance of MRC Detection in OFDM System with Virtual Carriers over V2V Channels

2019 , Del-Puerto-Flores, J. Alberto , Joaquin Cortez , Gutierrez, Carlos A. , Del-Valle-Soto, Carolina , Velázquez, Ramiro , Valdivia, Leonardo

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