Adaptive Neuro-Fuzzy Inference System (ANFIS) Digital Predistorter for RF Power Amplifier Linearization

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.

This letter presents a new digital adaptive predistorter\n\t\t\t\t (PD) for power amplifier (PA) linearization based on a nonlinear\n\t\t\t\t auto-regressive moving average (NARMA) structure. The distinctive\n\t\t\t\t characteristic of this PD is its straightforward deduction\n\t\t\t\t from the NARMA PA model, without the need of using an indirect\n\t\t\t\t learningapproachto identify the PD function.The PD itself presents\n\t\t\t\t a NARMA structure, and hence it can be quickly implemented by\n\t\t\t\t means of lookup tables. Single and multicarrier modulated signals\n\t\t\t\t collected from a three-stage LDMOS class AB PA, with a maximum\n\t\t\t\t output power of 48-dBm CW have been used to validate the\n\t\t\t\t linearity performance of this new predictive predistorter.

A platform of high accuracy and reliability is crucial for power amplifier (PA) designers to assess the characteristics of the PA prototype, and for the digital predistorter engineers to validate their models and algorithms. Digital processing techniques for building a test bed of high performance for PA characterization and predistortion (PD) are discussed in this article. We also proposed a novel technique to characterize the frequency responses of the vector signal generator and vector signal analyzer independently without using any other instrument. The techniques described in this article are quite useful, especially for narrowband vector transmitters and receivers, to improve their performance. These techniques were experimentally evaluated, both for characterization and PD of a class-F PA. Test results show that using such techniques can successfully build a test bed of high accuracy and wide bandwidth. © 2012 Wiley Periodicals, Inc. Int J RF and Microwave CAE, 2013.

In this paper, we propose a hybrid domain framework to model the predistorter (PD) of a power amplifier (PA). It is available for obtaining the PD not only through a PA model but also a PA circuit on ADS. Simulation results show that with predistortion, the NMSE of the linearity can reach -50 dB and the ACPR can reduce around 17dB. What's more, a processing unit is designed to work with the PD, so that the PD's coefficients can adjust to the changes of the PA adaptively, making the PA perform great linear in the transmitter system. The proposed framework is a helpful guidance for the design of circuits.

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.

Recently, many papers have been published on the designs of predistortion systems for power amplifiers (PA). Most of these studies are based on computer simulations. In this work, we examine our predistorter (PD) designs on a practical microwave PA in a laboratory setup. The objective is to validate two PDs of different design approaches. The first PD is modeled using a simplicial canonical piecewise linear (SCPWL) function while the second one is modeled using a polynomial function. The former exploits the properties of the SCPWL function to develop a reduced complexity PD identification method. The latter utilizes the secant method to iteratively search for the signal at the PD output, thus parameter identification is avoided. The implementation complexity and effectiveness of the PDs are compared. The limitations of the measurement system for predistorter design is also discussed briefly

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.

We have developed a new adaptive digital predistortion (DPD) linearization technique based on analog feedback predistortion (FBPD). The lookup-table-based feedback input can remove the bandwidth limitation of the feedback circuit related to the loop delay, and suppress feedback oscillation by accurate digital control of the feedback signal. Moreover, the predistortion (PD) signal can be extracted very efficiently. By combining the feedback linearization and DPD linearization techniques, the performance of the predistorter is enhanced significantly compared to the conventional DPD. To clearly visualize the characteristics of digital FBPD (DFBPD), we have compared it to the conventional DPD based on the recursive least square algorithm using Matlab simulation. The results clearly show that the new method is a good linearization algorithm, better than a conventional DPD. For the demonstration, a Doherty power amplifier with 180-W peak envelope power is linearized using the proposed DFBPD. For a 2.14-GHz forward-link wideband code-division multiple-access signal, the adjacent channel leakage ratio at 2.5-MHz offset is -58 dBc, which is improved by 15 dB at an average output power of 43 dBm

Digital predistortion (DPD), based on complex-valued memory polynomials (MP), is established as an efficient method for power amplifier (PA) linearization. The DPD facilitates compliance of the telecommunication infrastructure to strict standard specifications (transmit spectrum mask (TSM), error vector magnitude (EVM), bit error rate (BER), [Formula: see text]) by making PA more linear, while at the same time reduces the running cost of the wireless infrastructure (at both Base Transceiver Station (BTS) and User Equipment (UE) sides) by making PA more power efficient. Even when DPD is utilized, signals with high peak-to-average power ratio (PAPR) produce out-of-band PA spectrum emission due to intermodulation products affecting all above-mentioned critical standard specified parameters. The novelty proposed in this paper is as follows. PA is restricted to operate within “reasonably above” PA linear region using PAPR reduction technique. The residual nonlinearity is taken care of by DPD. The combination of DPD and PAPR PA linearization methods is implemented on software-defined radio board. The necessary steps for efficient PA linearization are presented, compensating both out-of-band and in-band signal distortions. We achieved EVM = 2.0%, ACPR [Formula: see text]50[Formula: see text]dBc, at 10[Formula: see text]W LTE modulated PA output, antenna point and PA output power of 39.5[Formula: see text]dBm.

Currently the purchases of drugs at Instalasi Farmasi RSU (IFRS) HKBP Balige are based on the examination of the amount of drugs usage. The purchases of drugs based on the examination of the amount of drugs usage cause frequent unplanned drugs purchases that must be hastened (cito) and purchases to other pharmacies. The purchases of cito and purchases to other pharmacies will inflict a financial loss to the patients, because when IFRS makes drugs purchases of cito or to other pharmacies, the cost of the drugs will be more expensive. Therefore, in this research, a prediction of drugs stock in IFRS HKBP Balige using Adaptive Neuro Fuzzy Inference System (ANFIS) will be carried out. ANFIS is a combination of Least Square Estimator (LSE) and Error Back Propagation (EBP) algorithms. ANFIS consists of forward pass and the backward pass learning. The sample data used to predict drugs stock in this research is data of drugs sales at the IFRS HKBP Balige from 2013 to 2015. From the results of drugs stock prediction research with ANFIS, obtained that number of errors of ANFIS model is 5.52%. Based on MAPE accuracy level evaluation, number of errors have an excellent rate so that it can be concluded that the predicted results of the drugs stock are good.

A hybrid neuro-fuzzy static var compensator stabilizer for power system damping improvement in the presence of load parameters uncertainty

Digital pre-distortion techniques are widely utilized in linearization of RF power amplifiers. In this paper recurrent neural networks are used to model an inverse function of the power amplifier. This function predistorts an input signal in digital domain in order to increase the linearity of the modeled power amplifier. The simulation results are presented.

Over the past twenty years or so there has been much interest in the use of digital pre-distortion techniques for the linearization of RF and microwave power amplifiers. This paper presents a snapshot of the current challenges posed by demands for wider bandwidth and lower power consumption, and some potential solutions.

Bandwidth constraints pose significant challenges to linearization of wideband RF power amplifiers (PAs) with digital predistortion (DPD). A recently proposed band-limited DPD scheme uses a band-limited modeling technique to eliminate the bandwidth constraints and reduce DPD implementation cost. However, time consuming convolution operations are involved for model extraction in this time domain data based band-limited modeling method. In this article, band-limited model extraction is formulated as a generalized least squares problem and investigated from a frequency domain perspective. A frequency domain data based model extraction method is proposed, which greatly reduces the computational complexity for extracting band-limited DPD model parameters. A 10 W GaN HEMT inverse class-F PA excited by a 20 MHz four-carrier WCDMA signal and a 40 MHz two-carrier LTE signal is tested to validate the method. Experimental results show that the computationally efficient frequency domain data based model extraction method for band-limited DPD provides as good linearization performance as the time domain data based method. © 2013 Wiley Periodicals, Inc. Int J RF and Microwave CAE 24:412–420, 2014.

An H-infinity approach to RF power amplifier (PA) linearization is presented. The proposed technique provides increased robustness to fabrication process variations while accounting for large signal effects. H-infinity robust feedback methods are applied that guarantee stability in the face of bounded uncertainty. With this feedback technique known variations are considered in the design process in an a priori manner. A Cartesian feedback loop is used to demonstrate the feasibility of the approach to RF PA linearization. The proposed method accounts for the uncertainty as an integral part of the design process, thus addressing the process variation in a predetermined manner and providing a powerful tool for robust design.