RF Power Amplifier Research Articles

The DC Performance and RF Characteristics of GaN-Based HEMTs Improvement Using Graded AlGaN Back Barrier and Fe/C Co-Doped Buffer

In this article, the impact of the graded AlGaN back barrier and Fe\C co-doping buffer structure on the AlGaN <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$/$ </tex-math></inline-formula> GaN high electron mobility transistors (HEMTs) is proposed and systematically investigated. Due to effective suppression of Fe tail in unintentionally doped GaN (uid-GaN) layer by the insertion of the thick graded AlGaN back barrier layer, a large maximum drain current density and a transconductance peak are achieved. Meanwhile, the breakdown voltage is significantly improved by the use of Fe\C co-doping GaN buffer design. More importantly, it is revealed that the graded-AlGaN design can reduce the range and intensity of the electrical potential distribution in uid-GaN layer and then effectively suppress the acceptor-induced trapping\detrapping effect under high drain voltage. The RF small-signal performance of Fe-doped GaN (GaN:Fe)\C co-doping buffer HEMT exhibits significant improvement. In addition, load-pull measurement at 8 GHz revealed that a saturation power increases from 38.04 to 41.07 dB, a power gain increases from 9.06 to 10.58 dB, and an associate power-added-efficiency (PAE) increased from 40.27% to 50.18%. Our proposed GaN-based epitaxial structure can not only suppress the gate lag by reduce AlGaN surface electric field, but it can also suppress the drain lag by reduce the amplitude and range of potential distribution. It indicates that our proposed device has great potential for future high-voltage RF power amplifier application.

Segmented Statistical Error-Based Adaptive Method for Linearization of Power Amplifiers

In this letter, we present an adaptive method for linearizing radio frequency (RF) power amplifier (PA). The input and output error is segmented in light of the signal magnitude to improve the convergence speed of the linearizer’s parameter optimization. The feedback bandwidth and the sampling rate of the feedback loop are only 1/8 of the input signal with the proposed method. Experimental results show that the convergence speed of the proposed method is eight times faster than that of the conventional method, and the adjacent channel power ratio (ACPR) is improved from −35.18 to −46.91 dB.

Digital Predistortion of RF Power Amplifiers Robust to a Wide Temperature Range and Varying Peak-to-Average Ratio Signals

In this work, a digital predistortion (DPD) model for the linearization of RF power amplifiers (PAs) is presented. The model provides a linearized gain (DPD &#x002B; PA) independent of the instantaneous transistor channel temperature within a predefined temperature window. Channel temperature variations due to varying ambient temperatures or changes in the signal probability density function (PDF) cause long-term memory effects, which results in dispersed (dynamic) AM/AM and AM/PM characteristics. The presented model is used to compensate for the memory effects due to self-heating and external temperature changes by estimating the transistor channel temperature through a linear single-pole Foster thermal network. The DPD model uses a first-order Taylor approximation to cancel out temperature-based nonlinearities. Gaussian pulses are used to extract the PA intrapulse gain at different temperatures without being affected by the signal PDF, thus allowing temperature- and signal-independent PA characterization. The model is validated from <inline-formula> <tex-math notation="LaTeX">$20~^\circ \text{C}$ </tex-math></inline-formula> to <inline-formula> <tex-math notation="LaTeX">$80~^\circ \text{C}$ </tex-math></inline-formula> and by considering a class-B 3.75-GHz 10-W gallium nitride (GaN)-on-SiC PA. The DPD performance is evaluated by considering the normalized root-mean-squared error (NRMSE), the output spectra, and adjacent channel power ratio (ACPR) with and without DPD for multiple signals bandwidths and peak-to-average power ratio (PAPR) and finally compared with other approaches.

F-OFDM in a novel form for analyzing 5G networks

The need for internet of things (IoT) and machine-to-machine communication (MTC) has been growing rapidly all across the world. To meet the client's needs, many literature reviews were undertaken in several countries. Orthogonal frequency division multiplexing (OFDM), Universal Filtered Multi-Carrier (UFMC), filter-bank multicarrier offset construction amplitude modulation (FBMC-OQAM), generalized frequency division multiplexing (GFDM), and others are candidates for LTE, LTE advance, and 5G, according to the majority of the researchers. However, because it is sensitive to propagation and noise, such as amplitude, with a huge dynamic range, it requires RF power amplifiers with a high peak to average power quantitative relationship; consequently, it is not recommended for LTE, LTE advance, or 5G. As a result, the same concerns were addressed by introducing innovative type filtered orthogonal frequency division multiplexing (F- OFDM), which was the subject of this study. In addition, F-OFDM mathematical models were constructed and simulated in the MATLAB software environment. To validate the proposed innovative F-OFDM, OFDM was compared. For innovative F-OFDM, the simulated result was 0.00083333 bit error rate (BER). Furthermore, the bit error rate (BER) of F-OFDM over OFDM was 89.4 percent, and the peak to average power ratio was 17 percent. The simulation results unmistakably show that the suggested innovative F-OFDM is the greatest fit for LTE, LTE advanced, and 5G contenders.

On the Use of Class D Switching-Mode Power Amplifiers in Visible Light Communication Transmitters.

Visible Light Communication (VLC) is a wireless communication technology that uses visible light to transmit information. The most extended implementation of a VLC transmitter employs a DC-DC power converter that biases the High-Brightness LEDs (HB-LEDs), and a Linear Power Amplifier (LPA) that reproduces the communication signal. Unfortunately, the power efficiency of LPAs is very low, thus reducing the overall system efficiency and requiring huge cooling systems to extract the heat. In this work, the use of Class D Switching-Mode Power Amplifiers (SMPAs) is explored in order to overcome that limitation. It is important to note that this SMPA is widely used for different applications, such as audio and RF power amplifiers. Therefore, there are a lot of versions of a Class D SMPA depending on the topology used for the implementation and the modulation strategy used to control the switches. Hence, this work aims to identify, adapt and explain in detail the best approach for implementing a Class D SMPA for VLC. In order to validate the proposed idea, a power-efficient VLC transmitter intended for short-range and low-speed applications was built and evaluated.

Broadband performance assessment of a microwave power transistor employing the real frequency technique

AbstractGeneration of proper source/load‐pull impedances for a selected active device is essential to design an RF power amplifier for optimum gain and power added efficiency. As they are obtained, these impedances may not be realizable network functions over the desired frequency band to yield the input and the output matching networks for the amplifier. Therefore, in this paper, first, we introduce a new method to test if a given impedance is realizable. Then, a novel “real frequency line‐segment technique” based numerical procedure is introduced to assess the gain‐bandwidth limitations of the given source and load impedances, which in turn results in the ultimate RF power‐intake and power‐delivery capacity of the amplifier. During the numerical performance assessments process, a robust tool called “virtual gain optimization” is presented. Finally, a new definition called “power performance product” is introduced to measure the quality of an active device. Examples are presented to test the realizability of the given source‐/load‐pull data and to assess the gain‐bandwidth limitations of the given source/load‐pull impedances for a 45 W‐GaN power transistor, namely, “Wolfspeed CG2H40045” over 0.8–3.8 GHz bandwidth.

High power solid state RF amplifiers for SARAF Phase II Linac

Compact narrow-band high power Solid State Power Amplifiers (SSPA) capable of delivering up to 10/20 kW CW RF power at 176 MHz were developed at SNRC for SARAF Linac Phase II. The 10/20 kW amplifiers were built by combining RF power from two/four 5 kW high power amplifiers using 3 dB 0–90° High Power Quad Hybrid Couplers (HPQHC). In their turn, the 5 kW amplifiers were combined from eight LDMOS water cooled amplifiers modules equipped with internal circulators and RF loads. The total power gain of the 10/20 kW amplifiers (including the driver stages) is 70/73 dB. These amplifiers have the ability to withstand with continuous wave full reflection power (VSWR at nominal rating > 100:1) for a long time without the use of an external circulator. Unconditional stability for CW and pulsed operation, reliability, linearity, high efficiency, simple design and compact size are the main features we sought for this amplifier. The underlying design principles, indigenous development and test results are presented.

Gallium nitride phononic integrated circuits platform for GHz frequency acoustic wave devices

Strong transverse confinement of high-frequency sound and low-loss routing in on-chip waveguides will bring new degrees of freedom to manipulate GHz frequency acoustic waves, analogous to the change brought forth by silicon integrated photonics to the routing and manipulation of light on a chip. Here, we demonstrate that high frequency (&amp;gt;3 GHz) sound can be efficiently guided in μm-scale gallium nitride (GaN) waveguides and ring resonators by exploiting the strong velocity contrast available in the GaN on silicon carbide (SiC) platform. Given the established use of GaN devices in RF amplifiers, our work opens up the possibility of building RF devices with tight integration between the active and passive components on the same die.

Intersubband transitions in nonpolar and semipolar III-nitrides: Materials, devices, and applications

In the last two decades, the third-generation wide bandgap semiconductor III-nitrides have revolutionized a myriad of electronic and photonic devices and applications, including power electronics, extreme-environment electronics, RF amplifiers, and optoelectronics such as light-emitting diodes and laser diodes. Recently, III-nitride heterostructures (e.g., AlGaN/GaN) based intersubband transition (ISBT) has garnered considerable research interest for infrared (IR), terahertz (THz), and ultrafast optoelectronics (e.g., photodetectors and quantum cascade lasers) due to its large conduction band offset, large optical phonon energy, and promising room-temperature operation. This paper presents a comprehensive review on the recent progress and challenges of III-nitrides based ISBT from the perspectives of materials, structures, devices, and applications, with a focus on nonpolar and semipolar III-nitrides. Various device structures have been demonstrated for III-nitrides based ISBT, including quantum wells, dots, and wires, among which AlGaN/GaN quantum wells are the most widely used. The effects of device parameters, crystal orientations, and doping on the ISBT properties of AlGaN/GaN quantum wells are discussed. Although the room-temperature operation is still elusive, theoretical and experimental studies show that nonpolar and semipolar III-nitrides based ISBT exhibits tunable ISBT wavelength from far-IR to THz spectral range with higher efficiency compared with polar c-plane ISBT. This review can serve as a gateway to and an important reference for the recent progress and challenges of III-nitrides based ISBT and its potential applications in sensing, communication, ultrafast optoelectronics, and integrated photonics.

High-Performance RF Power Amplifier Module Using Optimum Chip-Level Packaging Structure

This article presents a high-performance radio frequency (RF) power amplifier (PA) module for which an optimum chip-level packaging structure is proposed to reduce the operating temperature of the RF PA monolithic microwave integrated circuit (MMIC). Because the output power ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">P</i> <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">out</sub> ) and the efficiency of an RF PA module are strongly affected by the thermal characteristics of the PA MMIC, various types of heat spreader materials and thermal interface materials have been examined to implement the PA chip-level packaging structure, and the optimum combination is proposed for a performance enhancement of the PA module in this article. In addition, the optimum form-factor of the heat spreader was suggested based on a thermal simulation. To verify the proposed PA chip-level packaging structure, a 10 W 6–18 GHz RF PA MMIC using a commercial 0.25- <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">μ</i> m gallium nitride high electron mobility transistor process was designed and implemented for radar applications. The operating temperature of the PA MMIC on the proposed chip-level packaging structure shows a dramatic reduction of 24.8 °C, and accordingly, the average <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">P</i> <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">out</sub> and average power-added efficiency are enhanced by up to 9.2% and 2.8%, respectively, when compared with a PA module using the conventional chip-level packaging structure.

Digital Predistortion of RF Power Amplifiers With Phase-Gated Recurrent Neural Networks

In this article, we present a novel recurrent neural network (RNN)-based behavioral model to linearize radio frequency (RF) power amplifiers (PAs) under wideband excitations. Based on the lightweight Just Another NETwork (JANET) unit, we propose a new neural network structure that is especially suitable for modeling the complex behavior of the RF PAs. A novel signal preprocessing technique is developed to model the complex interaction between amplitude information and phase information in the digital predistortion (DPD) model. By integrating the preprocessing stage into the RNN model, the complete phase-gated JANET (PG-JANET) model can provide enhanced linearization performance with lower complexity compared to the existing models.

Design of a 5 T Non-magnetic Magnetic Resonance Radio Frequency Power Amplifier

Design of a 5 T Non-magnetic Magnetic Resonance Radio Frequency Power Amplifier

Fabrication and Characterization of Epitaxial Graphene Field Effect Transistor Devices Based on a Monolithic Bottom Gate

Current electronics technology increasingly demands higher integration, flexibility, higher efficiency, and performance aspects such as compatibility with higher temperature operation of the semiconductor devices, which may find limitations when silicon is used. The superior intrinsic properties of SiC, eventually combined with the ability of growing monolithically epitaxial, high quality graphene on a SiC wafer (1), makes it a reliable alternative for some electronic applications, such as field effect transistors (FET), radio frequency (RF) power amplifiers, integrated circuits (IC), or sensors. In this work, we describe the fabrication and preliminary electrical characterizations of epitaxial graphene (EG) on a SiC substrate FET devices based on an alternative back gate architecture. We propose a new approach in which the FET device is built on a 4◦ off-axis cut, N+ doped 4H-SiC substrate (the back gate) with, on top of, it a 1μm semi-insulating homoepitaxial layer of SiC compensated with vanadium (the dielectric layer). EG will be used as FET conduction channel. Using this V-compensated dielectric layer is aimed to minimize effects on the FET characteristics such as from defects in the SiC crystal, especially below the FET active areas, which would have occurred when using ion implantation to create a buried gate. The EG film was grown by the high temperature Si sublimation method under an Ar ambient. Raman spectroscopy, Atomic Force Microscopy (AFM) and Scanning Electron Microscopy (SEM) were applied in the structural characterization of epigraphene. The lack of D-peak in Raman spectra, together with SEM and AFM images, indicate that high quality monolayer to few layer epitaxial graphene fully covering the SiC surface is deposited. The electrical characteristics of the EG channel-devices and the functionality of the bottom gate were examined with 2-probe and 4-probe method. The electrical properties of the FET devices were also investigated with 3 terminal configuration.

Multiple beam-steering for 5G multi-user MIMO mobile fronthaul based on IFoF and RoF transmission

This paper describes the potential of analog radio-over-fiber (RoF) and intermediate-frequency-over-fiber (IFoF) transmission technology for the future mobile fronthaul (MFH). The background and approach of the analog RoF-based MFH combined with the beamforming technique are presented. We developed an antenna module by integrating sixteen sets of cascaded photodiode, RF amplifier and a patch antenna as a compact wireless transmitter. Three millimeter-wave (MMW) beams were successfully transmitted from the antenna module with beam separation of 30° by photonic controlled beam steering. The experimental results are presented to show the feasibility of a multi-user multiple-input multiple-output (MIMO) scenario.

Behavioral modeling and digital predistortion of RF power amplifiers based on time-delay kernel ridge regression

This paper, investigates and presents the behavioral modeling and digital pre-distortion (DPD) of radio frequency power amplifiers (RFPAs) using a time-delay kernel ridge regression (KRR) algorithm. The KRR is an advanced machine learning algorithm that can be effectively used for modeling the baseband characteristics of the RFPA considering both the effects of memory and transistor non-linearity. Compared to the traditional artificial neural network (ANN) based approach which is computationally intensive, the proposed approach using KRR with radial basis kernel function and min-max normalization method, extracts the PA behavioral and DPD model in a short time and yield consistently better results. The performance of the proposed approach in extracting PA and DPD model is demonstrated experimentally on a GaN based class AB power amplifier. The experimental results illustrates that, when compared to ANN based model, the proposed approach yields more accurate PA and DPD models, with an improvement in modeling performance by 2 dB in terms of normalized mean square error (NMSE). In addition, compared to the ANN based approach, the DPD model developed using the proposed approach exhibit improved linearization performance in suppressing spectral regrowth due to PA non-linearity.

Jitter enhanced full digital RF transmitter and PWM RFPA for 5G broadband communications

RFPA (radio frequency power amplifier) based on PWM (pulse width modulation) can be perfect linear without using complicated DPD (digital pre-distortion) hardware. However, PWM RFPA need ultra-high PWM time resolution (less than 10 ps) for wide-band 5G, which is limited by CMOS technologies (can reach 40 ps). It limits the complexity of modulation so that PWM RFPA cannot be really commercialized so far in wideband radio/mobile technologies. This paper presents our contribution by introducing jitter into PWM. For the first time, we demonstrate that jitter can improve the PWM time resolution equivalently reaching less than 2.6 ps. Hence PWM RFPA can be used in 5G supporting 256QAM OFDM modulation based on currently available digital CMOS technologies. We demonstrate that jitter can refine the inherent resolution of PWM hardware circuit modulation. The jitter makes the MCS (modulation and coding scheme) of the bandwidth OFDM system improved from 16QAM to 256QAM in the band n28 of 3GPP 38.101. We also verified that 5G 256QAM OFDM modulation is achievable in the 3GPP band n20, Softbank band28 and NTT Docomo band28. The RMS EVM (root mean square error vector magnitude) of 256QAM OFDM modulation is about −44 dB.

Design of Continuous Class-F Mode Power Amplifier with High Gain Flatness

In this letter, a novel RF power amplifier (PA) with high gain flatness and high efficiency operating in continuous Class-F mode is introduced. Since most continuous Class-F PAs can’t meet the requirement of high gain flatness, a new structure which can achieve high gain flatness is presented. A 1.7-2.5GHz PA is designed, which uses CGH40010F GaN device. Simulation results show that the drain efficiency (DE) of the continuous Class-F PA is between 69% and 79%, output power is more than 41dBm across the whole bandwidth. Gain is between 11dB and 11.8dB, and gain flatness is 0.8dB.

Digital Predistortion Using Extended Magnitude- Selective Affine Functions for 5G Handset Power Amplifiers With Load Mismatch

Load mismatch often occurs in radio frequency (RF) power amplifiers (PAs) in handset, which can complicate the nonlinear behavior of the transmitter, particularly when the voltage standing wave ratio (VSWR) is high. To effectively linearize handset PAs with load mismatch, in this article, we propose a low-complexity digital predistortion (DPD) model. After carefully analyzing the characteristics of handset transmitters with standing waves, we extend the magnitude-selective affine (MSA) function to construct nonlinear modeling terms in the DPD model. The new terms can effectively compensate for the distortion caused by load mismatch. Experimental results demonstrate that the proposed extended MSA (EMSA) model not only improves the modeling performance but also lowers the hardware complexity considerably, compared with the conventional models. The new model can thus serve as a good candidate for DPD deployment in 5G handset transmitters, where nonlinear behavior is more complicated and hardware resource is highly constrained.

Class-E Power Amplifiers Incorporating Fingerprint Augmentation With Combinatorial Security Primitives for Machine-Learning-Based Authentication in 65 nm CMOS

One means by which the security of Internet-of-Things (IoT)-enabled devices may be augmented is through radio-frequency fingerprinting-based authentication methods. As variability in CMOS processes increases with technology scaling, the hardware imperfections that form RF fingerprints can be controlled with small reconfigurable elements, enabling the feasibility of RF fingerprinting as a low overhead security measure for device authentication. To achieve rapid RF identification, we present an inherently secure RF power amplifier and a convolutional neural network-based machine learning classifier through an exploration of combinatorial randomness and self-aware detection mechanisms. By selecting different subsets of thinly sliced power amplifier elements, combinations of random process variations are exploited and updated to form a large search space of distinct RF fingerprints and improve fingerprint prominence. The rich features enabled by augmented device primitives are updated in a time-varying manner to strengthen built-in hardware security. Measurement results demonstrate the effectiveness of this approach at generating distinguishable RF fingerprints across a significant number of configurations.

Self-Sensing Digital Predistortion of RF Power Amplifiers for 6G Intelligent Radio

The future intelligent communication systems will dynamically adjust the transmitted signal according to the radio environment and human behavior, which will lead to the rapid change of the characteristics of power amplifier (PA) and bring new challenges for digital predistortion (DPD). In this letter, a novel self-sensing DPD (SS-DPD) technique is proposed to linearize PA driven by fast time-varied signals. By automatically sensing the features of input signal and integrating them into the neural network, the proposed model is capable of linearizing the PA operated in such time-varied scenarios without updating DPD coefficients. Furthermore, the polynomial basis functions are embedded into neural network to reduce the complexity. Experimental results on a Doherty PA driven by the fast time-varied signal show that the proposed method can achieve good performance constantly with low complexity.