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Armando Garcia-Berumen
Electrical Engineering Department, Sonora Institute of Technology, Sonora 85130, Mexico

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Journal article
Published: 05 March 2020 in IEEE Access
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Localization is one of the main problems in Mobile Wireless Sensor Networks, since it provides the location of an event occurrence. This paper presents a performance evaluation of the localization algorithms: Multilateration Algorithm, Weighted Multilateration Algorithm and Probabilistic Multilateration Algorithm (PMA). In addition, we propose an Improved Probabilistic Multilateration Algorithm that decreases the localization error of the interest node by using an approach that computes iteratively the position of a node of interest until it reaches the solution that minimizes the localization error. The proposed approach regards the noisy environment by its impact on a correlation matrix that involves the variance of the separation distance between the node of interest and the respective reference nodes (RNs). Furthermore, we also introduce a constant parameter called damping factor; which enhances the convergence of the localization algorithm providing the solution that minimizes the localization error. In this study, we evaluate localization algorithms in a single-hop and multi-hop scenarios considering a distribution with solid geometry of the RNs and randomly distributed RNs in both scenarios. The results we obtained show that our proposed algorithm Improved PMA presents a better performance according to the Normalized Root Mean Squared Error varying the number of reference nodes and noise proportion.

ACS Style

Joaquin Mass-Sanchez; Cesar Vargas-Rosales; Erica Ruiz-Ibarra; Armando Garcia-Berumen; Adolfo Espinoza-Ruiz. Localization Based on Probabilistic Multilateration Approach for Mobile Wireless Sensor Networks. IEEE Access 2020, 8, 54994 -55011.

AMA Style

Joaquin Mass-Sanchez, Cesar Vargas-Rosales, Erica Ruiz-Ibarra, Armando Garcia-Berumen, Adolfo Espinoza-Ruiz. Localization Based on Probabilistic Multilateration Approach for Mobile Wireless Sensor Networks. IEEE Access. 2020; 8 (99):54994-55011.

Chicago/Turabian Style

Joaquin Mass-Sanchez; Cesar Vargas-Rosales; Erica Ruiz-Ibarra; Armando Garcia-Berumen; Adolfo Espinoza-Ruiz. 2020. "Localization Based on Probabilistic Multilateration Approach for Mobile Wireless Sensor Networks." IEEE Access 8, no. 99: 54994-55011.

Journal article
Published: 31 January 2020 in Applied Sciences
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Diabetes mellitus (DM) is a metabolic disorder characterized by blood glucose levels above normal limits. The impact of this disease on the population has increased in recent years. It is already a public health problem worldwide and one of the leading causes of death. Recently, several proposals have been developed for better and regular monitoring of glucose. However, theses proposals do not discard erroneous readings and they are not able to anticipate a critical condition. In this work, we propose an algorithm based on the double moving average supported by an IoT architecture to prevent possible complications in elderly patients. The algorithm uses historical readings to construct a series. Given a number of periods, it is possible to calculate averages of different subsets and trends for the next periods and, in this way, the prognosis is obtained. With the prognosis, it is possible to notify the doctor and relatives in advance about a possible critical condition in the patient. The aim of our work is to validate the architecture and prognosis algorithm used for elderly persons. Tests of the algorithm and the architecture were performed with different readings and it was shown that the system generated corresponding notifications before the glucose values were higher than those defined by the WHO (World Health Organization), thus avoiding unnecessary alarms.

ACS Style

Francisco Valenzuela; Armando García; Erica Ruiz.; Mabel Vázquez; Joaquín Cortez; Adolfo Espinoza. An IoT-Based Glucose Monitoring Algorithm to Prevent Diabetes Complications. Applied Sciences 2020, 10, 921 .

AMA Style

Francisco Valenzuela, Armando García, Erica Ruiz., Mabel Vázquez, Joaquín Cortez, Adolfo Espinoza. An IoT-Based Glucose Monitoring Algorithm to Prevent Diabetes Complications. Applied Sciences. 2020; 10 (3):921.

Chicago/Turabian Style

Francisco Valenzuela; Armando García; Erica Ruiz.; Mabel Vázquez; Joaquín Cortez; Adolfo Espinoza. 2020. "An IoT-Based Glucose Monitoring Algorithm to Prevent Diabetes Complications." Applied Sciences 10, no. 3: 921.

Journal article
Published: 09 December 2019 in Electronics
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This paper presents a proposal for an architecture in FPGA for the implementation of a low complexity near maximum likelihood (Near-ML) detection algorithm for a multiple input-multiple output (MIMO) quadrature spatial modulation (QSM) transmission system. The proposed low complexity detection algorithm is based on a tree search and a spherical detection strategy. Our proposal was verified in the context of a MIMO receiver. The effects of the finite length arithmetic and limited precision were evaluated in terms of their impact on the receiver bit error rate (BER). We defined the minimum fixed point word size required not to impact performance adversely for n T transmit antennas and n R receive antennas. The results showed that the proposal performed very near to optimal with the advantage of a meaningful reduction in the complexity of the receiver. The performance analysis of the proposed detector of the MIMO receiver under these conditions showed a strong robustness on the numerical precision, which allowed having a receiver performance very close to that obtained with floating point arithmetic in terms of BER; therefore, we believe this architecture can be an attractive candidate for its implementation in current communications standards.

ACS Style

Ismael Lopez; L. Pizano-Escalante; Joaquin Cortez; O. Longoria-Gandara; Armando Garcia. Fast Scalable Architecture of a Near-ML Detector for a MIMO-QSM Receiver. Electronics 2019, 8, 1509 .

AMA Style

Ismael Lopez, L. Pizano-Escalante, Joaquin Cortez, O. Longoria-Gandara, Armando Garcia. Fast Scalable Architecture of a Near-ML Detector for a MIMO-QSM Receiver. Electronics. 2019; 8 (12):1509.

Chicago/Turabian Style

Ismael Lopez; L. Pizano-Escalante; Joaquin Cortez; O. Longoria-Gandara; Armando Garcia. 2019. "Fast Scalable Architecture of a Near-ML Detector for a MIMO-QSM Receiver." Electronics 8, no. 12: 1509.