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The objective of this article is to analyze the behavior of channels in mobile radio transmission chains and propose a solution for reducing propagation attenuation and ensuring Quality of Service (QoS) in telecommunications. As network coverage and throughput demands continue to grow, a thorough characterization of channels is essential. The primary contribution of this work is to investigate the different phases of the digital transmission chain jointly to achieve optimal reliability and QoS. Spatial and temporal representations must be considered at the same level when characterizing and modeling MIMO system channels. Accurate and realistic modeling can be achieved through transmission channel characterization in the spatial domain, which is critical in a MIMO context to improve throughput and performance compared to conventional systems. The article explores the behavior of information carriers in the propagation environment and the impact of fading, diversity, multiplexing, and multipath phenomena.

This paper addresses the minimization of energy consumption in device-to-device (D2D) communications in the healthcare logistics domain. Given the vital importance of actions in this field for patients' lives, it is crucial to reduce the energy consumed by the devices used. This study aims to propose a fuzzy approach to predict the energy consumption induced by different protocols in D2D communications to minimize the energy consumption of healthcare logistics devices. A fuzzy supervisor is developed to evaluate and forecast the energy consumption of the devices in D2D communications. This approach allows for obtaining more accurate predictions and a better understanding of how device energy consumption can be reduced. Numerical simulations were conducted to validate the proposed method. The results show the efficiency and sustainability of D2D communication systems and a significant reduction in energy consumption when a classical method is applied. [ABSTRACT FROM AUTHOR]

This paper seeks to improve mobile communications performance by integrating artificial intelligence (AI) techniques. The study is centered on device-to-device (D2D) communication, which has emerged as a significant aspect in the 5th generation of mobile networks (5G) and is expected to be extended to the 6th generation (6G). Based on the fuzzy system, the proposed solution tackles the critical issue of energy harvesting in D2D communication. The solution presents a support system that selects the best relay for the transmitter-receiver communication to minimize energy consumption and maximize the network's lifetime. Minimizing energy consumption optimizes the network's lifetime, thus providing a reliable and efficient communication system. The approach taken in this study offers a novel perspective in addressing the energy harvesting challenge in D2D communication. It is expected to have a significant impact on the performance of mobile communications. [ABSTRACT FROM AUTHOR]

This paper addresses the minimization of energy consumption in device-to-device (D2D) communications in the healthcare logistics domain. Given the vital importance of actions in this field for patients' lives, it is crucial to reduce the energy consumed by the devices used. This study aims to propose a fuzzy approach to predict the energy consumption induced by different protocols in D2D communications to minimize the energy consumption of healthcare logistics devices. A fuzzy supervisor is developed to evaluate and forecast the energy consumption of the devices in D2D communications. This approach allows for obtaining more accurate predictions and a better understanding of how device energy consumption can be reduced. Numerical simulations were conducted to validate the proposed method. The results show the efficiency and sustainability of D2D communication systems and a significant reduction in energy consumption when a classical method is applied. [ABSTRACT FROM AUTHOR]