This paper introduces a new method for designing power amplifiers (PAs) using a flexible, automatic approach. It employs a Gaussian process-assisted fast non-dominated sorting genetic algorithm (GP-NSGA-II) for both circuit synthesis and layout optimization. Traditional genetic algorithms are computationally intensive and have poor convergence, making them difficult to use with three-dimensional full-wave simulators. To address these issues, the authors incorporate Gaussian process regression from Bayesian optimization into NSGA-II, improving convergence and computational efficiency. The method integrates layout simulation and optimization, enabling automatic PA design with direct layout optimization. To demonstrate the method’s effectiveness, the authors design a wide-band PA and a tri-band PA using a 10-W gallium-nitride (GaN) high electron mobility transistor (HEMT). The tests show that the prototypes perform well: the wide-band PA has a power-added efficiency (PAE) of over 61% and an output power greater than 41.5 dBm in the 2-3 GHz band, while the tri-band PA achieves PAE values of over 59%, 55%, and 57% in the 0.7-1.1 GHz, 2.3-2.5 GHz, and 3.4-3.5 GHz bands, respectively, with output powers exceeding 41.2 dBm, 40.6 dBm, and 40.6 dBm.

In this article, a novel frequency-domain behavioral modeling approach for gallium-nitride (GaN) devices is presented. The proposed technique is based on using the canonical section-wise piecewise linear (CSWPL) model framework to interpolate the dc input and output bias voltages by a 2-D polynomial function. The basic theory associated with the developed model is described in detail and experimentally verified. The model is implemented in a commercial software and, then, validated through both dc and radio frequency (RF) tests with measured load-pull data from 6-W GaN devices. The achieved results demonstrate an excellent prediction capability, thereby proving the accuracy of the developed modeling methodology. Compared with the standard CSWPL model, the proposed model is able to predict the transistor behavior at different bias voltages with one single set of parameters, which greatly reduces the model complexity as well as the required extraction time. Compared with existing bias included models, the proposed solution shows accurate predictions over a wide range of input power levels and bias conditions, simultaneously. Additionally, the proposed model is utilized for a broadband power amplifier (PA) design for a further validation. The measurements carried out on the realized PA are compared with the simulations based on the proposed model. The comparison is performed at four different bias conditions. The agreement between measurements and simulations confirms the extracted model’s validity.

The article proposes a modified series compensation (MSC) outphasing power amplifier (OPA) that maximizes saturation output power and extends power back-off range. The proposed OPA enables achieving output power back-off (OBO) compensation without affecting the saturation matching. Then, the circuit structure is simplified by introducing a post-matching circuit to integrate the combiner and the reactive compensation network (RCN). Moreover, a simplified dual-impedance matching network (DIMN) is placed between each transistor and the output combiner, leading to increased OBO range with improved efficiency. This technique not only takes into consideration the influence of parasitic parameters but also match the required impedance at both saturation and OBO points, simultaneously. The above design idea is successfully verified by using the gallium nitride (GaN) high-electron-mobility transistor (HEMT) to develop an OPA circuit operating at 2.6 GHz, providing 45.2 dBm of peak output power. At the 12-dB output back-off point, the drain efficiency reaches 61.5%. In addition, the prototype achieves values of the adjacent channel leakage ratio (ACLR) equal to -48.17 dBc and 47.74 dBc for LTE modulated signal with 8 dB PAPR value and for 5G NR signal with 11.7 dB PAPR value, respectively.

In this work, the design of a load-modulated balanced power amplifier (LMBA), which is composed of a pair of classical balanced power amplifier (BA) and a signal control power amplifier (CA), based on using the X-parameter model is presented for the first time. A 10-W gallium nitride (GaN) packaged transistor is used for the power amplifier (PA) design. The extracted X-parameter model of the device under test (DUT) can accurately predict the nonlinear behavioral of the device, including both fundamental and harmonic characteristics, and determine the region of the Smith chart that leads to the optimal output power and drain efficiency (DE), with which the BA and CA are designed. In order to facilitate the application of the X-parameter for LMBA design, the X-parameter model of the classical BA pair is further extracted. Finally, an LMBA is fabricated and tested to verify the validity of the proposed design methodology. The measurements performed on the developed prototype show a saturation output power of up to 43.2 dBm in the frequency range of 1.3–1.6 GHz, with a saturation DE over 73% and an output power back-off (OBO) efficiency over 51% when it has more than 9-dB OBO. A single-carrier 20-MHz long-term evolution (LTE) signal is used to test the designed PA, and performance of the amplifier both with and without linearization are given.

Telehealth systems and applications are extensively investigated nowadays to enhance the quality-of-care and, in particular, to detect emergency situations and to monitor the well-being of elderly people, allowing them to stay at home independently as long as possible. In this paper, an embedded telehealth system for continuous, automatic, and remote monitoring of real-time fall emergencies is presented and discussed. The system, consisting of a radar sensor and base station, represents a cost-effective and efficient healthcare solution. The implementation of the fall detection data processing technique, based on the least-square support vector machines, through a digital signal processor and the management of the communication between radar sensor and base station are detailed. Experimental tests, for a total of 65 mimicked fall incidents, recorded with 16 human subjects (14 men and two women) that have been monitored for 320 min, have been used to validate the proposed system under real circumstances. The subjects' weight is between 55 and 90 kg with heights between 1.65 and 1.82 m, while their age is between 25 and 39 years. The experimental results have shown a sensitivity to detect the fall events in real time of 100% without reporting false positives. The tests have been performed in an area where the radar's operation was not limited by practical situations, namely, signal power, coverage of the antennas, and presence of obstacles between the subject and the antennas.