Feedback Quantization in Crosscorrelation Predistorters

Amplification of signals with fluctuating envelopes inevitably leads to distortion because of nonlinear behavior of the power amplifier (PA). Digital predistortion can counteract these nonlinear effects. In this letter, the crosscorrelation predistorter is described and the effects of quantization in the feedback path are presented. One of the effects is that the quantization noise is correlated with the signal to be quantized, resulting in reduced performance of predistortion. A technique to reduce these effects is to inject a dither signal before quantization. Because of the quantization noise and dither signal, more data has to be used to obtain estimates of the PA behavior that are accurate enough for effective predistortion

A crosscorrelation predistorter using memory polynomials

Amplification of signals with fluctuating envelopes inevitably leads to distortion because of nonlinear behavior of the power amplifier (PA). Digital predistortion can counteract these nonlinear effects. In this paper, a digital predistortion architecture is presented which is based on the calculation of correlation functions using coarsely quantized signals. The crosscorrelation functions are transformed to the frequency domain and the spectra are used to calculate the coefficients of the predistorter memory polynomial. This method has reduced complexity and slightly improved average performance in comparison with existing schemes

Analysis of Power Amplifier Modeling Schemes for Crosscorrelation Predistorters

Amplification of signals with fluctuating envelopes leads to distortion because of non-linear behavior of the Power Amplifier (PA). Digital Predistortion can counteract these non-linear effects. A crosscorrelation predistorter is a digital predistorter, based on the calculation of crosscorrelation functions using coarsely quantized signals. The crosscorrelation functions are transformed to the frequency domain and the spectra are used to calculate the coefficients of the predistorter memory polynomial. This method has reduced complexity and equivalent performance in comparison with existing schemes. In this paper, four alternative schemes to implement a crosscorrelation predistorter are analyzed. The PA characteristics can be determined either directly or indirectly using ’normal’ or orthogonal polynomials giving four alternatives. All four alternatives give significant reduction of Adjacent Channel Interference

A Low Complexity NARX Structure using Indirect Learning Architecture for Digital Pre-Distortion

In this paper, we demonstrate a nonlinear autoregressive with exogenous input (NARX) DPD technique which is more compact, less computationally intensive and less susceptible to errors caused by noise in the PA output compared to an equivalent memory polynomial based DPD. Experimental validation is performed with a 20 MHz LTE signal for a GaN Doherty power amplifier

Action: Baseline Channel Model for SCCC-X and DVB-S2X

This paper analyzes the impact to the error performance of very high-order modulations, specifically 256APSK and 128APSK, in the DVB-S2X and SCCC-X proposals due to transmitter distortions, i.e. phase and amplitude imbalance, amplification non-linearities, and phase noise. The receiver is assumed to be a matched filter with angle derotation capabilities. An exact theoretical prediction is developed as well as supporting simulations is provided

Memory polynomial with binomial reduction in digital pre-distortion for wireless communication systems

One of the biggest power consuming devices in wireless communications system is the Power Amplifier (PA) which amplifies signals non-linearly when operating in real-world systems. The negative effects of PA non-linearity are energy inefficiency, amplitude and phase distortion. The increases in transmission speed in present day communication technology introduces Memory Effects, where signal spreading happens at the PA output, thus causing overhead in signal processing at the receiver side. PA Linearization is therefore required to counter the non-linearity and Memory Effects. Digital Pre-distortion (DPD) is one of the outstanding PA Linearization methods in terms of its strengths in implementation simplicity, bandwidth, efficiency, flexibility and cost. DPD pre-distorts the input signal, using an inversed model function of the PA. Modelling of the PA is therefore vital in DPD, where the Memory Polynomial Method (MP) is used to model the PA with memory effects. In this paper, the MP method is improved in Memory Polynomial using Binomial Reduction method (MPB-imag-2k). The method is simulated using a modelled ZVE-8G Power Amplifier and sampled 4G (LTE) signals. It was found MPB-imag-2k is capable of achieving comparable anti-scattering/anti-distortion in MP for non-linearity order of 3, memory depth of 3 and pre-amplifier gain of 2

Cancellation of Power Amplifier Induced Nonlinear Self-Interference in Full-Duplex Transceivers

Recently, full-duplex (FD) communications with simultaneous transmission and reception on the same channel has been proposed. The FD receiver, however, suffers from inevitable self-interference (SI) from the much more powerful transmit signal. Analogue radio-frequency (RF) and baseband, as well as digital baseband, cancellation techniques have been proposed for suppressing the SI, but so far most of the studies have failed to take into account the inherent nonlinearities of the transmitter and receiver front-ends. To fill this gap, this article proposes a novel digital nonlinear interference cancellation technique to mitigate the power amplifier (PA) induced nonlinear SI in a FD transceiver. The technique is based on modeling the nonlinear SI channel, which is comprised of the nonlinear PA, the linear multipath SI channel, and the RF SI canceller, with a parallel Hammerstein nonlinearity. Stemming from the modeling, and appropriate parameter estimation, the known transmit data is then processed with the developed nonlinear parallel Hammerstein structure and suppressed from the receiver path at digital baseband. The results illustrate that with a given IIP3 figure for the PA, the proposed technique enables higher transmit power to be used compared to existing linear SI cancellation methods. Alternatively, for a given maximum transmit power level, a lower-quality PA (i.e., lower IIP3) can be used.Comment: To appear in proceedings of the 2013 Asilomar Conference on Signals, Systems & Computer

An LMS-based adaptive predistorter for cancelling nonlinear memory effects in RF power amplifiers

This paper presents the design of an adaptive Digital Predistorter (DPD) for Power Amplifier (PA) linearization whoseimplementation and real time adaptation can be fully performed in a Field Programmable Gate Array (FPGA). The distinctive characteristic of this adaptive DPD is its straightforward deduction from a Nonlinear Auto Regressive Moving Average (NARMA) PA model and the possibility to be completely implemented in a FPGA without the need of an additional digital signal processor performing the DPD adaptation. The adaptive DPD presents a NARMA structure that can be implemented by means of Look-Up Tables (LUTs). This configuration results in a Multi-LUT implementation where LUT contents are directly updated by means of an LMS algorithm. Details on the internal adaptive DPD organization as well as its linearization capabilities are provided, taking into account memory effects compensation

A Low Complexity Partial Transmit Sequence for Peak to Average Power Ratio Reduction in OFDM Systems

Partial transmit sequence (PTS) is one of the most important techniques for reducing the peak to average power ratio (PAPR) in OFDM systems. This paper presents a low complexity PTS scheme by applying a new phase sequence. Unlike the conventional PTS which needs several inverse fast Fourier transform (IFFT) operations, the proposed technique requires half IFFT operations only at the expense of slight PAPR degradation. Simulation and results are examined with QPSK modulation and OFDM signal and power amplifier with memory effects