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A novel technique is shown to improve the isolation between radiators in antenna arrays. The proposed technique suppresses the surface-wave propagation and reduces substrate loss thereby enhancing the overall performance of the array. This is achieved without affecting the antenna’s footprint. The proposed approach is demonstrated on a four-element array for 5G MIMO applications. Each radiating element in the array is constituted from a 3 × 3 matrix of interconnected resonant elements. The technique involves (1) incorporating matching stubs within the resonant elements, (2) framing each of the four-radiating elements inside a dot-wall, and (3) defecting the ground plane with dielectric slots that are aligned under the dot-walls. Results show that with the proposed approach the impedance bandwidth of the array is increased by 58.82% and the improvement in the average isolation between antennas #1&2, #1&3, #1&4 are 8 dB, 14 dB, 16 dB, and 13 dB, respectively. Moreover, improvement in the antenna gain is 4.2% and the total radiation efficiency is 23.53%. These results confirm the efficacy of the technique. The agreement between the simulated and measured results is excellent. Furthermore, the manufacture of the antenna array using the proposed approach is relatively straightforward and cost effective.

Improvement of power amplifier’s performance is the desired topic in communication systems. There are many efforts are made to provide good input and output matching, high efficiency, sufficient power gain and appropriate output power. This paper presents a power amplifier with optimized input and output matching networks. In the proposed approach, a new structure of the Hidden Markov Model with 20 hidden states is used for modeling the power amplifier. The widths and lengths of the microstrip lines in the input and output matching networks are defined as the parameters that the Hidden Markov Model should optimize. For validating our algorithm, a power amplifier has been realized based on a 10W GaN HEMT with part number CG2H40010F from the Cree corporation. Measurement results have shown a PAE higher than 50%, a Gain of about 14 dB, and input and output return losses lower than -10 dB over the frequency range of 1.8–2.5 GHz. The proposed PA can be used in wireless applications such as radar systems.

Power amplifier design is an important topic in communication systems. Improving the efficiency of a power amplifier has long been a key interest to RF designers. In this paper, a 10 W GaN HEMT power amplifier is designed based on Hidden Markov Model optimized by Particle Swarm Optimization. The widths and lengths of the microstrip lines at the input and output of the matching networks in the proposed power amplifier are modelled using the Hidden Markov Model. For training the parameters of the Hidden Markov Model, the Particle Swarm Optimization algorithm is used. The power amplifier utilizes a 10 W GaN HEMT transistor (model CG2H40010F from Cree Corporation) and operates over a bandwidth of 2.5–3 GHz. At 2.98 GHz, the power amplifier achieves an output power of 39.3 dBm, a power‐added efficiency of 63.2%, and a gain of 15.3 dB. Across the entire bandwidth, it maintains output power above 38.18 dBm and gain above 14.2 dB, with power‐added efficiency exceeding 50% between 2.8 and 3 GHz. These results highlight the effectiveness of the HMM‐PSO approach in enhancing the performance of the proposed GaN HEMT power amplifier. Improvement of a 10 W GaN HEMT power amplifier based on hidden Markov model optimized by particle swarm optimization algorithm is done. The obtained results show that the hidden Markov model optimized by particle swarm optimization has a good ability to increase the performance of the proposed power amplifier.

Antennas in wireless sensor networks (WSNs) are characterized by the enhanced capacity of the network, longer range of transmission, better spatial reuse, and lower interference. In this paper, we propose a planar patch antenna for mobile communication applications operating at 1.8, 3.5, and 5.4 GHz. A planar microstrip patch antenna (MPA) consists of two F-shaped resonators that enable operations at 1.8 and 3.5 GHz while operation at 5.4 GHz is achieved when the patch is truncated from the middle. The proposed planar patch is printed on a low-cost FR-4 substrate that is 1.6 mm in thickness. The equivalent circuit model is also designed to validate the reflection coefficient of the proposed antenna with the S11 obtained from the circuit model. It contains three RLC (resistor–inductor–capacitor) circuits for generating three frequency bands for the proposed antenna. Thereby, we obtained a good agreement between simulation and measurement results. The proposed antenna has an elliptically shaped radiation pattern at 1.8 and 3.5 GHz, while the broadside directional pattern is obtained at the 5.4 GHz frequency band. At 1.8, 3.5, and 5.4 GHz, the simulated peak realized gains of 2.34, 5.2, and 1.42 dB are obtained and compared to the experimental peak realized gains of 2.22, 5.18, and 1.38 dB at same frequencies. The results indicate that the proposed planar patch antenna can be utilized for mobile applications such as digital communication systems (DCS), worldwide interoperability for microwave access (WiMAX), and wireless local area networks (WLAN).

In this paper, an automated impedance matching circuit is proposed to match the impedance of the transmit and receive resonators for optimum wireless power transfer (WPT). This is achieved using a 2D open-circuited spiral antenna with magnetic resonance coupling in the low-frequency ISM band at 13.56 MHz. The proposed WPT can be adopted for a wide range of commercial applications, from electric vehicles to consumer electronics, such as tablets and smartphones. The results confirm a power transfer efficiency between the transmit and receive resonant circuits of 92%, with this efficiency being sensitive to the degree of coupling between the coupled pair of resonators.

A low form-factor design of an eight-element antenna array is presented for 5G mm-wave MIMO applications. The design features modified circular patch radiators that achieve an impedance bandwidth of 2.6 GHz, covering frequencies from 37.7 to 40.3 GHz. The radiating elements are strategically arranged on opposite sides of a common substrate and interleaved to significantly reduce mutual coupling between adjacent elements. This innovative technique effectively minimizes coupling between the array’s radiators without the need of a decoupling structure. The MIMO antenna is fabricated on a low-loss Rogers-5880 substrate, with a thickness of 0.8 mm, a dielectric constant of 2.2, and a loss tangent of 0.0009, ensuring minimal signal loss and confirming the accuracy of simulation results. The inter-element isolation exceeds 25 dB, and the array provides a gain greater than 6 dBi, with a peak gain of 7.5 dBi at 39 GHz. This high gain enhances the antenna’s ability to mitigate atmospheric attenuation at higher frequencies, making it highly suitable for 5G mm-wave applications.

Using of ultra-wideband (UWB) technology in radio transceiver systems has increased in recent years due to high-speed data transmission, low power dissipation, low cost, and low complexity. In particular, distributed amplifier (DA) is a critical component of transceiver in UWB technology. However, designing an ultra-wideband DA with high performance becomes challenging. The DA design suffers from the tight trade-offs between the amplifier parameters such as gain, noise, linearity, input/output impedance matching, and power dissipation. In this paper, a new approach for multi-objective optimization of the DA is introduced. In the proposed approach, the meta-heuristic optimization techniques are applied over the entire bandwidth of the UWB, while the most recent optimization approaches for amplifiers are performed at the center frequency and they can’t achieve the proper design specifications for wideband amplifiers. The simultaneous optimization of power gain ( S 21 ), noise figure (NF), input and output return loss ( S 11 and S 22 ) are conducted over the wide bandwidth using three multi-objective optimization algorithms including Multi-Objective Inclined Planes System Optimization (MOIPO), Non-dominated Sorting Genetic Algorithm II (NSGA-II), and Multi-Objective Particle Swarm Optimization (MOPSO). The obtained results demonstrate the tapered matrix DA optimized by MOIPO exhibits better performance than others. The circuit simulations are performed in 0.18 µm TSMC RF-CMOS technology. Simulation results show that the optimized tapered matrix DA by MOIPO, compared to NSGA-II and MOPSO, exhibits a good performance over the frequency band of 0.1–28 GHz with maximum S 21 of 12.9 dB, NF less than 5.9 dB, S 11 and S 22 below than  − 10 dB over the whole frequency band. The DC power dissipation is 25 mW from a 1.5 V supply.

Introduction:Diabetes is a common chronic metabolic disease that poses a significant global healthcare challenge. The International Diabetes Federation projects reported that 693 million people will experience diabetes by 2045. Given the serious complications and mortality associated with diabetes, it is essential to educate patients and promote self-care pratices. Mobile health technologies (mHealth) have become important tools in managing diabetes and supporting self-care. This study aimed to review how mHealth can assist diabetic patients in managing their self-care more effectively. Search Strategy:We utilized PICO criteria to search various databases, including PubMed, Web of Science, Medline, Scopus, SID, and Google Scholar using the keywords \"Mobile Health,\" \"Self-Care,\" and \"Diabetes\" from 2015 to 2023. Two operators independently conducted searches using Boolean operators. After screening and conducting a quality appraisal, 128 articles were identified, of which 11 met the inclusion criteria. Results: The results suggested that integrating AI-based mHealths into diabetes management programs has broadened their functionalities beyond monitoring blood glucose levels and HbA1c. These advanced software solutions have shown potential in promoting physical activity, reducing sedentary behavior, supporting short-term weight loss, assisting with insulin dose adjustments, educating users about diabetes complications, and facilitating data sharing with healthcare professionals for remote monitoring and care. One significant benefit of utilizing mHealths is their accessibility, with many programs being offered at no cost or requiring only a fixed or minimal subscription fee. Studies have indicated high adoption rates of mobile health interventions in underserved areas with limited access to healthcare providers and services. However, challenges and limitations linked to the use of mHealths have been recognized. These include the need for extensive data input, concerns about the security and privacy of personal information, potential erosion of patient trust, as well as issues regarding the accuracy and reliability of health information obtained through these platforms. Conclusion and Discussion: As artificial intelligence (AI) continues to gain traction in healthcare, it is essential to educate providers on the operation of these tools. Emphasizing distance education for technological products can significantly reduce hospital costs. Expanding mobile health initiatives for primary prevention can help mitigate complications associated with diabetes. Although the use of AI remains limited, aligning research policies with technological advancements and fostering interdisciplinary health support is crucial.