Multi-source in DF cooperative networks with the PSR protocol based full-duplex energy harvesting over a Rayleigh fading channel: performance analysis

Due to the tremendous energy consumption growth with ever-increasing connected devices, alternative wireless information and power transfer techniques are important not only for theoretical research but also for saving operational costs and for a sustainable growth of wireless communications. In this paper, we investigate the multi-source in decode-and-forward cooperative networks with the power splitting protocol based full-duplex energy harvesting relaying network over a Rayleigh fading channel. In this system model, the multi-source and the destination communicate with each other by both the direct link and an intermediate helping relay. First, we investigate source selection for the best system performance. Then, the closed-form expression of the outage probability and the symbol error ratio are derived. Finally, the Monte Carlo simulation is used for validating the analytical expressions in connection with all main possible system parameters. The research results show that the analytical and simulation results matched well with each other.Web of Science68327526

Power beacon-assisted energy harvesting in a half-duplex communication network under co-channel interference over a Rayleigh fading environment: Energy efficiency and outage probability analysis

In this time, energy efficiency (EE), measured in bits per Watt, has been considered as an important emerging metric in energy-constrained wireless communication networks because of their energy shortage. In this paper, we investigate power beacon assisted (PB) energy harvesting (EH) in half-duplex (HD) communication network under co-channel Interferer over Rayleigh fading environment. In this work, we investigate the model system with the time switching (TS) protocol. Firstly, the exact and asymptotic form expressions of the outage probability (OP) are analyzed and derived. Then the system EE is investigated and the influence of the primary system parameters on the system performance. Finally, we verify the correctness of the analytical expressions using Monte Carlo simulation. Finally, we can state that the simulation and analytical results are the same.Web of Science1213art. no. 257

Consideration of Data Security and Privacy Using Machine Learning Techniques

As artificial intelligence becomes more and more prevalent, machine learning algorithms are being used in a wider range of domains. Big data and processing power, which are typically gathered via crowdsourcing and acquired online, are essential for the effectiveness of machine learning. Sensitive and private data, such as ID numbers, personal mobile phone numbers, and medical records, are frequently included in the data acquired for machine learning training. A significant issue is how to effectively and cheaply protect sensitive private data. With this type of issue in mind, this article first discusses the privacy dilemma in machine learning and how it might be exploited before summarizing the features and techniques for protecting privacy in machine learning algorithms. Next, the combination of a network of convolutional neural networks and a different secure privacy approach is suggested to improve the accuracy of classification of the various algorithms that employ noise to safeguard privacy. This approach can acquire each layer's privacy budget of a neural network and completely incorporates the properties of Gaussian distribution and difference. Lastly, the Gaussian noise scale is set, and the sensitive information in the data is preserved by using the gradient value of a stochastic gradient descent technique. The experimental results showed that a balance of better accuracy of 99.05% between the accessibility and privacy protection of the training data set could be achieved by modifying the depth differential privacy model's parameters depending on variations in private information in the data

Hybrid TSR-PSR in nonlinear EH half duplex network: system performance analysis

Nowadays, harvesting energy (EH) from green environmental sources and converting this energy into the electrical energy used in purpose to supply the communication network devices is considered the main research direction. In this research, we investigate the hybrid TSR-PSR Nonlinear Energy Harvesting (EH) Half-duplex (HD) Relaying network in terms of the Success Probability (SP). For this purpose, we derive the integral-form of the system SP. In addition, we use the Monte Carlo simulation for verifying the correctness of the analytical expression. We can see in the research results that all the simulation and analytical values are the same in connection with all primary system parameters

Hybrid decode-amplify and forward protocol of FD EH relaying network: outage probability analysis

Nowadays, many research papers focus on the WPCN problem and how to improve its efficiency. In this research, we propose and investigate Hybrid Decode-Amplify and Forward Protocol (HDAF) of the Full-Duplex (FD) Energy Harvesting (EH) Relaying Network with the Time Switching (TS) protocol. In the beginning stage, we present the HDAF mode, which can be work like a Decode-and-Amplify (DF) or Amplify-and-Forward (AF) modes based on the best of its performance in the FD EH relaying network. Furthermore, the closed-form expression of the outage probability (OT) is analyzed and derived in connection with the primary system parameters. Besides, the comparison of the system performance in the AF, DF, and HDAF is proposed and investigated. Finally, all the results are convinced by the Monte Carlo simulation for all cases

Space Vector Modulation for Induction Motor on ARM-based Microcontroller

This article presents the review and the implementation of Space Vector Modulation (SVM) in a low-cost microcontroller-based motor drive system. The output three-phase voltages are obtained from a reference voltage vector in the polar coordinate system using the PWM technique; these voltages can reach up to the level of the DC voltage source (experimentally 16 VDC or practically 237 V with an inverter module). The article also provides a detailed presentation of the pre-calculations and the computations required for SVM on a STM32F1 ARM-based microcontroller. For achieving high frequency precision, a novel method for vector rotation based on the fixed-point arithmetic is proposed and tested. The experimental results highlight that the presented implementation including vector rotation can reach 1 Hz without significant error and it requires only 0.684 MIPS at 5 kHz computation rate for a 72 MIPS 32-bit microcontroller with single-cycle multiplication. The maximum instantaneous output phase-to-phase voltages could be as high as the DC voltage source