Linearization Of RF Power Amplifiers Research Articles

Recursive Neural Network With Phase-Normalization for Modeling and Linearization of RF Power Amplifiers

Recursive Neural Network With Phase-Normalization for Modeling and Linearization of RF Power Amplifiers

EFFICIENCY ANALYSIS OF SWITCHING CONVERTER-MODULATOR

The article discusses methods of highly efficient linear RF power amplifier and transmitter design for future 5G/6G networks. Based on a consideration of various known methods for constructing high-efficiency power amplifiers, the prospects of developments using the envelope elimination and restoration (EER, or Kahn method) and envelope tracking (ET) method are substantiated. The prospects for implementing PWM switching converter-modulator for these methods are assessed. Based on the evaluation calculations performed, it is shown that this structure can potentially be used as an EEP/ET modulator for a number of 5G/6G applications and will have advantages over structures using class AB amplification.

Phase-Normalized Neural Network for Linearization of RF Power Amplifiers

Phase-Normalized Neural Network for Linearization of RF Power Amplifiers

Parallel Delta-Sigma Modulator-Based Digital Predistortion of Wideband RF Power Amplifiers

In this article, we propose a new robust and highly efficient digital predistortion (DPD) concept for the linearization of wideband RF power amplifiers (PAs). The proposed approach is based on the combination of a parallelized delta-sigma modulator (DSM) and a forward model of the PA. This concept applies multi-rate techniques on a DSM that incorporates the forward PA model in its feedback loop to perform the required signal predistortion. Such a technique eliminates the need of reverse modeling and its associated problems. The multi-rate approach relaxes enormously the clock speed requirement of the DPD, which allows handling high signal bandwidths at feasible sampling rates. Moreover, enhanced performance can be achieved without the need of increasing the order of the modulator which reduces the sensitivity of the system to gain variations and phase distortions caused by the nonlinear PA characteristics. Three time-interleaved parallel DPD (P-DPD) variants are described and introduced, all of them have been shown to offer increased accuracy, and consequently better linearization performance compared to the DSM-based DPD state-of-the-art. The proposed architectures are tested and assessed using extensive real-world RF measurements at the 3.6 GHz band utilizing wideband 100 MHz 5G New Radio (NR) transmit waveforms, evidencing excellent transmit signal quality.

Design-Aware Parasitic-Aware Simulation Based Automation and Optimization of Highly Linear RF CMOS Power Amplifiers

In this paper, a parasitic-design-aware simulation-based design tool is proposed for highly linear RF power amplifiers. The main aim of the proposed tool is to speed up the design process of RF power amplifiers. In addition, it provides accurate final designs taking into consideration the effect of parasitic components of both active and passive devices. The proposed tool relies on the knowledge of designing highly linear RF power amplifiers. Both the optimization steps and design methodology are presented in this paper. The proposed tool is verified by designing a highly linear RF power amplifier at three different frequencies (7 GHz, 10 GHz, and 13 GHz) using 65 nm technology node. The results show that an OP1 dB higher than 18 dBm, gain/S21 higher than 7 dB, and OIP3 higher than 24 dBm at 6 dB back-off power can be obtained.

Sparsely Gated Mixture of Experts Neural Network For Linearization of RF Power Amplifiers

Sparsely Gated Mixture of Experts Neural Network For Linearization of RF Power Amplifiers

Switch-Mode MOSFETs for Class A Radio Frequency Amplification

Vertical double diffused MOSFETs (“VDMOSFETs”) developed for switching power supplies were successfully used in high voltage, high frequency linear amplifier circuits. These high voltage power switches are surprisingly useful for linear RF power amplifiers and transmitters. In most of their intended applications such as in switching power supplies or switched digital amplifiers, VDMOSFETs are pulsed by a high voltage and the pulsed output is heavily filtered. This avoids the linear region of the VDMOSFET, which normally limits the efficiency to a theoretical maximum of 25%. However, in a search of MOSFETs for high voltage linear amplification using Class A bias without heavy use of filtering, these low-cost switching MOSFETs were found to work best, if limited to radio frequencies above 1.5 MHz. Conditions, and in particular, very low impedance driving of the MOSFET gate, were discovered that gave efficiencies of 70%, rivaling that of non-linear pulse techniques such as Class C or Class D operation. The beneficial effect of linear operation combined with high efficiency at a high voltage is suggested to arise from Miller capacitance. This was only seen at radio frequencies and with the larger current, higher gate capacitance devices. Switching MOSFETs as described here should be considered alongside dedicated RF MOSFETs such as the more expensive LD (lateral diffused) MOSFET when working with RF power.

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.

Mixture of Experts Approach for Piecewise Modeling and Linearization of RF Power Amplifiers

Piecewise behavioral models are commonly adopted for modeling and linearization of RF power amplifiers (PAs) that exhibit strong amplitude-dependent nonlinear distortion characteristics, as global polynomial approximations tend to underperform in such scenarios. In this article, we consider a new piecewise model for PAs based on the mixture of experts (ME) approach, which builds on a probabilistic model that allows the different submodels to cooperate—as opposed to operating in an independent fashion that is commonly the case in existing reference methods. We first introduce the ME framework theory while also extend it such that it can be applied to model complex baseband signals and nonlinearities. Then, we show how the ME model allows overcoming some of the intrinsic shortcomings that existing piecewise behavioral models commonly exhibit, which translates into improved modeling accuracy and improved linearization performance. Furthermore, the extension of the ME approach to a tree-structured regression model, referred to as the hierarchical ME model, is also introduced and shown to provide further performance improvements over the basic ME approach. The proposed solutions are validated with extensive RF measurements, covering both PA direct modeling and digital predistortion (DPD)-based linearization, on a gallium nitride (GaN) load-modulated balanced PA, on a GaN Doherty PA, and on a class AB GaN high electron mobility transistor PA, while being compared against several state-of-the-art piecewise methods. The results demonstrate that the ME framework-based models outperform the state of the art.

A Highly Efficient Linear Multimode Multiband Class-J Power Amplifier Utilizing GaAs HBT for Handset Modules

This article presents the design techniques for a multimode multiband (MMMB) linear RF power amplifier (PA) with a high efficiency, suitable for wireless handset multichip modules. The PA operates with high efficiency at the saturated output power and maintains high linearity with an enhanced efficiency at the back-off power. It is, thus, able to operate in multimodes (saturated/linear) and covers multibands (814-915 MHz; bands: 5/8/18/19/20/26) without reconfiguration, representing a novel solution for the converged PA module architecture to reduce the number of PAs within the handset. A new technique to the handset industry, class-J, is adopted to improve the efficiency while maintaining the linearity. To the best of our knowledge, this work provides the first implementation of the class-J using the GaAs heterojunction bipolar transistor (HBT) technology in the multichip PA modules. The utilization of the GaAs HBT adds more degrees of freedom to enhance the linearity. A PA module, consisting of a GaAs HBT die mounted on a four-layer laminate, is designed. The die is fabricated using the flip-chip technology. The output matching network and the control/bias network are fabricated on the laminate using the printed inductors and the surface-mount device (SMD) capacitors. The results validate the design techniques, showing 2G power added efficiency (PAE) 62%, 2.5G error vector magnitude (EVM) ≤ 3%, and 3G adjacent channel leakage ratio (ACLR) of 5MHz ≤ -35 dBc. The design achieves a higher PAE than other reported reconfigurable and complex MMMB PAs, with comparable linearity.

On Segmented Predistortion for Linearization of RF Power Amplifiers

On Segmented Predistortion for Linearization of RF Power Amplifiers

Novel Drain-Connected Field Plate GaN HEMT Designs for Improved V BD–R ON Tradeoff and RF PA Performance

TCAD studies are performed to develop physical insights into the breakdown behavior of drain-connected field plate-based GaN HEMTs. Using the developed insights, to mitigate the performance bottleneck caused by the lateral drain-connected field plate design, we have proposed novel vertical-field-plate designs. The proposed designs alleviate the channel electric field by uniformly distributing it vertically into the GaN buffer region. As a result, the proposed vertical and dual-field-plate design offer ${2} \times $ and ${3} \times $ improvements in breakdown voltage, respectively, compared with the design without field plate. Similarly, compared with a design with a lateral field plate, a 50% improvement in the breakdown voltage was seen with dual-field-plate architecture. RF power amplifier (PA) performance extracted using load-pull simulations demonstrates an improved RF PA linearity at higher drain bias, improved output power, efficiency, and PA gain for HEMTs with dual- and vertical-field-plate designs.

Behavioral Modeling and Linearization of Wideband RF Power Amplifiers Using BiLSTM Networks for 5G Wireless Systems

Characterization and linearization of RF power amplifiers (PAs) are key issues of fifth-generation wireless communication systems, especially when high peak-to-average ratio waveforms are introduced. Recently, deep learning methods have achieved great success in numerous domains including wireless physical-layer. However, there has been limited work in using deep learning for PAs behavioral modeling and linearization. In this paper, we make a bridge between memory effects of the nonlinear PAs and memory of bidirectional long short-term memory (BiLSTM) neural networks. We then build a BiLSTM-based behavioral modeling architecture and its accompanying digital predistortion (DPD) model by reconciling a non causality concern. Next, an additional model is proposed in this paper to mitigate uncertainty of the tested PA when transforming phases. The experimental results demonstrate the effectiveness of the proposed scheme, in which the adequately trained networks are capable of characterizing the PA, and the artificial intelligence-based DPD shows promising linearization performance when considering the tested PAs inherent unpredictability.

RF Power Amplifier Linearization in Professional Mobile Radio Communications Using Artificial Neural Networks

This paper is focused on the linearization of the radio frequency power amplifier of a professional digital handheld by means of an artificial neural network. The simplicity of the neural network that is used, together with the fact that a feedback path is unnecessary, makes this solution ideal to reduce both the cost of a handheld and its hardware complexity, while fully maintaining its performance. A compensation system is also needed to keep the linearization characteristics of the neural network stable against frequency, temperature, and voltage variations. The whole solution that comprises both the neural network and the compensation system has been implemented in the digital signal processor of a real handheld and afterward fully tested. It has proved to be satisfactory to meet the telecommunication standard requirements in all frequency, temperature, and voltage ranges under consideration while efficient to lower the computational cost of the handheld and to make its internal hardware simpler in comparison with other traditional linearization techniques. The results obtained demonstrate that a neural network can be used to linearize the power amplifiers that are used in transmitters of telecommunication equipment, leading to a significant reduction of both their hardware cost and complexity.

High-Precision Joint In-Band/Out-of-Band Distortion Compensation Scheme for Wideband RF Power Amplifier Linearization

In this letter, a high-precision joint in-band/out-of-band (OOB) distortion compensation scheme is proposed to overcome the large modulated bandwidth issue for wideband radio frequency power amplifier linearization. It is achieved by dividing the linearization process into in-band predistortion and OOB suppression, respectively. Experimental results have proven that high-accuracy compensation can be realized by this scheme and the required bandwidth of the in-band and OOB distortion can be controlled flexibly, leading to significant reduction of the system bandwidth requirements.

Low-Cost RFin–RFoutPredistorter Linearizer for High-Power Amplifiers and Ultra-Wideband Signals

The 5G and beyond systems require the highly efficient linear power amplifier (PA) at the base station to deliver promised data rate in a power efficient manner. To facilitate higher data rates in future 5G communication, the demands for the wideband signals are continuously increasing, which creates adversity in employing digital predistortion (DPD) for the linearization of RF PA in ultra-wideband systems. System bandwidth constraint of the conventional DPD does not provide sufficient linearization of wideband signals. In this paper, we present two types of predistorter, first is RFin-RFout analog predistorter, in which linearization is performed by RF components in the analog domain, and the second is hybrid RF predistorter which takes the advantage of advanced DSP platform for improving the performance of RFin-RFout analog predistorter. The proposed predistorters eliminate the constraint on the system bandwidth of the conventional DPD. The requirements of data converters and reconstruction filters are relaxed in the analog predistorter (APD) architecture, whereas hybrid digitally controlled (HDC) APD eliminates the need of analog components by compensating the delay digitally. In order to validate this concept, a ZX60V-63+ PA from minicircuits is tested with 160-MHz eight-component carrier-long term evolution signal. The proposed APD architecture is able to deliver an adjacent channel power ratio (ACPR) of -46.4 dBc with an ACPR improvement of 13.4 dB at 1-dB back-off. Furthermore, with digital intervention, modified model, HDC-APD further provides a significant improvement in the linearization performance and delivers an ACPR of -53.5 dBc with an ACPR improvement of 20.5 dB.

A low-power high-performance digital predistorter for wideband power amplifiers

In this paper, we present a low-power high-performance digital predistorter (DPD) for the linearization of wideband RF power amplifiers (PAs). It is based on the novel FIR memory polynomial (FIR-MP) predistorter model, which significantly augments the performance of the conventional memory polynomial predistorter with the use of complex baseband digital FIR filter prior to the memory polynomial. The adjacent channel leakage ratio (ACLR) performance comparison between the conventional MP and the proposed FIR-MP is done based on simulations with multi-carrier modulated signals of 20 and 80 MHz bandwidths. The PA models used for the simulations are extracted from the measurements of a commercial $$1\,\hbox {W}$$ GaAs HBT PA. At the ideal system-level simulations, the improvements in ACLR over the conventional MP are 7.2 and 15.6 dB, respectively, for 20 and 80 MHz signals. The choice of selection of various parameters of the predistorter along with the subsequent digital-to-analog converter (DAC) is presented. The impact of fixed-point representation is assessed using ACLR metrics, which shows that a wordlength of 14 bits is sufficient to obtain ACLR beyond $$45\,\hbox {dBc}$$ with a margin of $$10\,\hbox {dB}$$ . The proposed predistorter is synthesized in $$28\,\hbox {nm}$$ fully-depleted silicon-on-insulator (FDSOI) CMOS process. It is shown that with a fraction of the power and die area of that of the MP a huge improvement in ACLR is attained. With an overall power consumption of 8.2 and 88.8 mW, respectively, for 20 and 80 MHz signals, the FIR-MP DPD proves to be a suitable candidate for small-cell base station PA linearization.

An accurate digital baseband predistorter design for linearization of RF power amplifiers by a genetic algorithm based Hammerstein structure

In this paper, a novel digital predistorter design based on the Hammerstein structure is proposed in order to linearize radio frequency power amplifiers. A genetic algorithm optimization method has been proposed to accurately identify the coefficients of a Wiener model for the power amplifier. Digital predistorter design based on the proposed Hammerstein model has been carried out according to the accurate Wiener model. The validation of the suggested model is carried out using the simulation of the power amplifier and the digital predistortion excited by 64QAM signals in the advanced design system software. According to the simulation results, the criterion of an adjacent channel power ratio decreased by about 16 dB. The simulation results show the adjacent channel power ratio of almost − 46 dBc. In order to assess the feasibility of the proposed predistorter, it is completely implemented in the Kintex FPGA using Vivado HLS. This proposed model enables a more accurate modeling of nonlinear distortion and memory effects compared to the previous linearization methods. This paper presents the new linearization method using the genetic algorithm based Hammerstein structure.

Robust Modeling and Linearization of MIMO RF Power Amplifiers for 4G and 5G Applications

In this paper, a novel set of orthogonal crossover polynomials for the baseband modelling and linearization of MIMO RF Pas is presented. The proposed solution is applicable to WCDMA and LTE applications. The new modelling approach has considerably reduced the numerical instability problem associated with the conventional polynomial model identification. In order to validate the efficiency and the robustness of the proposed solution, a 2x2 MIMO LDMOS RF power amplifier has been measured modelled and linearized. A comparison with the conventional polynomial MIMO models showed clearly the superiority of the proposed solution in a fixed-point calculation environment such as DSP and FPGA boards.

Progress of the Linear RF Power Amplifier for Mobile Phones

Progress of the Linear RF Power Amplifier for Mobile Phones