A Fast Digital Predistortion Algorithm for Radio-Frequency Power Amplifier Linearization With Loop Delay Compensation

Most existing behavioral models of the radio frequency (RF) power amplifiers assume that power amplifiers are memoryless devices. But in broadband communication systems, memory effects of the RF power amplifiers are significantly observed. The traditional memoryless models can no longer accurately depict the input-output relationship of power amplifiers. This paper investigates power amplifiers memory effects and a pre-distortion method is proposed for linearizing RF power amplifiers with memory effects. A valid behavioral model based on the Volterra series is suggested to treat memory effects. Since the characteristics of amplifiers change during transmission time, a recursive least squares algorithm with size- fixed observation matrices is developed to update the parameters of the proposed power amplifiers model. The identification algorithm can decrease computational complexity and data storage space and facilitate real-time online identification. Simultaneously, the pre-distortion model is constructed to simulate. Simulation results show that the proposed method can effectively compensate for the nonlinear distortion and memory effects of RF power amplifiers. The model's accuracy is used to evaluate power amplifiers memory effects by the enormalized mean square error (NMSE). In the end, simulation and evaluation of this pre-distortion system proceeded, and the power spectral density estimation was also applied to calculate the adjacent channel power ratio.

The nonlinearity of power amplifiers is one of the principal reasons degrading the transmission quality in the wireless communication systems comprising the single-carrier frequency-division multiple access (SC-FDMA) utilised for the up-link in the LTE system. In this letter, we analysed and predicted the nonlinearity of SC-FDMA signals in spectrum respect. Owing to the nonlinearity of radio frequency (RF) power amplifiers, an analytic model is established on the basis of a third-order intercept point (), which is fit for weakly nonlinear systems and devices. The research results confirm that the spectrum regrowth with RF power amplifier is specified and measured efficiently. This sort of design inherits the advantages of orthogonal frequency division multiplexing (OFDM) and is of great help for both designing RF power amplifiers and further improving the spectrum regrowth with pre-distortion outside channels, extended to other wireless systems based on SC-FDMA modulation.

Predistortion (PD) lineariser for microwave power amplifiers (PAs) is an important topic of research. With larger and larger bandwidth as it appears today in modern WiMax standards as well as in multichannel base stations for 3GPP standards, the relatively simple nonlinear effect of a PA becomes a complex memory-including function, severely distorting the output signal. In this contribution, two digital PD algorithms are investigated for the linearisation of microwave PAs in mobile communications. The first one is an efficient and low-complexity algorithm based on a memoryless model, called the simplicial canonical piecewise linear (SCPWL) function that describes the static nonlinear characteristic of the PA. The second algorithm is more general, approximating the pre-inverse filter of a nonlinear PA iteratively using a Volterra model. The first simpler algorithm is suitable for compensation of amplitude compression and amplitude-to-phase conversion, for example, in mobile units with relatively small bandwidths. The second algorithm can be used to linearise PAs operating with larger bandwidths, thus exhibiting memory effects, for example, in multichannel base stations. A measurement testbed which includes a transmitter-receiver chain with a microwave PA is built for testing and prototyping of the proposed PD algorithms. In the testing phase, the PD algorithms are implemented using MATLAB (floating-point representation) and tested in record-and-playback mode. The iterative PD algorithm is then implemented on a Field Programmable Gate Array (FPGA) using fixed-point representation. The FPGA implementation allows the pre-inverse filter to be tested in a real-time mode. Measurement results show excellent linearisation capabilities of both the proposed algorithms in terms of adjacent channel power suppression. It is also shown that the fixed-point FPGA implementation of the iterative algorithm performs as well as the floating-point implementation.

Two differential radio frequency (RF) power amplifier (PA) architectures are presented in this paper both of which can be used to implement a wideband Doherty PA. Classic PA architecture is compared to a SB (SB) PA in order to determine an architecture that offers the widest input impedance match without external component tuning. Both amplifiers presented in this paper have been designed to output an average of 10.5 dBm of continuous wave (CW) power with 1.8 V supply. The classic PA architecture is tuned to 1.9 GHz central frequency by external components and has a bandwidth of 500 MHz at S11=−10 dB. The SB PA architecture has an operating range spanning from 0.8 GHz to 2.2 GHz at S11=−10 dB. SB PA has a higher power added efficiency (PAE) at output compression point (OR-P1dB) in the whole 1.2 GHz–2.4 GHz range by 3 %–7 % with a peak efficiency of 31 %. The presented results indicate that a SB RF PA architecture can be implemented designing a wideband Doherty PA.

The burst-mode transmitter has been proposed as an efficiency enhancement technique for signals with high peak-to-average-power ratios (PAPRs), where appropriate modulation schemes such as pulse-width modulation (PWM) are used to generate a switching signal to drive the radio frequency (RF) power amplifier (PA). Ideally, a PWM signal is of infinite bandwidth, however, high-frequency spectral components are attenuated, e.g., by the bandlimitation of the PA matching network or the PWM circuit itself. Bandlimitation introduces ripples in the signal amplitude, which might reduce the PA efficiency in burst-mode operation. In this paper, we show that a bandlimited PWM signal does not necessarily degrade the overall transmitter efficiency because of the higher coding efficiency. The coding efficiency of bandlimited PWM signals, i.e., PWM signals with a finite number of harmonics, is derived analytically and verified by measurements. Additionally, from the measurements, we exemplarily determine the number of harmonics for bandlimited PWM signals with the best transmitter efficiency-linearity trade-off, and therefore demonstrate the excellence of bandlimited PWM for burst-mode transmitters in terms of transmitter efficiency as well as transmission signal quality.

The design of a temperature compensating bias circuit applicable to GaAs HBT radio frequency (RF) power amplifiers (PAs) is presented. It is developed by adding a simple voltage-compensation circuit to the existing base bias circuit. It is applied to a stage bypass RF PA and the experimental results show that the quiescent current (Q-current) remains nearly unchanged over a temperature range between −30–85°C, which markedly improves the linearity of the PA at low temperatures.

We have developed a high-speed pipelined superconductor look-up table to generate programmable predistortion functions for direct linearization of radio frequency (RF) power amplifiers. The look-up table comprises an address decoder and a memory matrix with throughput above 10 GHz. The decoder performs code-matching of each input word and its conversion into a row address of the memory matrix. We discuss different possible implementations of the address decoder, including a preferred one for integrated circuit implementation. The memory matrix consists of RS flip-flops with nondestructive readout connected in series for slow-speed contents writing. Each row of the memory matrix contains a number, which can be read out by signal from the decoder. We present the design and the results of experimental evaluation of the look-up table and its components.

It has been challenging for a wireless sensor node to realize long-range real-time information feedback in the low power harvesting scenarios, due to the limited power budget. In this article, a sensor node powered by low radio frequency (RF) power harvesting is proposed with long-communication capability without using an RF power amplifier or external power source. The proposed sensor node is capable of rectifying input RF power as low as −20 dBm at 433 MHz, while simultaneously generating a 866 MHz second harmonic during the harvesting process. To address problems of long-range data transmission, the generated harmonic is amplified by a tunnel diode powered by rectified dc power, while carrying sensor data of temperature, humidity, and CO2 concentration. The fabricated sensor node shows an output power of around −14.75 dBm for the second harmonic, even with an injecting RF power as low as −20 dBm. It enables a long range exceeding 40 m for indoor communication scenarios with a low energy consumption of just 20.7 mJ. The sensor node demonstrates a great potential for future internet of things (IoT) applications in low RF power harvesting scenarios.

In this work, a new particle swarm optimization (PSO) method with dynamic nonlinear self-adaptive hyperparameters (DNSHs) (PSO-DNSHs) is proposed for radio frequency (RF) power amplifier (PA) design. The theory and advantages of this method are described and analyzed. Based on the proposed PSO-DNSH method, a multioctave PA and a broadband pseudo-Doherty load-modulation balance amplifier (PD-LMBA) are designed. The multioctave single-ended PA achieves an output power exceeding 40.3 dBm, a drain efficiency greater than 60.9%, and a gain of over 10.3 dB between 0.5 and 3.6 GHz. While the broadband PD-LMBA shows a saturated output power of 41.1–43 dBm, a saturation drain efficiency of 57.7%–77.6%, a 6-dB output power back-off (OBO) DE of 47.3%–64.6%, and a 10-dB OBO DE of 51.2%–68.4%. Compared with other existing PSO-based methods, the results demonstrate that the proposed method not only achieves better performance for both PAs, but also shows faster convergence capability. Modulated signal tests along with the digital predistortion (DPD) are also conducted for both PAs, 20-MHz 5G new radio (NR) signal with 6- and 10-dB peak-to-average power ratios (PAPRs) are used for single-ended PA and PD-LMBA, respectively. Excellent linearity is achieved for both PAs.

Linear amplification using nonlinear components (LINC) is a method of vector summing two constant amplitude phase-modulated signals to achieve power amplification. The theoretical efficiency of the LINC power amplifier has been reported as 100% since highly efficient nonlinear constant amplitude amplifiers can be used. However, the 100% efficiency performance is only possible at one or two loads along the power output curve. The bulk of the papers regarding LINC has focused on clever implementations of the signal vector decomposition as well as methods to achieve highly linear signal separation. There has been little regard in the literature to the signal combiner implementation necessary to achieve the high power-added efficiency (PAE) of the LINC radio frequency (RF) power amplifier. Efficiency is not an intrinsic property of the combiner implementations, however, the combiner method is the single biggest contributor to efficient performance of a LINC RF power amplifier. This paper develops an analysis method that determines the efficiency of the LINC power amplifier as a function of the amplitude modulation statistics. This can be employed to design the RF communication system amplitude modulation characteristics and to tradeoff and optimize the RF transmitter PAE.

An adaptive digital predistortion (PD) technique is proposed for linearization of power amplifiers (PAs) in multiple-input multiple-output (MIMO) transmitters. Instead of constructing a separate feedback path at each PA, we propose a PD technique based on a combined feedback, which adds all the PAs' outputs to form a single feedback. We develop an algorithm for finding the multiple PA characteristics jointly from the combined feedback. The PD parameters are calculated from the identified PA characteristics. Although the proposed method requires more computations for PA identification than the conventional method, its hardware implementation is much simpler and can overcome the crosstalk problem of a radio frequency (RF) selector, which is necessary for multiple feedback selection. The simulation results show that, despite its simple structure, the linearization performance of the proposed method is almost the same as the separate multiple feedback method.

Dynamic load modulation (DLM) is a technique for increasing radio frequency (RF) power amplifier (PA) efficiency when amplifying amplitude modulated signals. It does this by manipulating a tuneable matching network (TMN) between the PA and the antenna in harmony with the envelope of the transmitted signal. The TMN is usually based on varactor diodes, requiring control voltages with up to 100 V peak-to-peak swing. Conventional off-the-shelf op-amps cannot produce a big enough voltage swing at sufficient speed, especially when amplifying modern communications standards like the 3GPP 4G Long Term Evolution (LTE). The discrete current mirror driver amplifier described here capable of producing 50V peak-to-peak voltage swing. When the driver amplifier was combined with a suitable RF PA and TMN, 46.0% DC-to-RF efficiency was achieved at 33.9 dBm output power (POUT) with a 1.4 MHz LTE signal. The adjacent channel power ratio (ACPR) was -40 dBc, confirming that the current mirror amplifier is suitable for LTE use.

This paper presents a novel technique of modeling a radio frequency (RF) power amplifier (PAs) using polynomials with infinite impulse response (IIR) bases functions. Non-linear PA behavior, including both short-term and long-term memory effects, is described with very few parameters compared to existing Volterra series models. Moreover, the use of polynomials with IIR bases is far less computationally intensive thereby providing a significant advantage over competing methods. Power amplifiers designed for second generation (EDGE) wireless system are investigated for model validation. Excellent results are obtained, where the error between model prediction and measurements is better than 50 dBc, with the amplifier being driven with an EDGE signal at several power levels.

Wireless sensing and communication for space exploration in areas inaccessible to human often suffer from severe performance degradation due to the cryogenic effects on the transmitters’ circuits. To survive extreme temperatures, programmable radio frequency (RF) power amplifiers (PA) can be built into the transmitter, and intelligent PA controllers need to be integrated into the system to interact with the environment and restore the PA’s functionalities. This problem can be modeled as the controller acts (control the PA) in an environment to maximize the reward (signal quality), and it is most suitable to use reinforcement learning as a solution. This paper presents a cryogenic and energy-efficient reinforcement learning (RL) module on Field Programmable Gate Arrays (FPGA) that can directly program the PA. By characterizing a self-healing PA in a liquid nitrogen environment, we generated an RF signal data set and built an interactive RL environment to model the PA’s behaviors across its configurations and cryogenic temperatures down to −197°C. We developed a deep RL model with a high generalization capability introduced by the neural networks to control the PA and restore its performance. The RL model with fixed-point training and inference is implemented on FPGA to survive the cryogenic conditions and carry out fast and low-power training and inference for PA control. All functionalities of the programmed FPGA operate correctly in the cryogenic testing environment.

A new dynamic behavioral modelling technique, based on support vector regression (SVR), is presented in this paper. As an advanced machine learning technique, the SVR method provides an effective option for behavioral modeling of radio frequency (RF) power amplifiers (PAs) including the nonlinear and memory effects. In this paper, the basic theory of the proposed SVR modelling method is provided, along with details on model implementation of RF PAs. Experimental test example for a LDMOS PA is presented, revealing that the new modelling methodology provides a very efficient and extremely accurate prediction.