Meenakshi Rawat

Adaptive Digital Predistortion of Wireless Power Amplifiers/Transmitters Using Dynamic Real-Valued Focused Time-Delay Line Neural Networks

Neural networks (NNs) are becoming an increasingly attractive solution for power amplifier (PA) behavioral modeling, due to their excellent approximation capability. Recently, different topologies have been proposed for linearizing PAs using neural based digital predistortion, but most of the previously reported results have been simulation based and addressed the issue of linearizing static or mildly nonlinear PA models. For the first time, a realistic and experimentally validated approach towards adaptive predistortion technique, which takes advantage of the superior dynamic modeling capability of a real-valued focused time-delay neural network (RVFTDNN) for the linearization of third-generation PAs, is proposed in this paper. A comparative study of RVFTDNN and a real-valued recurrent NN has been carried out to establish RVFTDNN as an effective, robust, and easy-to-implement baseband model, which is suitable for inverse modeling of RF PAs and wireless transmitters, to be used as an effective digital predistorter. Efforts have also been made on the selection of the most efficient training algorithm during the reverse modeling of PA, based on the selected NN. The proposed model has been validated for linearizing a mildly nonlinear class AB amplifier and a strongly nonlinear Doherty PA with wideband code-division multiple access (WCDMA) signals for single- and multiple-carrier applications. The effects of memory consideration on linearization are clearly shown in the measurement results. An adjacent channel leakage ratio correction of up to 20 dB is reported due to linearization where approximately 5-dB correction is observed due to memory effect nullification for wideband multicarrier WCDMA signals.

Linearization of Concurrent Tri-Band Transmitters Using 3-D Phase-Aligned Pruned Volterra Model

This paper reports a novel digital predistortion (DPD) scheme for concurrent tri-band power amplifiers (PAs). The proposed tri-band DPD is based on a pruned Volterra model that takes into account the impact of the phase distortion observed in multi-band PAs as well as the compound amplitude distortion. By taking into account the phase variation effects across a wide frequency band, the proposed 3-D phase-aligned Volterra DPD can effectively compensate for the crosstalk effects between the fundamental frequencies, their harmonics, and intermodulation products due to the nonlinearity the tri-band PA exhibited. The performance of the proposed DPD is validated using a broadband Class-AB PA driven concurrently by three independent carrier-aggregated long-term evolution signals at separation frequencies around 100 MHz. The measurement results validate the accurate performance of the proposed 3-D phase-aligned pruned Volterra DPD in suppressing the in-band and cross-band intermodulation effects, and shows improvement over a basic 3-D tri-band DPD model that neglects phase variation effects across frequency.

Compensating I–Q Imperfections in Hybrid RF/Digital Predistortion With an Adapted Lookup Table Implemented in an FPGA

The performance of hybrid RF/digital predistortion (RF-DPD) is limited, due to in-phase (I) and quadrature-phase (Q) imperfection in its key component, the RF vector multiplier, and the associated circuitry. These imperfections cause errors, in terms of implemented gain and phase of the predistortion function. This brief presents the methodology of implementing hybrid RF-DPD with a lookup table (LUT) adapted to compensate for hardware related I-Q imperfections of the RF vector multiplier within the digital signal processing domain. This modified LUT will accurately compensate for I-Q imperfection, without needing a precise tuning of the control voltages at the pins of the RF vector multiplier. This brief also presents the test setup for characterizing the RF-DPD system to obtain the I-Q imperfections within it and utilizes this information to modify the LUT to compensate for these imperfections. To verify the capability of the modified LUT in compensating for the I-Q imperfections, an experimental validation is carried out by linearizing a class-AB base station power amplifier using the hybrid RF-DPD system developed with an Altera Stratix field-programmable gate array (FPGA) evaluation board. In addition to the 12-dB adjacent-channel leakage ratio obtained using static RF-DPD, an improvement of 2.5 dB is achieved using the proposed I-Q compensation technique.

Three-Layered Biased Memory Polynomial for Dynamic Modeling and Predistortion of Transmitters With Memory

This paper proposes a new three-layered biased memory polynomial for behavioral modeling and digital predistortion of highly nonlinear transmitters/power amplifiers (PAs) for 3G wireless applications. The proposed model considers the possibility that the nonlinearity order of the dynamic part of the PA characteristics is different from the nonlinearity order of the static part. For highly nonlinear PAs, the proposed model offers some benefits, such as a low dispersion of coefficients, numerical stability and a low number of coefficients. Moreover, with the measurement setup, better in-band performance is reported. To establish the performance of the linearized PA under realistic conditions, experiments have been carried out for a deep biased class-AB PA and a Doherty PA for various modeling and signal quality norms defined for 3G signals.

A Ray Launching-Neural Network Approach for Radio Wave Propagation Analysis in Complex Indoor Environments

A novel deterministic approach to model the radio wave propagation channels in complex indoor environments reducing computational complexity is proposed. This technique combines a neural network and a 3-D ray launching algorithm in order to compute wireless channel performance in indoor scenarios. An example of applying the method for studying indoor radio wave propagation is presented and the results are compared with a very high resolution fully 3-D ray launching simulation as the reference solution. The new method allows the use of a lower number of launched rays in the simulation scenario whereas intermediate points can be predicted using neural network. Therefore a high gain in terms of computational efficiency (approximately 80% saving in simulation time) is achieved.

Generalized Rational Functions for Reduced-Complexity Behavioral Modeling and Digital Predistortion of Broadband Wireless Transmitters

In this paper, we present and analyze rational-function-based digital predistortion (DPD) of transmitters for broadband applications where system noise and prominent memory effects contribute to the overall nonlinearity of the system. The performance is reported for simulation and measured results for gallium nitride (GaN)-based class-AB and laterally diffused MOS (LDMOS)-based Doherty power amplifiers (PAs) using three different wideband code division multiple access signals with peak-to-average-power ratios of around 10 dB. The performance of the proposed model, in terms of normalized mean-square error, adjacent channel power ratio, matrix condition number, and coefficient dispersion, is compared against those of a memory polynomial (MP) model and a previously proposed rational-function-based model. It is shown by simulation and measurement that the previously proposed absolute-term denominator rational functions have limitations in the inverse modeling needed for DPD. A new variation of the rational function is proposed to alleviate this limitation. Depending on the type of PA and signals, a floating-point operation reduction of 8%-38% is reported as compared with a low-complexity MP model.

Three-Dimensional digital predistorter for concurrent tri-band power amplifier linearization

This paper reports a novel digital predistortion (DPD) scheme for concurrent tri-band power amplifier (PA). The proposed three-dimensional tri-band DPD is based on the analysis of crosstalk between the fundamental frequencies, their harmonics and intermodulation products due to the nonlinearity exhibited by the tri-band PA. The DPD performance is validated using a broadband PA driven concurrently with LTE, WIMAX, and WCDMA signals centered at 2.14 GHz, 2.425 GHz, and 2.655 GHz, respectively.

A Mutual Distortion and Impairment Compensator for Wideband Direct-Conversion Transmitters Using Neural Networks

This paper presents a one-step solution for transmitter nonlinearity estimation and linearization control in the presence of I/Q modulator imperfections for wideband direct-conversion transmitters. These transmitters include power amplifiers with frequency-dependent nonlinearities and modulator imperfections. With the proposed two-hidden-layer feedforward neural network, traditional two-step characterization and specially designed training signals are not required in the parameter estimation stage; and, estimation can be done without interrupting the operation of the transmitter. The measurement results and comparisons of the proposed neural network with the existing state-of-the-art methods show the superior performance in the presence of extreme RF impairments.

Rational Function Based Model for the Joint Mitigation of I/Q Imbalance and PA Nonlinearity

Nonlinearity in power amplifiers and In-phase and Quadrature phase (I/Q) imperfections degrade the performance of direct conversion transmitters. In this letter, a novel rational function based model is proposed to jointly alleviate both these impairments. The performance of the model is evaluated in terms of Normalized mean square error (NMSE) and Adjacent channel error power ratio (ACEPR). Simulation results and measurements show that the model has an improvement of around 2 dB NMSE and around 3 dB in ACEPR than the state of the art parallel Hammerstein based model . Also the model attains a lower complexity while maintaining almost same performance.

Concurrent Dual-Band Modeling and Digital Predistortion in the Presence of Unfilterable Harmonic Signal Interference

Motivated by advanced-generation signals and corresponding trends for multiband, broadband, and ultra-wideband transmitters, several models have recently been proposed for digital predistortion in a dual-band concurrent transmission. These state-of-the-art models assume that two frequencies of operation are uncorrelated and harmonic products can be filtered out. However, when the harmonic of one signal falls on the frequency band of another signal, it cannot be removed with filters. This paper proposes a 3-D harmonic memory polynomial based model for the dual-band concurrent transmission in the presence of harmonic interferences. The model is extracted and predistortion is implemented using a low-cost field-programmable gate-array-based system including a transmitter and a feedback receiver. Using the proposed model, a performance improvement up to 22 dB in terms of normalized mean square error and performance improvement up to 20 dB in terms of the adjacent channel power ratio is achieved compared to a conventional dual-band memory polynomial model not including harmonics.