Comparison and Experimental Verification of Two Low-complexity Digital Predistortion Methods

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.

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.

This paper describes an adaptive digital predistorter (ADP) for RF power amplifier (PA) linearization using an adaptive neuro-fuzzy inference system (ANFIS). The ANFIS predistorter (PD) employs the advantage of real-time modeling of the PA's responses in determining the PD's functions. The amplitude and phase corrections for the PD are represented in an easy-to-understand fuzzy if-then rule, while the parameters involved in the fuzzy representation are trained using neural networks algorithms, namely gradient-descent and least squares estimate (LSE). Experimental results show that a 26.3-dB improvement in linearity for a two-tone signal is obtained, while a distorted WCDMA signal is suppressed by at least 12 dB. The adaptability of the ANFIS PD to instantaneous variation in PA responses through time is also demonstrated, and results show that the ANFIS PD is capable of adapting to simulated environmental changes, which is a topic often omitted by researchers in this area. Further testing demonstrated that the tuning parameters involved in the training could be reduced by more than half for a fairly nonlinear PA without significantly degrading the suppression capability.

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.

Multi-band Orthogonal Frequency Division Multiplexing (MB-OFDM) is an efficient approach for Ultra Wideband (UWB) wireless communication applications. However, the high Peak to Average Power Ratio (PAPR) of MB-OFDM UWB signals, limits the power efficiency of the Solid State Power Amplifier (SSPA) due to nonlinear distortion caused by high PAPR. Hence, it is necessary to reduce the PAPR of MB-OFDM UWB signals. In this paper, we used a tunable Pre-Distorter (PD) based on the High Power Amplifier (HPA) characteristics for PAPR reduction of MB-OFDM UWB signals. The PD configuration is self-tuning, i.e., it can automatically readjust itself by tracking changes in the HPA characteristics with very few (typically two) training symbols. Through Computer simulations, the performance of the predistorter is evaluated in comparison with filtering after clipping, and clipping with turbo coding for PAPR reduction. The Bit-Error Rate (BER) is used as performance measure in this evaluation.

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.

Publication in the conference proceedings of EUSIPCO, Lausanne, Switzerland, 2008

High throughput coherent optical transmitters are key components in future optical communication infrastructure. However, these transmitters are often distorted with the nonlinearity of their components. A potential approach for compensating nonlinearity is by applying digital pre-distortion methods based on the Volterra series or one of its derivatives. However, the Volterra series-based solution is complex to implement, difficult to scale, and its simplified versions may not yield the desired performance. Recently digital pre distortion solutions based on neural networks were proposed, which may benefit from the generality of neural networks and can be more easily scaled. These solutions are often based on non-standard neural network architectures which require complex neurons-based architectures or being based on indirect training approach which suffer from noise enhancement. In this article, a novel method for neural network-based pre-distortion with direct learning is proposed. The direct learning with neural network does not assume a specific transmitter model and does not suffer from noise enhancement. The method assumes standard neural network inference architecture and is applied to a coherent nonlinear optical transmitted with long-short-term memory neural network. The overall performance and complexity of the direct learning method is compared with the indirect approach and with the Volterra series-based solution, showing significant advantage in performance, especially in cases of severe nonlinearity and noise conditions.

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

An adaptive, digital, baseband predistortion (PD) algorithm that compensates for the memoryless nonlinearities of radio-frequency (RF) power amplifiers (PAs) for wireless systems using non-constant-envelop modulation schemes is presented. Compared with the conventional, complex-gain predistorters based on lookup tables (LUTs), the proposed direct-learning, multilevel lookup table (ML-LUT) approach assisted by a hardware-efficient loop delay compensation scheme achieves a significant reduction in convergence time and an improvement in linearization accuracy in the presence of an unknown loopback delay. The experimental results in an FPGA prototyping platform show that the fast adaptation speed enables the predistorter to track time-varying PA nonlinearities as fast as in the tens of kilohertz range, constituting a potential solution for highly efficient PAs in mobile handsets.

Nonlinear effects of a power amplifier (PA) in communications systems include spectral spreading, which causes adjacent channel interference. For predistorter design, it is crucial to employ a model that can sufficiently model the intermodulation distortion (IMD) caused by the PA. The order of IMD generated by a polynomial is determined by its highest order basis. For a piecewise linear function, the order of nonlinearity cannot be directly deduced from its basis function. This paper investigates how IMD is introduced by the simplicial canonical piecewise linear (SCPWL) function. We examine the operation imposed by the SCPWL basis function on sinusoid and multi-tone signal in the time domain and frequency domain. Our analysis results in expressions that can be used to predict the output spectrum of the SCPWL basis. The SCPWL basis operation involves spreading of the input signal spectrum. The output spectrum of each SCPWL basis includes infinite IMD components. The IMD order of the SCPWL model is not determined by the highest order basis. Instead, the number of SCPWL parameters, i.e., the number of linear affine segments that defines the function, determines how accurately it can model the IMD components.

Orthogonal frequency division multiplexing (OFDM) modulation has several attributes which favor it for high speed wireless communications. But its high peak-to-average-power ratio (PAPR) seriously limits the linear range, and hence the power efficiency, of the transmitter's high power amplifier (HPA). The authors present two complementary approaches to the solution of this problem. The first approach uses an adaptive nonlinear predistorter (PD) to compensate for the nonlinearity in the HPA. The analytical expressions used, for the HPA and the corresponding PD, lead to satisfactory overall system operation up to the saturation region of the HPA, under rapidly time-varying conditions. The second approach reduces the PAPR to an acceptable range by means of a decision-oriented modification of the partial transmit sequence (PTS) technique. It uses a decision tree in seeking the best trade-off between the high-performance/high-complexity behavior of the ordinary PTS algorithm and the low-performance/low-complexity behavior of the iterative flipping PTS (IF-PTS) algorithm

This paper presents the novel design and analysis of a 25 W broadband Class-AB GaN HEMT-based power amplifier working over 0.9–1.7 GHz. A large signal model of the Wolfspeed-make GaN HEMT CG2H40025 has been used in this design. The comprehensive design process has been carried out with the help of the Advanced Design System software by Keysight. Instead of conjugately matching the load and source impedance obtained from load-pull analysis of a nonlinear model of CG2H40025, the value of load and source impedance has been tuned with the help of a novel design approach of an ideal matching design approach. Thus, to achieve an output power of more than 25 W and a flat large signal gain of 15.425 ± 0.375 dB, a novel design approach has been employed to create input and output matching networks, maintaining a lower Q value results in broad bandwidth and for determining the load and source impedances. The circuit has been fabricated on Roger’s substrate RO4350B having a dielectric constant of 3.66 and a loss tangent of 0.0031. The unique design approach based on electromagnetic simulation of the circuit at each design step yielded experimental results that agreed very well with the simulated results. The fabricated power amplifier achieves a power-added efficiency of over 54.78% and a drain efficiency of over 55.45% throughout the entire frequency range. It also delivers a maximum output power of 32.18 W at 1.3 GHz. This power amplifier is developed for L-band Foliage Penetrating Radar.

Theoretically, memoryless nonlinear effect is the main concern for RF power amplifier (PA) modelling and analysis. However, the latest generation wireless communication systems, such as Wi-Fi, WiMAX and LTE, using wider bandwidth, add new problems for the analysis of RF PAs, which is the memory effect associated with the bandwidth. The memory effect causes additional distortion to the PA and affects the performance of digital predistortion (DPD) design. Previously, we predicted the memoryless spectrum regrowth of a PA related to its intercept points up to arbitrary high order for a few of wireless communication signals, such as TDMA, CMDA and OFDM. In this letter, we propose a simplified Hammerstein structure-based method to consider the memory effect as well in order to analyse the nonlinear characteristic of PAs more precisely and completely. The simplification greatly reduced the complexity of classic Hammerstein system identification for PAs. The result will be useful in the analysis of RF PAs with memory effect and the proposed PA model is intended to be used in predistorter design for modern wideband wireless communication systems.