We address the throughput maximization problem for downlink transmission in DF-relay-assisted cognitive radio networks (CRNs) based on Simultaneous wireless information and power transfer (SWIPT) capability. In this envisioned network, multiple-input multiple-output (MIMO) relay and secondary user (SU) equipment are designed to handle both radio frequency (RF) signal energy harvesting and SWIPT functional tasks. Additionally, the cognitive base station (CBS) communicates with the SU only via the MIMO relay. Based on the considered network model, several combined constraints of the main problem complicate the solution. Therefore, in this paper, we apply heuristic guidelines within the convex optimization framework to handle this complexity. First, consider the problem of maximizing throughput on both sides of the relay separately. Second, each side progresses to solve the complex problem optimally by adopting strategies for solving sub-problems. Finally, these optimal solutions are synthesized by proposing a heuristic iterative power allocation algorithm that satisfies the combinatorial constraints with short convergence times. The performance of the optimal proposed algorithm (OPA) is evaluated against benchmark algorithms via numerical results on optimality, convergence time, constraints’ compliance, and imperfect channel state information (CSI) on the CBS-PU link.

wireless networks suffer from battery discharging specially in cooperative communications, where multiple energy constrained relays are used. To overcome this problem, energy harvesting from RF signals is used to charge the node battery. These intermediate nodes have the ability to harvest energy from the source signal and use the harvested energy to transmit information to the destination. In fact, the node tries to harvest energy and then transmit the data to destination. Division of energy harvesting and data transmission periods can be done in two different protocols, namely time switching based relaying protocol (TSR) and power splitting based relaying protocol (PSR). These two protocols can also be applied in delay-limited and delay-tolerant transmission systems. The previous works have assumed a single relay for energy harvesting; However, in this paper, the proposed method is concentrated on improving the outage probability and throughput using multiple antennas in each relay node instead of using single antenna. Also the optimum location of multiple relays is discussed and its effect on throughput of the system is mainly considered. According to our simulation results, when multi-antenna relays are used, ability of energy harvesting is increased and thus system performance will be improved to a great extent. MRC selection relay scheme is used when the destination chooses a group of relays and antennas satisfying the required SNR.

The wireless body area network (WBAN) is one of the applications of the Internet of things (IoT) for healthcare, which monitors human physiological parameters. In this paper, a two-objective optimization problem is designed to maximize the sum-throughput and wireless transferred energy Simultaneously. The designed one-tier network includes body surface sensors, an implantable sensor, and one coordinator. All of these sensors can harvest energy from the body and radio frequency (RF) signals. A temperature constraint is considered for the implanted sensor due to the sensitivity of internal tissues. Each sensor transmits physiological data to the coordinator in the uplink according to the scheduled time slots obtained by solving the optimization problem. At the beginning of each frame in the downlink, the coordinator transmits a pilot signal to transfer wireless energy and for channel estimation at the sensors. We have used a Recurrent Neural Network (RNN) architecture to predict one time step ahead of the channel. Then by interpolation, the channel gains of all time slots of a frame are estimated and the time scheduling of the sensor access to the channel is improved. The simulation results show that the objective function and time scheduling are improved by the proposed algorithms.

Introduction: The hospital information system is an integrated and comprehensive information system designed to manage the administrative, financial and clinical aspects of the hospital. This system performs the process of processing patients' information using the used subsystems. The main goal of this system is to improve the quality of patient care in the best possible way using wireless and web-based technologies. The higher the hospital information systems are in terms of the quality of the facilities, the better they can provide services to the patients. Considering these cases, it is obvious that the first step in increasing the quality of treatment facilities is to know these facilities and get to know their advantages and disadvantages. This study aimed to identify and introduce the role of wireless technologies on hospital information systems. Methods: This study was conducted in 2021, in the form of a narrative and unstructured review. In this study, ISI, PubMed, Scopus, Google Scholar, MagIran and SID databases were searched. Results: In this study, some wireless technologies such as barcodes, touch screens, browsers, document imaging systems, speech recognition/transformation technologies, mobile cards, tablet and pen, and electronic forms were identified. Conclusion: This study showed the use of wireless technologies can improve the quality of care and expedite the treatment process. In addition to the introduction, some advantages and disadvantages of these technologies will be presented so that healthcare providers and managers can provide appropriate conditions and facilities for their medical centers.

In this paper, we address the challenges of energy and throughput management in a wireless Body Area Network (WBAN) with a focus on a heart rate sensor. Our approach utilizes the sleep and wake-up method to minimize sensor energy consumption while harnessing Radio Frequency (RF) waves and human activities (running, walking, and relaxing) as Energy Harvesting (EH) sources to supplement battery power. Bluetooth Low Energy 5 (BLE5) technology is employed for wireless information and energy transfer. Our goal is to strike a balance between throughput and battery residual energy. The advantages of using 𝒬-learning for action selection in comparison to Random Action (RA) selection are demonstrated through simulations. The results reveal that the reward function in 𝒬-learning, incorporating a balancing parameter, effectively achieves a compromise between throughput and battery residual energy. Additionally, our 𝒬-learning method improves system throughput by 43% compared to RA selection. In addition, we compare the performance of the 𝒬-learning and State- Action- Reward- State- Action (SARSA) algorithms using the same reward function to evaluate their respective abilities in managing system throughput and battery residual energy. These findings have significant implications for developing energy-efficient WBANs, enabling prolonged operation and reliable data transmission.

This paper investigates beamforming design for Simultaneous transmission and reflection reconfigurable intelligent surface (Star RIS) assisted secure wireless communication with three operating protocols (energy splitting (ES), mode switching (MS), and time switching (TS)) with the assumption of the availability of imperfect CSI of two eavesdroppers at BS. We maximize the sum rate of legitimate users by designing both active and passive beamforming at BS and RIS, respectively, under the constraint of the limited maximum tolerable rate of eavesdroppers and a limited transmission power budget. The non-convex problem is solved by alternating optimization (AO) for active and passive beamforming optimization, and also successive convex approximation (SCA), and the penalty concave-convex procedure (PCCP). According to the simulation results, Star-RIS outperforms conventional RIS, ES mode outperforms MS and TS, and the performance is higher with lower channel estimation error.