This paper proposes a transfer learning neural network (TLNN) approach for digital predistortion (DPD) of mm-Wave active phased arrays (APA) operated under variable signal bandwidth regimes. Compared with the conventional artificial (ANN) method, proposed can achieve similar linearization performance much lower computational complexity by transferring part trained model from one to another band...

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 ...

In this article, a sparse-Bayesian treatment is proposed to solve the crucial questions posed by power amplifier (PA) and digital predistorter (DPD) modeling. To learn model, advanced Bayesian framework includes group of specific processes that maximize likelihood measured data: regressor pursuit identification, coefficient estimation, stopping criterion, deselection. The relevance vector machi...

The subject of this paper is the compensation for nonlinearities in digital communication systems by means of predistortion. In this work, we apply the Generalized Cerebellar Model Articulation Controller (GCMAC) to simplify and accelerate the predistorter convergence. The range of analyzed predistorters includes: 1) a symbol-rate data predistorter that, for a given time span, achieves a simila...

Wireless communications are accelerating into the realm of higher data rates from hundreds of megabits to tens of gigabits per second. Increase in data rate requires higher throughput and higher utilization of spectral bandwidth. At the same time, we are seeing a demand for smaller chipsets with lower power budgets. Digital basebands with increased energy-efficiency are needed while fitting wit...

Digital predistortion of nonlinear systems is an important topic in many practical applications. This paper considers direct predistortion of a Volterra system by connecting in tandem an adaptive Volterra predistorter. The coefficients of the predistorter can be recursively estimated using the nonlinear filtered-x least mean squares (NFxLMS) algorithm. In this paper, the prediction error method...

Digital predistortion is an effective means to compensate for the nonlinear effects of a memoryless system. In case of a cellular transmitter, a digital baseband predistorter can mitigate the undesirable nonlinear effects along the signal chain, particularly the nonlinear impairments in the radiofrequency (RF) amplifiers. To be practically feasible, the implementation complexity of the predisto...

Digital compensation of nonlinear distortion due to nonlinear characteristic of electronic or electromechanical device is becoming more and more important. This paper considers Direct Learning Architectures (DLAs) for predistortion of nonlinear systems described using Volterra series. The adaptive predistorter which is connected in tandem with the nonlinear system can be modeled as a Volterra f...

It is well known that power amplifier induced nonlinear distortions produce a signal spectral regrowth at the transmitter output of digital radio communication systems. This effect is responsible for both adjacent channel interference and BER degradation. Signal predistortion is a technique that counteracts such phenomena. Technological advances in the last decade, renewing the interest in this...

A linearized digital radio frequency (RF) power amplifier (PA), a switched RF PA, is more power efficient than an analog amplifier, but may cause interference in adjacent transmitting channels similar to analog amplifiers. This interference is due to the inherent nonlinearities, and this project investigated the possibility of reducing this interference by using a prefilter, a predistorter, to ...